The DataWeave Blog

Category: Regions

  • Turning Headwinds Into Wins: How Brands Can Navigate Price, Share, and Visibility Amid Tariff Disruption

    Turning Headwinds Into Wins: How Brands Can Navigate Price, Share, and Visibility Amid Tariff Disruption

    Disruption Is Now the Baseline

    Tariffs can spike landed costs overnight, regulations rewrite labelling rules, and competitors slash prices before your team finishes its daily stand-up. And yet, some consumer brands thrive.

    The winning brands see changes early, decide quickly, and execute flawlessly across the digital shelf. This post blends three decades of pricing and merchandising expertise with timely digital shelf insights from DataWeave, offering a clear path forward for brands navigating today’s volatile retail environment.

    From Cost Shock to Chronic Uncertainty

    Tariffs are no longer just one-off headlines; they’ve become an unpredictable, ongoing variable in the global marketplace. The true challenge isn’t always the duty rate itself, but the constant whiplash of not knowing if, when, or how much that duty will change. This pervasive uncertainty is having a tangible impact:

    • Market Uncertainty: Tariff talk alone disrupts planning and fuels market instability.
    • Operational cost inflation: Shifting trade rules raise expenses across sourcing, freight, and distribution.
    • Compromised SKU-level Margin: The profitability of individual products is under constant threat.
    • Shrinkflation: Brands shrink product quantities to mask rising costs, risking consumer trust.

    Unpredictable Competitive Response: Delaying price moves while watching competitors can erode margins as much as tariffs.

    To stay ahead, pricing decisions must be stress-tested against multiple tariff scenarios and aligned with likely competitor reactions. Timing matters as much as accuracy, move too soon or too late, and margins suffer either way.

    The Tariff Math No One Can Afford to Get Wrong

    When it comes to tariff disruption, the difference between profit and loss often hinges on a precise understanding of a three-step process. Get any part of this chain wrong, and the financial ripple effect can undermine pricing and promotions. The duty you pay, therefore, is the direct result of the following three critical steps:

    Step 1: Harmonized System (HS) Code

    • What it is: A six- to ten-digit classifier that drills down to product sub-types.
    • Why it matters: A single digit change can shift an item into a higher-tariff bracket.

    Step 2: Country of Origin

    • What it is: The nation in which the imported item was made.
    • Why it matters: Mis-tagging the origin can lead to mis-pricing and inaccurate margin calculations.

    Step 3: Trade-Agreement Overlay

    • What it is: Differentiation between the World Trade Organization (WTO) baseline tariffs and special trade agreements (e.g., USMCAUnited States-Mexico-Canada Agreement).
    • Why it matters: The same HS code can result in significantly different duties, up to a 10% swing, depending on the originating country (see the example below).

    This isn’t just about paying the correct duty; it’s about safeguarding your bottom line in a global marketplace where every digit and every designation carries substantial weight.

    The wrong origin, the wrong rule, the wrong margin.

    Hard Numbers: Where Prices Are Already Climbing

    DataWeave’s latest digital shelf analysis shows import-driven price inflation diverging sharply by source country.

    The intricate dance of HS codes, country of origin, and trade agreements directly translates into the prices consumers see. And the data doesn’t lie. Below, we delve into the hard numbers: where prices are already climbing, as illuminated by DataWeave’s latest digital shelf monitoring, showing significant import-driven price inflation by source country.

    • China: Products sourced from China are up 5%. This is largely attributable to the numerous tariffs currently imposed on Chinese goods.
    • Mexico: Prices for products from Mexico have risen by 3%.
    • United States: Interestingly, even U.S.-sourced products show a 3% increase.
    tariff price increases

    This rise in U.S. product prices might seem counterintuitive if tariffs are solely focused on imports. However, the reality lies in the global supply chain for many products.

    Consider guacamole as an example: While the final product might be “Made in the USA,” its components often come from various international sources. Avocados might be imported from Mexico, lime juice from Central America, and seasonings from India or China. Even packaging could originate in Asia. Each of these imported components can be subject to tariffs. Therefore, even if an item is assembled in the U.S., the tariffs on its constituent parts contribute to an overall price increase, explaining the rising rates for U.S.-sourced goods.

    Action step: Map tariff exposure at both finished-goods and component-level to avoid “Made in USA” blind spots.

    Timing Is a Competitive Weapon

    With duty tables and competitor reactions changing fast, the question is: move first or follow? Early movers recoup cost fastest but risk overshooting if tariffs ease; laggards may enjoy a brief price advantage but suffer sudden margin compression.

    The Strategic Dilemma

    The table below illustrates this strategic choice and its potential outcomes:

    Shrinkflation: Margin Patch or Trust Erosion?

    Beyond direct price adjustments, many brands are turning to shrinkflation to manage tariff-driven cost pressure, shaving net weight instead of hiking prices. DataWeave’s analysis reveals an average package reduction of 5 – 6%, with extreme cases reaching 15 – 25%, sometimes even coupled with a shelf-price increase.

    While this can cushion immediate margin, it comes at a significant cost: brand credibility. Savvy shoppers quickly spot these changes, sharing “before-and-after” photos online and fueling consumer frustration. What begins as a margin patch can rapidly erode trust and damage long-term loyalty.

    Ultimately, navigating this volatile environment requires dynamic intelligence and a holistic pricing strategy that balances profitability with market share and, crucially, consumer trust.

    Price Hikes May be Inevitable, But You Can Still Run Your Digital Shelf

    Tariff‑driven cost pressure can force list‑price increases, but it does not dictate how well your products show up, sell through, or satisfy shoppers online. Those outcomes still hinge on five levers that live entirely inside your control. Master them and you cushion margin hits while protecting (or even expanding) share.

    The Five Levers of Digital‑Shelf Control

    • Inventory Depth – Maintain online in‑stock rates above 95 percent for high‑velocity SKUs and flag substitute logic when unavoidable out‑of‑stocks occur.
    • Content Quality & Accuracy – Keep titles keyword‑rich, imagery crisp, and attributes complete so search filters never bury you.
    • Ratings & Reviews Cadence – Proactively request fresh reviews to earn retailer search boosts and reassure value‑conscious shoppers.
    • Retail‑Media Precision – Bid where pages are healthy and in‑stock; pause spend on broken listings that leak conversion and ROAS.
    • Fulfillment Excellence – Monitor pick‑pack accuracy, on‑time delivery, and substitution rates; each one influences retailer algorithmic visibility.

    Content Hygiene Keeps You Visible, Compliant, and Conversion-Ready

    Missing or incorrect product attributes (e.g., “gluten-free,” “caffeine content”) can swiftly jeopardize both regulatory compliance and your product’s fundamental search visibility. Simply put, if it’s not labeled right, it won’t be found.

    This impact plays out in two crucial areas:

    1. Retailer Search Visibility: Filter logic on major e-commerce platforms like Target.com, Walmart.com, and Instacart is increasingly driven by precise attribute tags (e.g., “gluten-free,” “BPA-free,” “0g added sugar”). Fail to provide or correctly format these claims, and your product will simply never appear when shoppers apply these critical search filters. You become invisible to a motivated audience.
    2. Regulatory Compliance: Global regulatory bodies, including the U.S. FDA and EU authorities, now treat online product detail pages as officially regulated labeling space. This means that a single missing allergen statement or an inaccurate nutritional claim can trigger severe consequences, from product takedowns and hefty fines to a devastating “straight-to-zero” share of search. Non-compliance isn’t just a legal risk; it’s a direct threat to your market presence (see example below).

    The Hygiene Playbook: Audit → Score → Fix → Grow

    Your Product Detail Pages (PDPs) are your digital storefronts, and they need to be impeccable. Modern content-intelligence tools are like vigilant auditors, constantly scanning, structuring, and scoring every PDP across your retail network.

    Tools like DataWeave do the heavy lifting by:

    • Surfacing critical gaps: They’ll pinpoint issues like blurry images, inaccurate titles, or missing nutrition information.
    • Optimizing for search: They ensure your product attributes align with live search filters, turning claims into clicks.
    • Flagging compliance risks: You’ll know about potential issues before regulators or retail partners ever do.
    • Quantifying your impact: Get a clear Content Quality Score that your teams can own and improve, week after week.

    When you execute this well, it’s not just about tidying up; it’s a powerful growth engine. This proactive approach fuels every step of the digital customer journey – from getting found, to winning the click, converting the cart, and ultimately, capturing reviews that boost your search rankings.

    A Case Study: Bush’s Beans Converts Visibility into Revenue

    Before Bush’s Beans achieved rapid success with their “audit → scorecard → rapid-fix” approach, they confronted a significant hurdle. Here’s how they overcame it to drive impressive revenue growth.

    The Challenge

    Bush’s Beans saw its e-commerce contribution stall at just 1.5 percent while competition in canned goods intensified. A quick audit revealed three root causes:

    1. Dipping online sales that signalled slipping visibility and conversion.
    2. Fragmented product content across major retailer sites as images, titles, and claims were inconsistent or missing altogether.
    3. Heavier category competition  making it harder to hold first-page search positions.

    The Fix

    The brand adopted DataWeave’s Digital Shelf Analytics to create a single source of truth for every PDP. A lean internal team then:

    • Ran content audits across priority retailers to surface incomplete or non-compliant attributes.
    • Prioritized quick wins focusing on high-velocity SKUs where simple edits (e.g., adding pack-size keywords or allergy statements) would unlock search filters.
    • Tracked progress weekly using an automated scorecard to keep everyone focused on the next set of fixes.

    The Win

    Twelve months later the numbers told the story:

    Bush’s Beans transformed their product data into a strategic asset, significantly improving online visibility, safeguarding brand reputation, and driving sustained revenue growth. Accurate and complete product pages ensured compliance and boosted search rankings, directly increasing sales. While you can’t control external factors like tariffs, you can control the quality and compliance of your product pages and that control directly translates margin pressure into market share gains.

    Unified Insight: Turning Signals into Sustained Advantage

    Imagine one living dashboard where every digital shelf signal like timely price moves, share-of-search shifts, retail media spend, on-shelf availability gaps, compliance flags, MAP breaches, plus content and review health flows together. With that single lens, the “whose numbers are right?” debate disappears and cross-functional teams can act in minutes rather than days.

    A consolidated feed lets you:

    • Build market awareness: Spot competitor price changes as they happen, understand who owns first-page search, and measure the true lift of retail media campaigns.
    • Mitigate emerging risks: Surface impending out-of-stocks before rank erodes, catch claim or label errors ahead of audits, and receive instant alerts when a seller breaks MAP.
    • Activate growth levers: Prioritize content edits that open search filters and use ratings and reviews trends to fine-tune messaging and assortment.

    Brands that weave these signals into one workflow move faster than the disruption. That’s the connective tissue highlighted in our recent post on pairing Digital Shelf Analytics with Marketing-Mix Modelling: when granular shelf data sits beside strategic performance metrics, smarter decisions follow.

    A platform like DataWeave brings the pieces together quietly ingesting millions of price checks, availability reads, and PDP audits each day, then presenting only the next best actions. The payoff is simple: sharper market awareness, lower operational risk, and growth that compounds with every iteration.

    Keep Moving, Keep Winning

    Tariffs, evolving regulations, and agile competitors are no longer storms; they are the climate. Brands that pair a clear, shared insight stream with rapid execution turn volatility into durable advantage. Keep your data united, keep iterating on the five digital-shelf levers, and every new headwind becomes another step ahead.

  • Bridging the Gap: How Digital Shelf Analytics Empowers Marketing Mix Modelling for Smarter Brand Decisions

    Bridging the Gap: How Digital Shelf Analytics Empowers Marketing Mix Modelling for Smarter Brand Decisions

    Marketing Mix Modeling (MMM) has been a cornerstone of marketing analytics for decades: first as a service offered by large consultancies like Nielsen and IRI, and later as software solutions from NielsenIQ and Ekimetrics. By 2024, some 64% of senior marketing leaders had already adopted and used MMM solutions.

    However, despite this widespread adoption, MMM faces significant limitations in our fast-moving digital marketplace. According to Gartner, opaque pricing models and siloed data integration remain substantial barriers to actionable insights from these tools. Most critically, traditional MMM often misses vital variables influencing consumer behavior, such as:

    • Competitor price drops and promotions
    • Product availability issues and stockouts
    • Negative review trends and sentiment shifts
    • Search ranking fluctuations

    These blind spots must be addressed to unlock the full value of MMM investments and make truly informed marketing decisions.

    The Critical Data Gap In Traditional MMM

    Traditional MMM solutions expose brands to considerable risk, especially in the CPG and retail space. The fundamental challenge lies in MMM’s reliance on lagging indicators for essential metrics like historical sales and ad spend. Data inputs may be months or quarters old before they’re used for scenario analysis.

    That’s like making million-dollar marketing decisions while only looking in the rearview mirror when you need to watch the road ahead simultaneously.

    MMM tools also typically overlook external market factors that can dramatically impact performance. In today’s retail landscape, where market conditions change rapidly, being blind to real-time competitive dynamics creates significant vulnerability. Key external factors that traditional MMMs fail to capture include:

    • Competitor moves: Price changes, promotions, content updates
    • Consumer sentiment: Review trends, ratings, social engagement
    • Market dynamics: Stockouts, search ranking shifts, category growth

    How Digital Shelf Analytics Completes The Picture

    This is where Digital Shelf Analytics (DSA) plays a crucial complementary role. Brands and retailers leveraging DSA gain insights into real-time market dynamics that MMM alone cannot provide. However, brands using DSA in isolation often struggle to quantify how digital shelf improvements directly impact revenue. Answering questions like “Did better product content drive sales, or was it the influencer campaign?” remains challenging.

    Bridging these disconnected platforms requires intentional integration and a DSA platform that can feed intensively cleaned and organized data into existing MMM platforms. With the right data inputs, companies establish a powerful feedback loop for agile, data-driven decisions.

    A comprehensive DSA solution like DataWeave provides granular, actionable data on critical external variables such as:

    • Daily or weekly competitor pricing movements and promotional activity
    • Product content standardization and optimization across retailers
    • Review sentiment trends and potential reputation issues
    • Share of search/shelf performance relative to competitors

    When merged with established MMM capabilities, DSA creates a complete picture that fills the blind spots holding marketing teams back from maximizing ROI.

    The DSA + MMM Advantage in Retail Media

    The popularity of retail media networks has further amplified the need for integrated DSA and MMM approaches. These advertising platforms, operated by retailers, allow brands to display targeted ads to shoppers across digital properties based on first-party customer data and purchase insights.

    The retail media revolution has transformed e-commerce pages into sophisticated search engines for product discovery. This evolution has been so impactful that retail media ad revenue surged 16.3% in 2023, reaching $43.7B in the U.S., with continued growth projected.

    Major platforms like Walmart have expanded their retail media networks to capitalize on closed-loop attribution. Since retailers own the entire customer journey, they can track everything from ad impression to purchase on their e-commerce sites. This creates a significant advantage through accurate ROI measurement, unlike traditional advertising where attribution remains challenging.

    How DSA Enhances Retail Media Optimization

    With retail media emerging as a top-performing sales channel, brands need sophisticated optimization strategies. Every brand wants to maximize visibility and performance across individual eCommerce sites, just as they optimize for Google or emerging AI platforms.

    Integrating digital shelf analytics into marketing mix models enables brands to:

    • Allocate ad spend more intelligently using real-time competitive insights
    • Identify timely campaign activation opportunities in response to market changes
    • Monitor organic ranking trends to strategically time paid promotional activities
    • Measure true campaign impact on digital shelf performance metrics

    For example, when a competitor launches an aggressive price drop in your category, DSA provides visibility into this change. This intelligence can trigger recommended campaign adjustments, such as increased sponsored ad bidding in affected categories. Traditional MMM alone cannot deliver this level of responsive optimization.

    How to Integrate DSA into MMM: A 3-Step Framework

    Digital Shelf Analytics for Marketing Mix Modeling - 3 Step Framework

    Here’s how to integrate your Digital Shelf Analytics into your Marketing Mix Models to start making better data-driven decisions for your brand.

    Step 1: Map DSA Variables to MMM Inputs

    Begin by mapping specific DSA variables to your static MMM inputs. Ensure that competitors are properly configured for monitoring in your DSA platform and that metrics like price changes and search ranking positions are linked with your MMM’s models.

    This integration is crucial because traditional MMM models rely exclusively on historical data for forecasting. Adding real-time inputs delivers several benefits:

    • More accurate elasticity curves reflecting current market conditions
    • Better understanding of root causes behind demand shifts
    • Prevention of misattributing sales changes to your marketing activities when external factors may be responsible

    At DataWeave, our comprehensive coverage spans 500+ billion data points, 400,000 brands, and 1,500+ websites, ensuring brands never miss a competitor move and maintain complete visibility across the connected e-commerce landscape.

    Step 2: Feed High-Quality DSA Data into MMM Platforms

    Next, integrate critical digital shelf metrics into your MMM framework:

    • Review and sentiment scores and trends
    • Content quality measurements
    • Competitive positioning data
    • Price gap analytics
    • Search ranking performance

    DataWeave employs a rigorous data accuracy validation process to ensure teams work with the cleanest, most reliable data possible. Our sophisticated processing pipeline removes anomalies and standardizes information across retailers, providing the consistent, high-integrity data foundation that robust marketing mix modeling demands.

    Step 3: Validate and Iterate

    A powerful DSA solution helps measure whether your marketing efforts achieved their intended impact on the digital shelf. Use your DSA platform to assess campaigns’ actual effect on key performance indicators:

    • Do promo-driven sales lifts correlate with improved search rankings?
    • How do content improvements impact conversion rates?
    • What is the relationship between paid media and organic visibility?

    DataWeave enables users to correlate metrics across the entire consumer journey, from awareness through post-purchase. Rather than focusing solely on short-term spikes, brands can measure lasting impacts on digital shelf health. This end-to-end visibility empowers teams to make increasingly informed decisions with each campaign cycle.

    Executive Decision Support in Uncertain Times

    It is no surprise to anyone that we are living through volatile times. Executives may be uncomfortable if they cannot provide their teams with strategic direction based on data or the tools they need to accelerate their workdays.

    By integrating DSA with MMM, companies gain early warning signals about market shifts, enabling smarter resource allocation during budget constraints. This integration helps organizations move from tactical execution to strategic direction by:

    • Providing cross-channel impact analysis to understand the full marketing ecosystem
    • Equipping category managers with tactical optimization tools that support broader strategic objectives
    • Identifying competitive threats before they impact sales
    • Forecasting potential ROI impacts across various spending scenarios

    These capabilities help prevent wasted ad spend, missed opportunities, and lost sales.

    Future-Proofing with DSA-Driven MMM

    Several emerging trends highlight the growing importance of DSA-enhanced marketing mix modeling:

    • Trend 1: Navigating Economic Volatility – Brands can use DSA to track how competitors adjust pricing in response to cost shocks like tariffs and inflation. This real-time intelligence directly improves MMM’s inflation modeling accuracy.
    • Trend 2: AI-Powered Predictive Insights – Combining DSA trend detection (such as viral product reviews or sudden inventory fluctuations) with MMM helps forecast demand spikes from otherwise unforeseen events.
    • Trend 3: Automated Optimization – Smart campaign activations and adjustments based on real-time DSA triggers drive efficiency. DataWeave’s vision includes an automated retail media intelligence layer that optimizes spend across channels based on integrated insights.

    DataWeave’s Unique Advantage

    At DataWeave, we’ve seen our digital shelf analytics customers significantly improve their organic search rankings because of better-sponsored ad campaigns. What makes our approach to DSA-MMM integration uniquely powerful? Our platform is specifically designed to address the challenges of modern marketing mix modeling:

    • Superior data refresh rates ensure timely insights when they matter most
    • Unmatched marketplace coverage across more than 1,500 eCommerce sites globally
    • Advanced data normalization that standardizes metrics across disparate categories and retailers
    • API-first architecture enabling flexible data access and utilization

    Conclusion – From Hindsight to Foresight

    In the past, companies relied primarily on historical data for their marketing mix models. Today’s market leaders are incorporating digital shelf analytics to unlock superior insights, improve decision accuracy, and drive measurable ROI.

    DataWeave serves as the essential bridge between MMM systems and real-time, comprehensive market intelligence. When DSA and MMM work together, brands gain a complete picture: MMM shows precisely what happened, while DSA explains why it happened—and together, they reveal what’s coming next.

    Ready to transform your marketing mix modeling from hindsight to foresight? Contact us today to discover how our Digital Shelf Analytics can enhance your existing MMM investments and drive measurable business results.

  • Standard Reporting vs. Competitive Intelligence: What Retail Leaders Need to Know

    Standard Reporting vs. Competitive Intelligence: What Retail Leaders Need to Know

    Back in the day, pricing strategies were a lot easier. These days, not only do teams need to have robust standard price reporting workflows, but they also need to have the know-how and tools to gain and act on competitive intelligence. Retail leaders should prioritize automation and strategic thinking and ensure their teams have the tools, processes, and methodologies required to monitor the competition at scale and over the long term.

    Retail leaders who recognize the distinction between standard reporting and competitive intelligence are more likely to gain team buy-in, especially when developing pricing strategies that drive results. You can’t be everywhere at once, but you can optimize pricing strategies to stay ahead of the competition.

    This article has everything you need to know about the differences between standard reporting and competitive intelligence and how to use both to make your teams more effective than ever!

    Understanding the Distinction

    Standard price reporting is much like checking the weather to see if it’s stormy before grabbing a raincoat or sunhat. You need to do it to make essential, everyday choices, but it will not help you predict when the next storm is coming. Standard price reporting deals more with the short-term and immediate actions needed as opposed to long-term strategy.

    Don’t get us wrong, standard price reporting is still an essential responsibility of a pricing team’s function—but there’s more to it. It is also lower-tech than a competitive intelligence strategy and can rely on route heuristics.

    Think of it as data-in, data-out. It deals with pricing operations like:

    • Weekly price movements: Seeing which competitors, product categories, and individual items had pricing shifts in the short-term
    • Basic price indices: Outlining benchmarks to watch how your own, and your competitors’, products are trending in the market
    • Price competitiveness metrics: Setting thresholds that show whether your products are priced below, above, or equal to your competition for general trend reporting

    Standard price reporting is fundamental for operational teams that manage price adjustments in the short term. It can also help teams remain agile and reactive to market condition changes.

    It’s likely that your team already has standard reporting strategies or tools to help them with tactical execution. But are they harnessing competitive intelligence correctly with your help?

    Characteristics of Competitive Intelligence

    While standard price reporting is like checking the weather, competitive intelligence is like being a meteorologist who measures atmospheric changes, predicts storms, and scientifically analyzes weather patterns to keep everyone informed and in the know.

    Competitive intelligence goes well beyond simply tracking price movements and benchmarking them against a single set of standards. Competitive intelligence helps steer teams in a strategic direction based on insights from the market. It can drive long-term business success and is one of your best tools to ‘steer the ship’ as a retail leader.

    Here are some of the essential elements of competitive intelligence:

    • Strategic insights: Including but not limited to understanding your competitors’ pricing strategy, promotions, and product positioning
    • Market-wide patterns: Identifying trends based on geography, product category, or individual SKU across retailers to inform broader strategies
    • Long-term trends: Taking historical market and competitor data and combining it with real-time retail data to predict future price movements as shifts in consumer behavior to inform pricing strategies

    The pricing team serves as a critical strategic partner to senior leadership, delivering the cross-functional insights and market analysis needed to inform C-suite decision-making. By equipping executives with a holistic view of the competitive landscape, pricing gaps, and emerging trends, the team empowers leadership to align pricing strategies with broader business objectives.

    This partnership enables senior leaders to guide day-to-day pricing operations with confidence—ensuring tactical execution aligns with corporate goals, monitoring strategy effectiveness, and maintaining competitive agility. Through ongoing market intelligence and scenario modeling, the pricing function helps leadership proactively position the brand, capitalize on untapped opportunities, and future-proof revenue streams.

    Different Audiences, Different Needs

    As mentioned, there is a place for both standard price reporting and competitive intelligence. They have different roles to play, and different teams find them valuable. Since standard reporting mainly focuses on day-to-day shifts and being able to react to real-time changes, operational teams find it most useful.

    On the other hand, competitive intelligence is a tool that leadership can use to shape overarching pricing strategies. The insights from competitive intelligence drive operational activities over months and quarters, whereas standard reporting drives actions daily.

    To succeed in pricing, you need to rely on a combination of tactical standard reporting and competitive intelligence for long-term planning. With both, you can successfully navigate the ever-fluctuating retail market.

    Price Reporting for Operational Teams

    Your operational team is responsible for making pricing adjustments that directly impact sales volume. Automated data aggregation and AI-powered analytics can make this process faster and more accurate by eliminating the need for manual intervention.

    Instead of spending hours identifying changes, standard reporting tools surface the most critical areas that need attention and recommend adjustments. This helps operational teams react fast to shifting market conditions.

    Key functions of standard price reporting include:

    • Daily/weekly pricing decisions: Frequent price adjustments based on market trends will help your company remain competitive across entire product categories. With automated, real-time dashboards, your pricing team can monitor broad category-level pricing shifts and make necessary adjustments accordingly.
    • Individual SKU management: Not all pricing changes happen at the category level. Standard reporting also allows teams to view price and promotion changes on individual SKUs down to the zip code. It’s important to have targeted, granular insights when a change occurs even on a single SKU, especially because these individual changes are easy to miss. Advanced product matching algorithms can tie together exact products across retailers to monitor items conjointly. By incorporating similar product matching technologies beyond standard reporting, your teams can monitor individual price changes on comparable products.
    • Immediate action items: The best standard reporting tools alert pricing teams when there has been a change in competitor pricing and give them recommendations for what to change. If a competitor launches a flash sale or an aggressive discount program, your team should know as fast as possible which product to adjust. Without this functionality, teams can miss important changes or experience a delay in action that results in lost sales or customer perception.

    Competitive Intelligence for Leadership

    For Senior Retail Executives, Category Directors, and Pricing Strategy Leaders, pricing cannot only be about reacting to individual competitor price changes. Instead, you must proactively think about your market positioning and brand perception. Doing this without a complete competitive intelligence strategy can feel like throwing darts while blindfolded. Sometimes, you’ll hit the target, but mostly, you’ll miss or only come close. Competitive intelligence tools can help you hit that target every time. They leverage big data, artificial intelligence (AI), and predictive modeling to help you derive holistic insights to understand your current positioning relative to the current and future pricing landscape.

    Core strategic functions of competitive intelligence include:

    • Strategic planning: Competitive intelligence tools can help you forecast competitor behavior, economic shifts, and category-specific patterns you’d otherwise overlook (ex, price drops before new releases, subscription or bundling trends, or seasonable price cycles). Instead of reacting to a change, your team can already have made changes or at least know what playbook to implement.
    • Market positioning: Geographic pricing intelligence built into competitive intelligence tools can help you understand variations across locations and optimize multiple channels simultaneously. This can be the foundation of regional pricing strategies that factor in local economies and consumer perception.
    • Long-term decision-making: You can use competitive intelligence technology to align your pricing strategy with upcoming seasonal trends isolated using historical data, predicted economic shifts, and changes in customer purchasing behavior. This aggregate view of the pricing landscape will help you step out of the weeds and make better company decisions.

    From Data to Strategy – Transforming Basic Price Data

    Shifting your focus from isolated, reactive data to broader market trends is the key to going from basic price reporting to real competitive intelligence. Never forget the importance of real-time data, but know it’s your responsibility as a leader to bring a broader viewpoint to operations.

    Transforming from basic price data to competitive intelligence involves:

    1. Harnessing the data
      • Pattern recognition: Your solution should help you identify repeat pricing behaviors and competitor strategies
    2. Figuring out what to do with the data
      • Strategic implications: It should help you understand how your pricing changes will affect customer perception of your brand
    3. Doing something with the insights from your data
      • Action planning: The solution should help you create proactive strategies that position you as a market leader, leaving your competition to try to keep up with you instead of vice versa

    Leveraging Technology for Competitive Intelligence

    Technology is at the heart of leveling up your standard price reporting game. If you want industry-leading competitive intelligence, you can leverage DataWeave’s comprehensive pricing intelligence solution with built-in competitive intelligence capabilities and features for your operational teams.

    You can also uncover gaps and stay competitive in the dynamic world of eCommerce. It provides brands with the competitive intelligence they need to promptly adapt to market demand and competitors’ pricing. Stay ahead of market shifts by configuring your own alerts for price fluctuations on important SKUs, categories, or brands, all time-stamped and down to the zip.

    And since our platform relies on human-backed AI technology, you can have complete confidence in your data’s accuracy at any scale. If you want to bring a new strategic mindset to your pricing team, consider adding competitive intelligence to your tech stack. If you want to learn more, connect with our team at DataWeave today.

  • Preparing for Tariff Impact: A Retailer’s Guide to Price Intelligence

    Preparing for Tariff Impact: A Retailer’s Guide to Price Intelligence

    The power to impose tariffs on foreign countries is one of the most impactful measures a government has at their disposal. The government can use this power for various reasons: to punish rivals, equalize trade, give domestic products a comparative advantage, or collect more funds for the federal government.

    Whatever the reason, tariffs have real-world impacts on brands and retailers selling in a global economy. They effectively make products more expensive for some and comparatively cheaper for others. Since tariffs can be added or removed at the drop of a hat, retail executives, category managers, and pricing teams trying to keep up have their work cut out for them.

    You’ve come to the right place if you’re wondering how to prepare for and respond to potential tariffs. The answer lies in technology that will make you flexible when you need to react to policy changes. Establishing workflows and processes embedded with pricing intelligence can help you stay competitive even when global politics intercepts your business.

    Understanding Tariff Impact

    Before diving into tariffs’ implications on pricing strategies, we need to understand how tariffs work and the current economic environment. Tariffs are a government’s tax on products a foreign country sells to domestic buyers. You might remember President Trump’s expanded tariff policy in September 2018. It placed a 10% tax on $200 billion worth of Chinese imports for three months before raising to a rate of 25% in January 2019. At that time, an American buyer would pay the original price of the goods plus the tax to the American government. Many additional tariffs and counter-tariffs by other countries were enacted during Trump’s first term in office, including the European Union, Canada, Mexico, Brazil, and Argentina, resulting in a trade war.

    Announcements of when, where, and on what new tariffs will be imposed are unpredictable. The only predictable thing is that this type of market volatility is here to stay. Pricing teams should adjust their mindsets to assume that volatility may always be on the horizon. This is because tariffs have many cost implications. Besides the flat rate imposed by the government on a certain product, tariffs have historically raised the price of all goods.

    In economic terms, tariffs create a multiplier effect. Consider a tariff placed on gasoline imported from Canada. This measure may encourage American drilling but will have immediate ripple effects throughout the economy. Everything that relies on ground transportation will increase in price, at least in the short term.

    This means that a fashion brand that sources and manufactures its entire line domestically will incur more costs since transportation will be more expensive. If fashion companies act like most companies, they will pass that added tax burden on to the consumer through higher prices. The company will make this decision based on how sensitive its consumers are to price increases, i.e., the elasticity of demand. These interwoven relationships extend across industries and products, affecting most retailers somehow.

    Of course, category exposure varies by industry and sector. Tariffs are known to impact specific industries more than others. For example, steel, electronics, and agriculture products are at risk of price fluctuations based on their reliance on imported components. These have high category exposure. Some industries reliant on domestic production with stable input costs are less prone to category exposure. These include domestic power grids, natural gas, real estate, and handmade goods. No matter which industry you’re in, however, expect some spill over.

    Preparation Strategies

    Strategies to battle disruption in retail

    Forward-thinking leaders can help position their teams for success in the face of pricing volatility brought on by tariffs. The key is to enable teams to sense disruptions quickly and provide a way to take corrective action that doesn’t diminish sales. Here are three strategies you can implement ahead of time that will help keep you competitive during tariff disruption.

    Cost Monitoring

    Start by getting a firm handle on internal and external costs. Understand and analyze fluctuations in the cost of raw materials, production, and supply chain for your business to operate. Make sure that your products are priced with pre-defined logic so changes in price on one SKU don’t create confusion with another. For example, faux leather costs rise while genuine leather stays the same. In that case, a leather version of a product should be raised to reflect the price increase in the pleather variation, not to devalue the perception of luxury.

    Next, you will want to understand historical pricing trends as well as pricing indexes across your categories. These insights can help your teams anticipate cost fluctuations before they even arise and mitigate the risk that economic shifts create, even unexpected tariffs.

    Competition Tracking

    Tracking your competition is likely already a strategy you have in mind. But how well are your teams executing this important task? If they’re trying to watch for market shifts and adjust pricing in real time without the help of technology, things are likely slipping through the cracks.

    Competitive intelligence solutions help retailers discover all competitive SKUs across the e-commerce market, monitor for real-time pricing shifts, and take action to mitigate risk. You need an “always-on” competitive pricing strategy now so that the second a tariff is announced, you can see how it’s affecting your market. This way, you can maintain price competitiveness and avoid margin erosion when competitors’ pricing changes in response to a tariff or other market shift.

    Consumer Impact Assessment

    The multiplier effect is felt throughout the supply chain when tariffs are implemented. The effect can affect consumers in a number of ways and cause them to become spending averse in certain areas. Often, during times of economic hardship, grocery items remain relatively inelastic. This is because consumers continue to purchase essentials regardless of price changes. Conversely, the price of eating out or home delivery becomes more elastic since consumers cut back on dining expenses when costs rise across their shopping basket.

    You need to establish clear visibility into the results of your pricing changes. The goal should be to monitor progress and measure the ROI on specific and broad pricing changes across your assortment. Conducting market share impact analysis will also help you determine if you are losing out on potential customers or whether a decline in sales is being felt across your competition. Impact analysis tools can help your company check actual deployed price changes in real time.

    Response Framework

    Tariff response action plan for retailers

    Once you’ve prepared your team with strategies and technologies to set them up for success, it’s time to think about what to do once a tariff is announced or implemented. Here are three real-time decision-making strategies you should consider before your feet are to the fire. Having these in your back pocket will help you avoid financial disruption.

    Price Adjustment Strategies

    Think about how you strategically adjust prices. These could include percentage increases, flat rate increases, or absorbed via other strategies like bundling. You should also determine a cost increase threshold that you’re willing to absorb before raising prices. Think about the importance of remaining price attractive to consumers and weigh the risk of increasing prices past consumers’ ability or willingness to pay.

    Promotion Planning

    Folding increased costs into value-added offerings for consumers can be a good way to retain customer sentiment and sales volume without negatively affecting profit margins. You can leverage discounts, promotions, or bundling options to sell more of an item to a customer at a lower per-unit cost.

    What you don’t want to do is panic-adjust prices in response to tariffs of competitor moves. Instead, you can use a tool competitor intelligence solutions to watch if your competition is holding prices steady or adjusting. With full information about pricing at your disposal, you can make better decisions on your promotional strategy and not undercut yourself or lose customer loyalty.

    Alternative Sourcing

    Let’s face it: putting all your eggs in one basket is bad for business. Instead of relying solely on a single supplier for production, you should have a diverse set of suppliers ready and able to shift production when tariffs are announced. If a tariff impacts Chinese exports, having a backup supplier in Vietnam can prevent added costs entirely. You can also consider strategies like bulk pricing, set pricing, or shifting entirely to domestic suppliers.

    Forward Buying

    Proactively stockpile inventory by purchasing large quantities of at-risk products before tariffs take effect. This strategy locks in lower costs and ensures supply continuity during disruptions. However, balance this with careful demand forecasting to avoid overstocking, which ties up cash flow and incurs storage costs. Use historical sales data and tariff implementation timelines to optimize order volumes—this is especially effective for products with stable demand or long shelf lives.

    Market Intelligence Requirements

    Preparing your pricing teams and giving them a framework upon which to act when tariffs are announced doesn’t have to be complicated. You can get access to the right data on costs, competitors, and consumer behavior with DataWeave’s pricing intelligence capability.

    We provide retailers with insights on pricing trends, category exposure, and competitor adjustments. Our AI-powered competitor intelligence solutions allow you to get timely alerts whenever a significant change happens. This can include changes to competitor pricing and category-level shifts that you’d otherwise react to when it’s too late.

    These automated insights can also help you track historical pricing trends, elasticity, and margin impact to construct a clear response framework in an emergency. Additionally, our analytics capabilities can help you identify patterns to power pre-emptive pricing and promotional strategies.

    Getting the right pricing intelligence strategy in place now can prevent disaster later. Think through your preparedness strategy and how you want your teams to respond in the event of a new tariff, and consider how much easier reacting accurately would be with all the data needed at your fingertips. Reach out to us to know more.

  • Beyond MAP Pricing: Strategic Approaches for Brands and Retailers

    Beyond MAP Pricing: Strategic Approaches for Brands and Retailers

    Many retailers view minimum advertised pricing (MAP) policies as a necessary evil since they present several challenges for competitive positioning. In an idealistic free market, there wouldn’t be a need for MAP policies, and healthy competition would do the work of setting the final advertised price.

    However, MAP policies aren’t beneficial only for brands; they also greatly benefit retailers. This article will examine why MAP pricing can be a strategic advantage for both brands and retailers. We’ll also look at ways brand managers and retail pricing teams can navigate MAP requirements to maintain profitability and safeguard customer trust.

    Understanding MAP Fundamentals

    Minimum Advertised Price (MAP) is a policy set by brands that requires their sales channels to price the brand’s products at a minimum dollar value. Retailers are free to price the items higher, but the advertised price is never to exceed the minimum threshold.

    This agreement is established at the outset of a relationship or new product launch and can change at the brand’s discretion. Consumers typically see only the minimum advertised price when they search for a product across competing retailers. This means retailers need to find other ways to differentiate themselves beyond offering the lowest price.

    But a retailer can still effectively price the product at a lower cost to win sales away from the competition. This comes in the form of discounts applied at checkout, bundled deals, or other promotions that affect the final cart but not the advertised price. Only the advertised price must remain within MAP guidelines. This gives retailers a way to set themselves apart from the competition while still protecting the brand.

    A minimum advertised price has three central values: one for the brand, one for the retailer, and one for both.

    1. Brand or manufacturer: A MAP policy protects the brand’s value and prevents price erosion. If a retailer consistently undercuts a product’s price to make it more competitive, customers may begin to perceive the brand as lower in value over time. It can cause the brand to appear less premium than if prices hold steady. If a customer pays full price one day and then sees the same item advertised at a lower base price the next, it can weaken brand loyalty and cause dissatisfaction.
    2. Retailer: Minimum advertised pricing policies prevent retailers from engaging in a pricing war with one another, driving the price of an item down and hurting margins. This race to the bottom is bad for business. Apart from reducing profits, it discourages sellers from investing in marketing and other activities that drive sales. It also means that smaller retailers can compete with larger retailers, effectively leveling the playing field across the market.
    3. All parties: The issue of counterfeit and unauthorized sellers on the grey market plagues retailers and brands. One of the most straightforward ways to identify these sellers that undercut prices and damage brand perception is to track who is pricing products outside of agreements. Unauthorized or counterfeit sellers can be identified by establishing a MAP policy and monitoring who sells at the wrong price. Then, official legal action can be taken to prevent those merchants from selling the product.

    Brand Perspective

    Developing a clear and precise MAP policy is an important option for brands looking to stay competitive. Make sure you outline the minimum advertised price for each product for each sales channel and do so by geography. Write clear instructions on how discounts, promotions, and sales can be applied to the advertised price to avoid misunderstandings later. Ensure you work with your legal team to fill in any gaps before presenting them to retailers.

    If you find sellers acting outside the MAP policy, you must act swiftly to enforce your MAP policy. Cease and desist orders are the most common enforcement strategy a brand can use on unauthorized sellers and counterfeiters. But there are legal considerations for authorized sellers, too. You may need to fine the retailer for damages, restrict inventory replenishment until prices have been adjusted, remove seller authorization by terminating the relationship entirely, or escalate to your legal team.

    Open communication between the brand and retailer is in everyone’s best interest to ensure minimum pricing is being used. Have explanatory documents available for your retailers’ non-legal teams to reference while they set prices. These can take the form of checklists, video explainers, or even well-informed brand representatives working closely with retail pricing teams. It’s likely that some MAP violations will occur from time to time. The importance your retail partners place on fixing those errors will help you determine how much goodwill you will give them in the future.

    Brands can consider rewarding retailers that consistently adhere to minimum advertised price policies. Rewards often take the form of more lenient promotion policies, especially during major holidays like Christmas, Prime Day, or Black Friday. However, it’s never advisable to relax the actual MAP policy to allow one retailer to advertise a lower price year-round.

    Retailer Strategies

    A retailer can take several approaches to complying with a brand’s MAP policy while still maximizing sales. First, you need a dedicated compliance process spearheaded by compliance specialists or, better yet, enabled by technology. Embedding a process that checks for MAP violations into daily or weekly operations will prevent problems before brands become aware.

    Automated price tracking tools can help discover discrepancies so that you don’t accidentally violate a MAP agreement. Make sure MAP training extends beyond your pricing team and includes marketing. Anyone who participates in promotions or events should be made aware of the agreements made with specific brands. Determine if there are alternative promotion methods available to attract customers. You could offer free shipping on certain items, bundle giveaways, or apply cart-wide discounts at checkout.

    Monitoring your competition in real time will also help you stay ahead. If you discover a competitor undercutting your prices, bring this to the attention of your brand representative. This can build loyalty with the brand and help prevent lost sales due to market share loss.

    Digital Implementation for MAP Compliance

    Pricing teams at brands and retailers manually attempting to manage MAP pricing will lag behind the competition without help. They must discover, monitor, and enforce MAP compliance simply and effectively.

    Over the past several years, there has been a seemingly exponential proliferation of online sellers, complicating the industry and making it nearly impossible to find and discover all instances of every product you sell. It’s further complicated by marketplaces like Amazon, Walmart, and eBay, which are full of individual unauthorized sellers and resellers.

    Implementing a digital tool is the first step to effectively discovering and monitoring MAP compliance, even across these marketplaces. This tool should monitor all competition for you and discover imbalances in pricing parity.

    DataWeave’s MAP Violations Merchant Analytics solution has AI-backed software that scours the web for your products. It uses identifiers like UPCs and product titles and compares imagery to find where the product is sold. Our AI-powered image recognition capabilities are especially helpful in identifying inauthentic listings that may be counterfeit products or unauthorized sellers. It also has built-in geographic and channel-specific MAP monitoring capabilities to help with localized enforcement.

    The tool can aggregate all this data and present dashboard views of your own and competitors’ pricing that are easy to digest and act on. After all, retailers need to monitor their own MAP compliance as well as the competition’s. Brands can also track competitor sellers’ networks to explore potential new retail partnerships and grow their network reach.

    The MAP Violations Merchant Analytics solution has automated violation alerts and advanced reporting built into it. This means you can get real-time alerts instead of pouring through dashboards searching for exceptions each week. For deeper insights, the dashboards provide time-stamped proof of which sellers are undercutting MAP minimums, so you have all the information you need to make a case against them. Discovering repeat offenders is easy with historical trends dashboards that show which sellers have a history of violations.

    With all this information on who is violating what—and when—enforcement becomes much more manageable. Send cease and desist orders to unauthorized sellers and start having conversations with authorized sellers acting outside of your agreement. Acting quickly will help prevent hits to your brand’s reputation, price erosion, and lost sales.

    DataWeave’s MAP solution gives you the competitive edge to effectively discover MAP violations, monitor market activity, and act quickly when an issue is discovered.

    Make MAP Compliance a Strategic Advantage

    Basic MAP compliance and enforcement isn’t simply about setting pricing policies anymore. These policies are foundational to brand strategies, maintaining good relationships with retailers, and establishing long-term profitability for your business.

    When you let MAP violations go unchecked, it can erode your margins, damage how your customers perceive your brand, and create confusion across channels. Discovering, monitoring, and acting on MAP violations is much easier with the help of tools like DataWeave’s AI-enabled MAP Violations Merchant Analytics.

    Ready to take control of MAP pricing at your company? Request a MAP policy assessment from DataWeave today!

  • Portfolio Enhancement Through Price Relationship Management: Building Coherent Pricing Across Product Lines

    Portfolio Enhancement Through Price Relationship Management: Building Coherent Pricing Across Product Lines

    Do you remember when the movie Super Size Me came out? If you missed it, it was about the harmful effects of eating fast food too often. One aspect of the film that stands out is McDonald’s clever use of pricing to encourage consumers to buy bigger—and therefore more expensive—meals.

    Hungry patrons could upgrade their meal to a Super Size version for only a few cents more. In doing so, McDonald’s was able to capitalize on perceived value, i.e., getting more product for an apparent lower total price for the volume. It encouraged restaurant-goers to spend a little more while feeling like they got a great deal. It was a smart use of strategic pricing.

    There are hundreds of pricing relationship types like this one that pricing leaders need to be aware of and can use to their advantage when creating their team’s pricing strategy and workflows. You need to maintain profitable and logical price relationships across your entire product portfolio while keeping up with the competition. After all, the gimmick to Super Size would never have worked if the upgrade had been of less value than just buying another burger, for example.

    In this article, we’ll examine more real-world examples of pricing challenges so you can consider the best ways to manage complex price relationships. We’ll examine things like package sizes, brands, and product lines and how they’re intertwined in systematic price relationship management. Read on to learn how to prevent margin erosion, improve customer perception of your brand, and keep your pricing consistent and competitive.

    The Price Relationship Challenge

    Pricing is one of the most challenging aspects of managing a retail brand. This is especially true if you are dealing with a large assortment of products, including private label items, the same products of differing sizes, and hundreds, or even thousands, of competing products to link. Inconsistencies in your price relationship management can confuse customers, erode trust, and harm your bottom line.

    Let’s take a look at a few common pitfalls in portfolio pricing that you might run into in real life to better understand the impact on customer perception, trust, and sales.

    Pricing Relationship Challenges Retailers Need to Account For

    Private Label vs. Premium Product Pricing

    Let’s consider a nuanced scenario where price relationships between a retailer’s private label and premium branded products create an unexpected customer perception. Imagine you’re in a supermarket, comparing prices on peanut butter. You’ve always opted for the store’s private-label brand, “Best Choice,” because it’s typically the more affordable option. Here’s what you find:

    • Best Choice (Private Label) 16 oz – $3.50
    • Jif (National Brand) 16 oz – $3.25

    At first glance, this pricing feels off—shouldn’t the private label be the cheaper option? If a customer has been conditioned to expect savings with private-label products, seeing a national brand undercut that price could make them pause.
    This kind of pricing misalignment can erode trust in private-label value and even push customers toward the national brand. When price relationships don’t follow consumer expectations, they create friction in the shopping experience and may lead to lost sales for the retailer’s own brand.

    Value Size Relationships

    A strong value-size relationship ensures that customers receive logical pricing as they move between different sizes of the same product. When this relationship is misaligned, customers may feel confused or misled, which can lead to lost sales and eroded trust.

    Let’s look at a real-world example using a well-known branded product—salad dressing. Imagine you’re shopping for Hidden Valley Ranch (HVR) dressing and see the following pricing on the shelf:

    • HVR 16 oz – $3.99
    • HVR 24 oz – $6.49
    • HVR 36 oz – $8.99

    At first glance, you might assume that buying a larger size offers better value. However, a quick calculation shows that the price per ounce actually increases with size:

    • 16 oz = $0.25 per ounce
    • 24 oz = $0.27 per ounce
    • 36 oz = $0.25 per ounce

    Customers expecting a discount for buying in bulk may feel misled or frustrated when they realize the mid-size option (24 oz) is actually the most expensive per ounce. This mispricing could drive shoppers to purchase the smallest size instead of the intended larger, more profitable unit—or worse, lead them to a competitor with clearer pricing structures.

    Retailers must maintain logical price progression by ensuring that price per unit decreases as the product size increases. This not only improves customer trust but also encourages higher-volume purchases, driving profitability while maintaining a fair value perception.

    Price Link Relationships

    A well-structured price link relationship ensures customers can easily compare similar offerings of the same product and size. When the pricing across different versions or variations of the same item isn’t clear or consistent, it can confuse customers and damage trust, ultimately leading to missed sales and a negative brand perception.

    Let’s break this down with an example of a popular product—coffee. Imagine you’re shopping for a bag of Starbucks coffee and you see the following pricing on the shelf:

    • Starbucks Classic Coffee, 12 oz – $7.99
    • Starbucks Coffee, Mocha, 12 oz – $9.99
    • Starbucks Ground Coffee, Pumpkin Spice, 12 oz – $12.99

    At first glance, the product is the same size (12 oz) across all options, but the prices vary significantly. One might assume that the price difference is due to differences in quality or features, but what if there’s no clear indication of why the different flavors are priced higher than the standard?

    After investigating, you may realize that the only differences are related to different variants—like “Mocha” or “Pumpkin Spice” rather than any significant changes in the product’s core attributes. When customers realize they’re paying a premium for just different flavors, without any tangible difference in product quality, it can lead to feelings of confusion and frustration.

    Retailers must ensure that price links between similar offerings are justifiable by clearly communicating what differentiates each product. This avoids the perception that customers are being charged extra for little added value, building trust and encouraging repeat purchases. By maintaining transparent price link relationships, businesses can foster customer loyalty, increase sales, and drive better overall satisfaction.

    What is the Foundational Process to Tackle the Price Relationship Challenge?

    Now that we’ve reviewed several challenges brands face when pricing their products, what can be done about them?

    If you’re a pricing leader, you must create a robust pricing strategy that considers customer expectations, competitive data, sizing, and the overall value progressions of your product assortment. These are the three foundational steps to solve your price relationship challenges.

    1. First, you need to group products together accurately.
    2. Second, you need to establish price management rules around the group of related items.
    3. Third, you should set in place a process to review your assortment each week to see if anything is out of tolerance.

    This process is difficult, if not impossible, to manage manually. To effectively set up and execute these steps, you’ll need the help of an advanced pricing intelligence system.

    Implementation Strategy

    Want to know how to roll out a price relationship management strategy? Follow this implementation strategy for a practical way to get started.

    1. Set up price relationship rules: Determine which of your products go together, such as same products with different sizes or color options. Assign different product assortment groups and determine tolerances for scaling prices based on volume or unit counts.
    2. Monitoring and maintenance: Establish rules to alert the appropriate party when something is out of tolerance or a price change has been discovered with a competitive product.
    3. Exception management: Only spend time actioning the exceptions instead of pouring through clean data each week, looking for discrepancies. This will save your team time and help address the most significant opportunities first.
    4. Change management considerations: Think about the current processes you have in place. How will this affect the individuals on your team who have managed pricing operations? Establish a methodology for rolling this new strategy and technology out over select product assortments or brands one at a time to build trust with internal players.

    DataWeave offers features specifically built to help pricing teams manage pricing strategies. These applications can help you optimize profit margins and improve your overall market positioning for long-term success. A concerted effort to create brand hierarchies within your own product assortment from the get-go, followed by routine monitoring and real-time updates, can make all the difference in your pricing efforts.

    Within DataWeave, you can create price links between your products (value sizing) and those of the competition. These will alert you to exceptions when discrepancies are discovered outside your established tolerance levels. If a linked set of your products in different sizes shows inconsistent pricing based on scaled volumes, your team can quickly know how to make changes. If a competitor’s price drops significantly, you can react to that change before you lose sales.

    DataWeave even offers AI-driven similar product matching capabilities, which can help you manage pricing for private label products by finding and analyzing similar products across the market.

    If you want to learn more about price relationship management, connect with our team at DataWeave today.

  • Maximizing Competitive Match Rates: The Foundation of Effective Price Intelligence

    Maximizing Competitive Match Rates: The Foundation of Effective Price Intelligence

    Merchants make countless pricing decisions every day. Whether you’re a brand selling online, a traditional brick-and-mortar retailer, or another seller attempting to navigate the vast world of commerce, figuring out the most effective price intelligence strategy is essential. Having your plan in place will help you price your products in the sweet spot that enhances your price image and maximizes profits.

    For the best chance of success, your overall pricing strategy must include competitive intelligence.

    Many retailers focus their efforts on just collecting the data. But that’s only a portion of the puzzle. The real value lies in match accuracy and knowing exactly which competitor products to compare against. In this article, we will dive deeper into cutting-edge approaches that combine the traditional matching techniques you already leverage with AI to improve your match rates dramatically.

    If you’re a pricing director, category manager, commercial leader, or anyone else who deals with pricing intelligence, this article will help you understand why competitive match rates matter and how you can improve yours.

    Change your mindset from tactical to strategic and see the benefits in your bottom line.

    The Match Rate Challenge

    To the layman, tracking and comparing prices against the competition seems easy. Just match up two products and see which ones are the same! In reality, it’s much more challenging. There are thousands of products to discover, analyze, compare, and derive subjective comparisons from. Not only that, product catalogs across the market are constantly evolving and growing, so keeping up becomes a race of attrition with your competitors.

    Let’s put it into focus. Imagine you’re trying to price a 12-pack of Coca-Cola. This is a well-known product that, hypothetically, should be easy to identify across the web. However, every retailer uses their own description in their listing. Some examples include:

    How product names differ on websites - Amazon Example
    Why matching products is a challenge - Naming conventions on Target
    Match Rate Challenge - how product names differ on retailers - Wamlart
    • Retailer A lists it as “Coca-Cola 12 Fl. Oz 12 Pack”
    • Retailer B shows “Coca Cola Classic Soda Pop Fridge Pack, 12 Fl. Oz Cans, 12-Pack”
    • Retailer C has “Coca-Cola Soda – 12pk/12 fl oz Cans”

    While a human can easily deduce that these are the same product, the automated system you probably have in place right now is most likely struggling. It cannot tell the difference between the retailers’ unique naming conventions, including brand name, description, bundle, unit count, special characters, or sizing.

    This has real-world business impacts if your tools cannot accurately compare the price of a Coca-Cola 12-pack across the market.

    Why Match Rates Matter

    If your competitive match rates are poor, you aren’t seeing the whole picture and are either overcharging, undercharging, or reacting to market shifts too slowly.

    Overcharging can result in lost sales, while undercharging may result in out-of-stock due to spikes in demand you haven’t accounted for. Both are recipes to lose out on potential revenue, disappoint customers, and drive business to your competitors.

    What you need is a sophisticated matching capability that can handle the tracking of millions of competitive prices each week. It needs to be able to compare using hundreds of possible permutations, something that is impossible for pricing teams to do manually, especially at scale. With technology to make this connection, you aren’t missing out on essential competitive intelligence.

    The Business Impact

    Besides the bottom-line savings, accurately matching competitor products for pricing intelligence has other business impacts that can help your business. Adding technology to your workflow to improve match rates can help identify blind spots, improve decision quality, and improve operational efficiency.

    • Pricing Blind Spots
      • Missing competitor prices on key products
      • Inability to detect competitive threats
      • Delayed response to market changes
    • Decision Quality
      • Incomplete competitive coverage leads to suboptimal pricing
      • Risk of pricing decisions based on wrong product comparisons
    • Operational Efficiency
      • Manual verification costs
      • Time spent reconciling mismatched products
      • Resources needed to maintain price position

    Current Industry Challenges

    As mentioned, the #1 reason businesses like yours probably aren’t already finding the most accurate matches is that not all sites carry comparable product codes. If every listing had a consistent product code, it would be very easy to match that code to your code base. In fact, most retailers currently only achieve 60-70% match rates using their traditional methods.

    Different product naming conventions, constantly changing product catalogs, and regional product variations contribute to the industry challenges, not to mention the difficulty of finding brand equivalencies and private label comparisons across the competition. So, if you’re struggling, just know everyone else is as well. However, there is a significant opportunity to get ahead of your competition if you can improve your match rates with technology.

    The Matching Hierarchy

    • Direct Code Matching: There are a number of ways to start finding matches across the market. The base tier of the hierarchy of most accurate approaches is Direct Code matching. Most likely, your team already has a process in place that can compare UPC to UPC, for example. When no standard codes are listed, your team is left with a blind spot. This poses limitations in modern retail but is an essential first step to identifying the “low-hanging fruit” to start getting matches.
    • Non-Code-Based Matching: The next level of the hierarchy is implementing non-code-based matching strategies. This is when there are no UPCs, DPCIs, ASINs, or other known codes that make it easy to do one-to-one comparisons. These tools can analyze complex metrics like direct size comparisons, unique product descriptions, and features to find more accurate matches. They can look deep into the listing to extract data points beyond a code, even going as far as analyzing images and video content to help find matches. Advanced technologies for competitive matching can help pricing teams by adding different comparison metrics to their arsenal beyond code-based. 
    • Private Label Conversions: Up until this level of the hierarchy, comparisons relied on direct comparisons. Finding identical codes and features and naming similarities is excellent for figuring out one-to-one comparisons, but when there is no similar product to compare with for pricing intelligence, things get more complicated. This is the third tier of the matching hierarchy. It’s the ability to find similar product matches for ‘like’ products. This can be used for private label conversions and to create meaningful comparisons without direct matches.
    • Similar Size Mappings: This final rung on the matching hierarchy adds another layer of advanced calculations to the comparison capability. Often, retailers and merchants list a product with different sizing values. One may choose to bundle products, break apart packs to sell as single items or offer a special-sized product manufactured just for them. 
    Similar Size Mappings - product matching hierarchy - Walmart
    Similar Size Mappings - product matching hierarchy - Costco

    While at the end of the day, the actual product is the same, when there are unusual size permutations, it can be hard to identify the similarities. Technology can help with value size relationships, package variation handling, size equalization, and unit normalization.

    The AI Advantage

    AI is the natural solution for efficiently executing competitive product matching at scale. DataWeave offers solutions for pricing teams to help them reach over 95% product match accuracy. The tools leverage the most modern Natural Language Processing models for ingesting and analyzing product descriptions. Image recognition capabilities apply methods such as object detection, background removal, and image quality enhancement to focus on an individual product’s key features to improve match accuracy.

    Deep learning models have been trained on years of data to perform pattern recognition in product attributes and to learn from historical matches. All of these capabilities, and others, automate the attribute matching process, from code to image to feature description, to help pricing teams build the most accurate profile of products across the market for highly accurate pricing intelligence.

    Implementation Strategy

    We understand that moving away from manual product comparison methods can be challenging. Every organization is different, but some fundamental steps can be followed for success when leveling up your pricing teams’ workflow.

    1. First, conduct a baseline assessment. Figure out where you are on the Matching hierarchy. Are you still only doing direct code-based comparisons? Has your team branched out to compare other non-code-based identifiers?
    2. Next, establish clear match rate targets for yourself. If your current match rate is aligned with industry norms, strive to significantly improve it, aiming for a high alignment that supports maximizing the match rate. Break this down into achievable milestones across different stages of the implementation process.
    3. Work with your vendor on quality control processes. It may be worth running your current process in tandem to be able to calculate the improvements in real time. With a veteran technology provider like DataWeave, you can rely on the most cutting-edge technology combined with human-in-the-loop checks and balances and a team of knowledgeable support personnel. Additionally, for teams wanting direct control, DataWeave’s Approve/Disapprove Module lets your team review and validate match recommendations before they go live, maintaining full oversight of the matching process.
    4. The more data about your products it has, the better your match rates. DataWeave’s competitive intelligence tools also come with a built-in continuous improvement framework. Part of this is the human element that continually ensures high-quality matches, but another is the AI’s ‘learning’ capabilities. Every time the AI is exposed to a new scenario, it learns for the next time.
    5. The final step, ensure cross-functional alignment is achieved. Every one from the C-Suite down should be able to access the synthesized information useful for their role without complex data to sift through. Customized dashboards and reports can help with this process.

    Future-Proofing Match Rates

    The world of retail is constantly evolving. If you don’t keep up, you’re going to be left behind. There are emerging retail channels, like the TikTok shop, and new product identification methods to leverage, like image comparisons. As more products enter the market along with new retailers, figuring out how to scale needs to be taken into consideration. It’s impossible to keep up with manual processes. Instead, think about maximizing your match rates every week and not letting them degrade over time. A combination of scale, timely action, and highly accurate match rates will help you price your products the most competitively.

    Key Takeaways

    Match rates are the foundation of pricing intelligence. You can evaluate how advanced your match rate strategy is based on the matching hierarchy. If you’re still early in your journey, you’re likely still relying on code-to-code matches. However, using a mix of AI and traditional methods, you can achieve a 95% accuracy rate on product matching, leading to overall higher competitive match rates. As a result, with continuous improvement, you will stay ahead of the competition even as the goalposts change and new variables are introduced to the competitive landscape.

    Starting this process to add AI to your pricing strategy can be overwhelming. At DataWeave, we work with you to make the change easy. Talk to us today to know more.

  • From Raw Data to Retail Pricing Intelligence: Transforming Competitive Data into Strategic Assets

    From Raw Data to Retail Pricing Intelligence: Transforming Competitive Data into Strategic Assets

    Poor retail data is the bane of Chief Commercial Officers and VPs of Pricing. If you don’t have the correct inputs or enough of them in real time, you can’t make data-driven business decisions regarding pricing.

    Retail data isn’t limited to your product assortment. Price data from your competition is as important as understanding your brand hierarchies and value size progressions. However, the vast and expanding nature of e-commerce means new competitors are around every corner, creating more raw data for your teams.

    Think of competitive price data like crude oil. Crude or unrefined oil is an extremely valuable and sought-after commodity. But in its raw form, crude oil is relatively useless. Simply having it doesn’t benefit the owner. It must be transformed into refined oil before it can be used as fuel. This is the same for competitive data that hasn’t been transformed. Your competitive data needs to be refined into an accurate, consistent, and actionable form to power strategic insights.

    So, how can retailers transform vast amounts of competitive pricing data into actionable business intelligence? Read this article to find out.

    Poor Data Refinement vs. Good Refinement

    Let’s consider a new product launch as an example of poor price data refinement vs. good data refinement, which affects most sellers across industries.

    Retailer A

    Imagine you’re launching a limited-edition sneaker. Sneakerheads online have highly anticipated the launch, and you know your competitors are watching you closely as go-live looms.

    Now, imagine that your pricing data is outdated and unrefined when you go to price your new sneakers. You base your pricing assumptions on last year’s historical data and don’t have a way to account for real-time competitor movements. You price your new product the same as last year’s limited-edition sneaker.

    Your competitor, having learned from last year, anticipates your new product’s price and has a sale lined up to go live mid-launch that undercuts you. Your team discovers this a week later and reacts with a markdown on the new product, fearing demand will lessen without action.

    Customers who have already bought the much-anticipated sneakers feel like they’ve been overcharged now, and backlash on social media is swift. New buyers see the price reduction as proof that your sneakers aren’t popular, and demand decreases. This hurts your brand’s reputation, and the product launch is not deemed a success.

    Retailer B

    Imagine your company had refined competitive data to work with before launch. Your team can see trends in competitors’ promotional activity and can see that a line of sneakers at a major competitor is overdue for sale based on trends. Your team can anticipate that the competitor is planning to lower prices during your launch week in the hope of undercutting you.

    Instead of needing to react retroactively with a markdown, your team comes up with clever ways to bundle accessories with a ‘deal’ during launch week to create value beyond just the price. During launch week, your competitor’s sneakers look like the lesser option while your new sneakers look like the premium choice while still being a good value. Customer loyalty improves, and buzz on social media is positive.

    Here, we can see that refined data drives better decision-making and competitive advantage. It is the missing link in retail price intelligence and can set you ahead of the competition. However, turning raw competitive data into strategic insights is easier said than done. To achieve intelligence from truly refined competitive pricing data, pricing teams need to rely on technology.

    The Hidden Cost of Unrefined Data

    Technology is advancing rapidly, and more sellers are leveraging competitive pricing intelligence tools to make strategic pricing decisions. Retailers that continue to rely on old, manual pricing methods will soon be left behind.

    You might consider your competitive data process to be quite extensive. Perhaps you are successfully gathering vast data about your competitors. But simply having the raw data is just as ineffective as having access to crude oil and making no plan to refine it. Collection alone isn’t enough—you need to transform it into a usable state.

    Attempting to harmonize data using spreadsheets will waste time and give you only limited insights, which are often out of date by the time they’re discovered. Trying to crunch inflexible data will set your team up for failure and impact business decision quality.

    The Two Pillars of Data Refinement

    There are two foundational pillars in data refinement. Neither can truly be achieved manually, even with great effort.

    Competitive Matches

    There are always new sellers and new products being launched in the market. Competitive matching is the process of finding all these equivalent products across the web and tying them together with your products. It goes beyond matching UPCs to link identical products together. Instead, it involves matching products with similar features and characteristics, just as a shopper might decide to compare two similar products on the shelf. For instance private label brands are compared to legacy brands when consumers shop to discern value.

    A retailer using refined competitive matches can quickly and confidently adjust its prices during a promotional event, know where to increase prices in response to demand and availability and stay attractive to sensitive shoppers without undercutting margins.

    Internal Portfolio Matches

    Product matching is a combination of algorithmic and manual techniques that work to recognize and link identical products. This can even be done internally across your product portfolio. Retailers selling thousands or even hundreds of thousands of products know the challenge of consistently pricing items with varying levels of similarity or uniformity. If you must sell a 12oz bottle of shampoo for $3.00 based on its costs, then a 16oz bottle of the same product should not sell for $2.75, even if that aligns with the competition.

    Establishing a process for internal portfolio matching helps to eliminate inefficiencies caused by duplicated or misaligned product data. Instead of discovering discrepancies and having to fire-fight them one by one, an internal portfolio matching feature can help teams preempt this issue.

    Leveraging AI for Enhanced Match Rates

    As product SKUs proliferate and new sellers seem to enter the market at lightning speed, scaling is essential without hiring dozens more pricing experts. That’s where AI comes in. Not only can AI do the job of dozens of experts, but it also does it in a fraction of the time and at an improved match accuracy rate.

    DataWeave’s AI-powered pricing intelligence and price monitoring offerings help retailers uncover gaps and opportunities to stay competitive in the dynamic world of e-commerce. It can gather competitive data from across the market and accurately match competitor products with internal catalogs. It can also internally match your product portfolio, identifying product family trees and setting tolerances to avoid pricing mismatches. The AI synthesizes all this data and links products into a usable format. Teams can easily access reports and dashboards to get their questions answered without manually attempting to refine the data first.

    How AI helps convert raw data to pricing and assortment intelligence

    From Refinement to Business Value

    Refined competitive price data is your team’s foundation to execute these essential pricing functions: price management, price reporting, and competitive intelligence.

    Price Management

    Refined data is the core of accurate price management and product portfolio optimization. Imagine you’re an electronics seller offering a range of laptops and personal computing devices marketed toward college students. Without refined competitive data, you might fail to account for pricing differences based on regionality for similar products. Demand might be greater in one city than in another. By monitoring your competition, you can match your forecasted demand assumptions with competitor pricing trends to better manage your prices and even offer a greater assortment where there is more demand.

    Price Reporting

    Leadership is always looking for new and better market positioning opportunities. This often revolves around how products are priced, whether you’re making a profit, and where. To effectively communicate across departments and with leadership, pricing teams need a convenient way to report on pricing and make changes or updates as new ad hoc requests come through. Spending hours constructing a report on static data will feel like a waste when the C-Suite asks for it again next week but with current metrics. Refined, constantly updated price data nips this problem in the bud.

    Competitive Intelligence

    Unrefined data can’t be used to discover competitive intelligence accurately. You might miss a new player, fail to account for a new competitive product line, or be unable to extract insights quickly enough to be helpful. This can lead to missed opportunities and misinformed strategies. As a seller, your competitive intelligence should be able to fuel predictive scenario modeling. For example, you should be able to anticipate competitor price changes based on seasonal trends. Your outputs will be wrong without the correct inputs.

    Implementation Framework

    As a pricing leader, you can take these steps to begin evaluating your current process and improve your strategy.

    • Assess your current data quality: Determine whether your team is aggregating data across the entire competitive landscape. Ask yourself if all attributes, features, regionality, and other metrics are captured in a single usable format for your analysts to leverage.
    • Setting refinement objectives: If your competitive data isn’t refined, what are your objectives? Do you want to be able to match similar products or product families within your product portfolio?
    • Measuring success through KPIs: Establish a set of KPIs to keep you on track. Measure things like match rate accuracy, how quickly you can react to price changes, assortment overlaps, and price parity.
    • Building cross-functional alignment: Create dashboards and establish methods to build ad hoc reports for external departments. Start the conversation with data to build trust across teams and improve the business.

    What’s Next?

    The time is now to start evaluating your current data refinement process to improve your ability to capture and leverage competitive intelligence. Work with a specialized partner like DataWeave to refine your competitive pricing data using AI and dedicated human-in-the-loop support.

    Want help getting started refining your data fast? Talk to us to get a demo today!

  • How AI Can Drive Superior Data Quality and Coverage in Competitive Insights for Retailers and Brands

    How AI Can Drive Superior Data Quality and Coverage in Competitive Insights for Retailers and Brands

    Managing the endlessly growing competitive data from across your eCommerce landscape can feel like pushing a boulder uphill. The sheer volume can be overwhelming, and ensuring that data meets standards of high accuracy and quality, and the insights are actionable is a constant challenge.

    This article explores the challenges eCommerce companies face in having sustained access to high-quality competitive data and how AI-driven solutions like DataWeave empower brands and retailers with reliable, comprehensive, and timely market intelligence.

    The Data Quality Challenge for Retailers and Brands

    Brands and retailers make innumerable daily business decisions relying on accurate competitive and market data. Pricing changes, catalog expansion, development of new products, and where to go to market are just a few. However, these decisions are only as good as the insights derived from the data. If the data is made up of inaccurate or low-quality inputs, the outputs will also be low-quality.

    Managing eCommerce data at scale gets more complex every year. There are more market entrants, retailers, and copy-cats trying to sell similar or knock-off products. There are millions of SKUs from thousands of retailers in multiple markets. Not only that, the data is constantly changing. Amazon may add a new subcategory definition in an existing space, or Staples might decide to branch out into a new industry like “snack foods for the office”, an established brand might introduce new sizing options in their apparel, or shrinkflation might decrease the size of a product.

    Given this, it is imperative that conventional data collection and validation methods need to be revised. Teams that rely on spreadsheets and manual auditing processes can’t keep up with the scale and speed of change. An algorithm that once could match products easily needs to be updated when trends, categories, or terminology change.

    With SKU proliferation, visually matching product images against the competition becomes impossible. Knowing where to look for comprehensive data becomes impossible with so many new sellers in the market. Luckily, technology has advanced to a place where manual intervention isn’t the main course of action.

    Advanced AI capabilities, like DataWeave’s, tackle these challenges to help gather, categorize, and extract insights that drive impactful business decisions. It performs the millions of actions that your team can’t accomplish with greater accuracy and in near real-time.

    Improving the Accuracy of Product Matching

    Image Matching for Data Quality

    DataWeave’s product matching capabilities rely on an ensemble of text and image-based models with built-in loss functions to determine confidence levels in all insights. These loss functions measure precision and recall. They help in determining how accurate – both in terms of correctness and completeness – the results are so the system can learn and improve over time. The solution’s built-in scoring function provides a confidence metric that brands and retailers can rely on.

    The product matching engine is configurable based on the type of products that we are matching. It uses a “pipelined mode” that first focuses on recall or coverage by maximizing the search space for viable candidates, followed by mechanisms to improve the precision.

    How ‘Embeddings’ Enhance Scoring

    Embeddings are like digital fingerprints. They are dense vector representations that capture the essence of a product in a way that makes it easy to identify similar products. With embeddings, we can codify a more nuanced understanding of the varied relationships between different products. Techniques used to create good embeddings are generic and flexible and work well across product categories. This makes it easier to find similarities across products even with complex terminology, attributes, and semantics.

    These along with advanced scoring mechanisms used across DataWeave’s eCommerce offerings provide the foundation for:

    • Semantic Analysis: Embeddings identify subtle patterns and meanings in text and image data to better align with business contexts.
    • Multimodal Integration: A comprehensive representation of each SKU is created by incorporating embeddings from both text (product descriptions) and images or videos (product visuals)
    • Anomaly Detection: AI models leverage embeddings to identify outliers and inconsistencies to improve the overall score accuracy.
    DataWeave's AI Tech Stack

    Vector Databases for Enhanced Accuracy

    Vector databases play a central role in DataWeave’s AI ecosystem. These databases help with better storage, retrieval, and scoring of embeddings and serve to power real-time applications such as Verification. This process helps pinpoint the closest matches for products, attributes, or categories with the help of similarity algorithms. It can even operate when there is incomplete or noisy data. After identification, the system prioritizes data that exhibits high semantic alignment so that all recommendations are high-quality and relevant.

    Evolution of Embeddings and Scoring: A Multimodal Perspective

    Product listings undergo daily visual and text changes. DataWeave takes a multimodal approach in its AI to ensure that any content shown on a listing is accounted for, including visuals, videos, contextual signals, and text. DataWeave is continually evolving its embedding and scoring models to align with industry advancements and always works within an up-to-date context.

    DataWeave’s AI framework can:

    • Handle Diverse Data Types: The framework captures a holistic view of the digital shelf by integrating insights from multiple sources.
    • Improve Matching Precision: Sophisticated scoring methods refine the accuracy of matches so that brands and retailers can trust the competitive intelligence.
    • Scale Across Markets: Additional, expansive datasets are easy for DataWeave’s capabilities, meaning brands and retailers can scale across markets without pausing.

    Quantified Improvements: Model Accuracy and Stats

    • Since we deployed LLMs and CLIP Embeddings, Product Matching accuracy improved by > 15% from the previous baseline numbers in categories such as Home Improvement, Fashion, and CPG.
    • High precision in certain categories such as Electronics and Fashion. Upwards of 85%.
    • Close to 90% of matches are auto-processed (auto-verified or auto-rejected).
    • Attribute tagging accuracy > 75% and significant improvement for the top 5 categories.

    Business Use Case: Multimodal Matching for Price Leadership

    For example, if you’re a retailer selling consumer electronics, you probably want to maintain your price leadership across your key markets during peak times like Black Friday Cyber Monday. Doing so is a challenge, as all your competitors are changing prices several times a day to steal your sales. To get ahead of them, this retailer could use DataWeave’s multimodal embedding-based scoring framework to:

    • Detect Discrepancies: Isolate SKUs with price mismatches with your competition and take action before revenue is lost.
    • Optimize Coverage: Establish a process to capture complete data across the competition so you can avoid knowledge gaps.
    • Enable Timely Decisions: Address the ‘low-hanging fruit’ by prioritizing products that need pricing adjustments based on confidence scores on high-impact products. Leverage confidence metrics to prioritize pricing adjustments for high-impact products.

    This approach helps retailers stay competitive even as eCommerce evolves around us. By acting fast on complete and reliable data, they can earn and sustain their competitive advantage.

    DataWeave’s AI-Driven Data Quality Framework

    Let’s look at how our AI can gather the most comprehensive data and output the highest-quality insights. Our framework evaluates three critical dimensions:

    • Accuracy: “Is my data correct?” – Ensuring reliable product matches and attribute tracking
    • Coverage: “Do I have the complete picture?” – Maintaining comprehensive market visibility
    • Freshness: “Is my data recent?” – Guaranteeing timely and current market insights
    The 3 pillars to gauge data quality at DataWeave

    Scoring Data Quality

    To maintain the highest levels of data quality, we rely on a robust scoring mechanism across our solutions. Every dataset that is evaluated is done so based on several key parameters. These can include things like accuracy, consistency, timeliness, and completeness of data. Scores are dynamically updated as new data flows in so that insights can be acted upon.

    • Accuracy: Compare gathered data with multiple trusted sources to reduce discrepancies.
    • Consistency: Detect and rectify variations or contradictions across the data with regular audits.
    • Timeliness: Scoring emphasizes data recency, especially for fast-changing markets like eCommerce.
    • Completeness: Ensure all essential data points are included and gaps in coverage are highlighted by analysis.

    Apart from this, we also leverage an evolved quality check framework:

    DataWeave's Data Quality Check framework

    Statistical Process Control

    DataWeave implements a sophisticated system of statistical process control that includes:

    • Anomaly Detection: Using advanced statistical techniques to identify and flag outlier data, particularly for price and stock variations
    • Intelligent Alerting: Automated system for notifying stakeholders of significant deviations
    • Continuous Monitoring: Real-time tracking of data patterns and trends
    • Error Correction: Systematic approach to addressing and rectifying data discrepancies

    Transparent Quality Assurance

    The platform provides complete visibility into data quality through:

    • Comprehensive Data Transparency & Statistics Dashboard: Offering detailed insights into match performance and data freshness
    • Match Distribution Analysis: Tracking both exact and similar matches across retailers and locations as required
    • Product Tracking Metrics: Visibility into the number of products being monitored
    • Autonomous Audit Mechanisms: Giving customers access to cached product pages for transparent, on-demand verification

    Human-in-the-Loop Validation (Véracité)

    DataWeave’s Véracité system combines AI capabilities with human expertise to ensure unmatched accuracy:

    • Expert Validation: Product category specialists who understand industry-specific similarity criteria
    • Continuous Learning: AI models that evolve through ongoing expert feedback
    • Adaptive Matching: Recognition that similarity criteria can vary by category and change over time
    • Detailed Documentation: Comprehensive reasoning for product match decisions

    Together, these elements create a robust framework that delivers accurate, complete, and relevant product data for competitive intelligence. The system’s combination of automated monitoring, statistical validation, and human expertise ensures businesses can make decisions based on reliable, high-quality data.

    In Conclusion

    DataWeave’s AI-driven approach to data quality and coverage empowers retailers and brands to navigate the complexities of eCommerce with confidence. By leveraging advanced techniques such as multimodal embeddings, vector databases, and advanced scoring functions, businesses can ensure accurate, comprehensive, and timely competitive intelligence. These capabilities enable them to optimize pricing, improve product visibility, and stay ahead in an ever-evolving market. As AI continues to refine product matching and data validation processes, brands can rely on DataWeave’s technology to eliminate inefficiencies and drive smarter, more profitable decisions.

    The evolution of AI in competitive intelligence is not just about automation—it’s about precision, scalability, and adaptability. DataWeave’s commitment to high data quality standards, supported by statistical process controls, transparent validation mechanisms, and human-in-the-loop expertise, ensures that insights remain actionable and trustworthy. In a digital landscape where data accuracy directly impacts profitability, investing in AI-powered solutions like DataWeave’s is not just an advantage—it’s a necessity for sustained eCommerce success.

    To learn more, reach out to us today or email us at contact@dataweave.com.

  • Black Friday vs Boxing Day: Which Sale Event Offered Better Deals?

    Black Friday vs Boxing Day: Which Sale Event Offered Better Deals?

    When it comes to shopping events, Black Friday stands out as one of the most anticipated dates for scoring deals. Typically occurring the day after Thanksgiving, the weekend kicks off the holiday shopping season with a frenzy of discounts. But Boxing Day, celebrated on December 26, is also well-known for its post-Christmas clearance sales.

    This Black Friday, US eCommerce sales increased by a hefty 14.6% in 2024, according to Mastercard SpendingPulse. While Black Friday leads in overall revenue generation for retailers, Boxing Day presents unique opportunities for clearing post-holiday inventory.

    For a consumer, which sale event is likely to offer the most attractive deals?

    At DataWeave, we analyzed discounts across retailers and categories to uncover the answer.

    Our Methodology

    For this analysis, we tracked pricing data across major retailers for Black Friday and Boxing Day. To provide a comprehensive analysis of Black Friday pricing strategies, we explored a matched products dataset, comparing identical 14,000+ SKUs across retailers within key categories.

    • Categories included: Consumer Electronics, Home & Furniture, Apparel, Health & Beauty, Grocery
    • Retailers included: Amazon, Target, Walmart, Sephora, Ulta Beauty, Overstock, Home Depot, Best Buy, Saks Fifth Ave, Nordstrom, Macy’s, Bloomingdale’s, Neiman Marcus
    • Timeline: November 26 (Black Friday), December 26 (Boxing Day)

    Average Discounts: Black Friday vs Boxing Day

    Our analysis reveals that Black Friday generally offered steeper discounts across most categories, although Boxing Day wasn’t far behind. Here’s a breakdown:

    Boxing Day Vs. Black Friday - Discounts Across Categories

    While Black Friday led in most categories, Apparel saw a slight edge on Boxing Day, with discounts averaging 40.22% compared to 37.67% on Black Friday. Electronics, Beauty, and Home, however, remained more lucrative during Black Friday.

    Top 5 Products Higher Discounts on Black Friday

    Diving deeper into specific products, here are our top 5 picks offering better discounts during Black Friday.

    Top 5 Products With Higher Discounts on Black Friday
    • Appliances like an Immersion blender set offering a discount of 88.29%, significantly higher than its Boxing Day offer of 86.62%. 
    • High-end electronics like the Microsoft Surface Pro 4 also saw substantial markdowns at 84.60%. 
    • In beauty and fashion, both La Roche Posay’s retinol serum and Vera Bradley’s satchel offered discounts above 80%. 
    • Even everyday essentials like paper towels enjoyed generous discounts, with markdowns reaching 82.35% during Black Friday compared to 76.47% on Boxing Day.

    Top 5 Products With Higher Discounts on Boxing Day

    Boxing Day revealed some remarkable deals across diverse categories, with certain products offering significantly better value than their Black Friday counterparts.

    Top 5 Products With Higher Discounts on Boxing Day
    • The JBL Go 2 portable speaker emerged as the standout, with an extraordinary 82% Boxing Day discount compared to just 20% on Black Friday—a dramatic 62% difference.
    • Home furnishings showed strong Boxing Day performance, with the Costway accent armchair set reaching 80.30% off.

    In Conclusion

    Black Friday reigns supreme in driving early holiday sales, offering deeper discounts and drawing larger crowds. However, Boxing Day remains critical for retailers to offload surplus inventory and attract post-holiday shoppers.

    By combining insights from both events, retailers can refine their strategies to maximize revenue and enhance customer satisfaction. For shoppers, the decision comes down to timing—shop early for better deals or wait to capitalize on clearance markdowns. The products and categories with more attractive offers tend to vary between these two sale events. Hence, as a shopper, it’s a good idea to keep track of prices all through the holiday season to take advantage of the best deals.

    Check out our comprehensive coverage of Black Friday 2024 deals and discounts across categories.

    For a deeper dive into the world of competitive pricing intelligence and to explore how our solutions can benefit apparel retailers and brands, reach out to us today!

  • Enterprise Data Security at DataWeave: Empowering Smarter Decisions with Seamless, Secure Data Management and Integration

    Enterprise Data Security at DataWeave: Empowering Smarter Decisions with Seamless, Secure Data Management and Integration

    At DataWeave, data security isn’t just about compliance—it’s about enabling peace of mind and better decision-making for our customers. Our customers rely on us not just for competitive and market intelligence but also for the seamless integration of critical data sources into their decision-making frameworks. To achieve this, we have built a security-first infrastructure that ensures organizations can confidently leverage both external and internal data without compromising privacy or protection.

    Secure Data Integration: The Foundation of Smarter Decisions

    Effective decision-making in today’s digital commerce landscape depends on combining multiple data sources—including first-party customer data, pricing intelligence, and business rules—into a unified framework. However, without the right security measures in place, businesses often struggle to operationalize this data effectively.

    At DataWeave, we eliminate this challenge by offering:

    • Integration with Leading Data Storage Solutions: Our platform seamlessly connects with data lakes and warehouses like AWS S3 and Snowflake, ensuring that businesses can easily ingest and analyze our data in real time.
    DataWeave's Data Security Framework
    • Support for Sandboxed Environments & Data Clean Rooms: Organizations can securely merge internal and external datasets without compromising confidentiality, unlocking deeper insights for pricing and business strategies.
    • Automated Data Ingestion & Management: We simplify the process of integrating first-party data alongside competitive insights, allowing customers to focus on execution rather than infrastructure management.

    Our Purpose-Built Security Framework

    Handling millions of data points daily demands a security framework that is not only robust but also scalable and adaptable to evolving threats. DataWeave’s multi-tenant architecture ensures seamless data security without compromising operational efficiency.

    • Multi-Tenant Architecture: Our system allows multiple customers to share the same application infrastructure while maintaining complete data isolation and security.
      • Tenants share infrastructure and computing resources but remain logically isolated.
      • Application-level controls ensure privacy while maximizing cost efficiency.
      • Centralized updates, maintenance, and easy scalability for new tenants.
    • End-to-End Encryption & Access Controls: Every piece of data is encrypted both in transit and at rest. Role-based access controls (RBAC) restrict visibility to only authorized personnel, ensuring minimal risk of unauthorized data access.

    Active Monitoring & Automated Compliance Management: We leverage automated access controls that adjust permissions dynamically as organizational roles evolve, ensuring that compliance is continuously maintained.

    Certifications That Inspire Confidence

    Data security is at the core of everything we do. Our compliance with the highest industry standards ensures that businesses can trust us with their sensitive data.

    SOC 2 Type II Certification: DataWeave’s SOC 2 compliance is a testament to our commitment to stringent security protocols. This certification guarantees that we adhere to strict standards in data protection, availability, and confidentiality.

    We implement a phased approach to security improvement:

    • Prioritizing Critical Systems: To maximize impact, we prioritized systems that had the highest data security relevance and expanded the coverage thereafter. By addressing these priority areas, we were able to make meaningful security improvements early in the process.
    • Automating Monitoring and Compliance: Partnering with Sprinto streamlined the compliance journey by automating key processes. This included real-time monitoring of our cloud environments, automated generation of audit-ready evidence, and integration with critical systems like AWS, Bitbucket, and Jira. These enhancements ensured efficient management of compliance requirements while reducing the burden on our teams.
    SOC 2 Compliance at DataWeave
    • Fostering a Culture of Shared Responsibility: We conducted organization-wide training sessions to embed compliance as a shared responsibility across all teams. By educating employees on the importance of security practices and providing them with the tools to manage compliance autonomously, we established a security-first mindset throughout the company.

    This systematic method allowed us to deliver immediate improvements while aligning long-term practices with industry’s best standards.

    What This Means for Our Customers

    By combining robust security with seamless data integration, DataWeave empowers businesses to:

    • Optimize Price Management & Modelling: With secure access to real-time data, organizations can make informed pricing decisions that enhance profitability and market competitiveness.
    • Run Advanced Simulations & Testing: Reliable, secure data enables businesses to model various pricing and assortment strategies before implementation, reducing risks and maximizing returns.
    • Uncompromised Data Security: SOC 2 Type II compliance ensures stringent protocols to protect your data at every stage.
    • Simplified Vendor Processes: Verified security certifications reduce friction during due diligence and onboarding, making it easier to partner with us.
    • Aligned Standards: Our adherence to industry benchmarks reflects our commitment to meeting your expectations as a trusted technology partner.
    • Scalable Operations: Expand across regions while maintaining full confidence in data privacy and security.
    • Secure Collaboration: Share insights across teams with tools designed to protect sensitive information.

    Our customers are increasingly looking to integrate their internal datasets with the external competitive intelligence provided by DataWeave. This can be a complex and risky process without the right security measures in place. We remove these roadblocks by providing a secure, scalable infrastructure designed to help businesses unify data without security concerns.

    By ensuring seamless compatibility with key data storage platforms, such as Snowflake and AWS S3, we enable organizations to consolidate valuable first-party data with timely market insights. This integration empowers businesses to refine their pricing, assortment, and digital shelf strategies, thereby driving superior customer experiences—without the headaches of data security risks.

    Security remains a top priority in everything we do. Our SOC 2 Type II-certified framework enforces rigorous encryption, access controls, and real-time compliance monitoring. We take on the burden of data security so our customers can focus on innovation and growth.

    With DataWeave, businesses can confidently leverage secure data-driven decision-making to unlock new opportunities, optimize operations, and scale without compromise.

    To learn more, write to us at contact@dataweave.com or request a consultation here.

  • Black Friday 2024 in Canada: Insights on Consumer Electronics and Home & Furniture

    Black Friday 2024 in Canada: Insights on Consumer Electronics and Home & Furniture

    Black Friday and Cyber Monday are major retail events in Canada, with 43% and 29% of the population making purchases during these sales respectively, according to a YouGov report. Consumer electronics continue to lead the Canadian retail market during these events, with 55% of surveyed shoppers choosing to buy tech products on Black Friday. Household appliances come in second, with 25% of shoppers opting for these items, while 18% prefer to shop for furniture deals.

    These statistics highlight the importance of delivering value during the Thanksgiving sales week. Retailers must cater to shoppers’ expectations with competitive pricing, attractive deals, and a seamless shopping experience. So, what unique offerings did Canadian retailers present to shoppers this season?

    To understand the pricing and discount dynamics during BFCM 2024 in Canada, DataWeave analyzed discounts across leading consumer electronics and home & furniture retailers. Using our AI-powered pricing intelligence platform, we analyzed 37,108 SKUs across these categories for major retailers including Amazon, Walmart, Best Buy, Home Depot, and Canadian Tire from the 10th to 29th November. We focused on the top 500 products ranked for each search keyword on each retail site, using targeted terms aligned with categories like “sofa” and “wearables”.

    In the following insights, the Absolute Discount represents the reduction of the selling price compared to the Manufacturer’s Suggested Retail Price (MSRP). The Additional Discount reflects how much lower the selling price is during Black Friday compared to its price a week before the sale. This metric reveals the actual or effective value of the sale event, beyond the standard discounts typically offered.

    Also check out our detailed analysis of discounts and pricing for the consumer electronics, apparel, health & beauty, grocery, and home & furniture categories across major US retailers this Black Friday.

    Consumer Electronics

    Retailers in Focus

    Consumer electronics saw robust participation from major retailers, with Amazon, Best Buy, and Walmart leading the charge. Here’s how they stacked up in terms of discounts:

    Pricing Trends Across Leading Consumer Electronics Retailers in Canada - Black Friday Cyber Monday 2024
    • Best Buy emerged as the frontrunner in absolute discounts at 31.2%, while Amazon impressed with a notable 19.7% additional discount, indicating a strong Black Friday-specific markdown strategy.
    • Walmart offered steady competition, particularly in audio and video products, which reached an average absolute discount of 37.2%. However, it’s average additional discount was only 3.1%, indicating muted BFCM-specific price reductions in this category.

    Subcategory Insights

    Diving deeper into consumer electronics subcategories, we observed varied discounting strategies.

    Pricing Trends Across Leading Canadian Consumer Electronics Retailer Subcategories - Black Friday Cyber Monday 2024
    • Audio & Video stood out as the most discounted subcategory, with Walmart leading at 37.2%.
    • In Wearables, Walmart again took the top spot with 36.4%, while Amazon offered higher additional discounts (22.4%).
    • Discounting for computers and gaming was less aggressive, highlighting strategic pricing to maintain profitability in these high-demand segments.

    Brand Performance

    Brand-level data highlighted how key players used Black Friday to drive visibility and sales.

    Pricing Trends Across Leading Canadian Consumer Electronics Brands - Black Friday Cyber Monday 2024
    • Dell led in average absolute discounts (36.7%) followed by Samsung at 36.68%
    • Audio brand JBL offered significant absolute discounts at 35.9%.
    • Apple and Lenovo offered comparatively fewer discounts but maintained strong visibility, as seen in their increase in the Share of Search during the sale period.
    Visibility Trends Across Leading Canadian Consumer Electronics Brands - Share of Search - Black Friday Cyber Monday 2024
    • MSI (laptop brand) and Bose (audio and earphone brand) experienced significant increases in visibility, with Share of Search increases of 5% and 3.6%, respectively.
    • Notably, HP faced a decline (-3.2%) in the Share of Search, suggesting missed opportunities to align promotions with consumer interest.

    Home & Furniture

    Retailers in Focus

    The home and furniture category saw competitive discounting, with Walmart, Canadian Tire, and Home Depot vying for consumer attention.

    Black Friday - Cyber Monday Trends Across Leading Canadian Home & Furniture Retailers
    • Walmart took the lead with the highest absolute discounts at 36.8%. The retailer’s additional discounts were more conservative at 3.6%. This is similar to their discount levels in Consumer Electronics.
    • Canadian Tire offered stiff competition, providing 31.6% absolute discounts and 25% additional discounts.
    • Home Depot matched its absolute and additional discounts, maintaining consistency at 24.1%.

    Subcategory Insights

    Home and furniture subcategories revealed targeted discount strategies.

    Black Friday - Cyber Monday Trends Across Leading Home & Furniture Subcategories - Canada
    • Bedding emerged as the most discounted subcategory at Walmart (50.6%) and Canadian Tire (35.3%).
    • Kitchenware saw competitive pricing, with Walmart leading at 42.9%, followed by Canadian Tire at 33.9%.
    • Canadian Tire focused on lighting, offering the highest absolute discounts in this subcategory (38.2%)

    Brand Performance

    Brand-level analysis revealed stark contrasts in discounting approaches.

    Black Friday - Cyber Monday Trends Across Leading Home & Furniture Brands - Canada
    • Furniture brands Homcom led in absolute discounts (36.4%), while South Shore stood out with the highest additional discounts (30.2%).
    • Value-oriented brands like furnishings brand Mainstays and mattress and bedding brand Zinus offered more modest discounts, focusing on consistent affordability.
    Black Friday - Cyber Monday Trends Across Leading Canadian Home & Furniture Brands - Share of Search and Visibility
    • Zinus (mattresses and sofa brand) experienced a significant 7.9% increase in the Share of Search, driven by aggressive promotions.
    • Home furnishings brands like Costway and Safavieh faced declines, reflecting the importance of aligning promotional strategies with consumer expectations.

    Insights for Retailers and Brands

    This Black Friday, Canadian retailers effectively balanced deep discounts with category-specific strategies to maximize sales. However, the fluctuating Share of Search highlights the critical need for brands to align promotions with consumer interest.

    For brands and retailers looking to stay ahead of the competition, DataWeave’s pricing intelligence platform offers unparalleled insights to refine discounting strategies and boost visibility. Contact us to learn how we can help you stay competitive in this dynamic retail landscape.

  • A Deep Dive into Consumer Electronics Pricing During Black Friday 2024

    A Deep Dive into Consumer Electronics Pricing During Black Friday 2024

    Americans spent a whopping total of $10.8 billion online this Black Friday. As Thanksgiving Week 2024 wraps up, one thing is clear: the consumer electronics category continues to dominate seasonal shopping trends. Fueled by a blend of enticing deals and high consumer demand, the sector delivered competitive discounts across subcategories like wearables, gaming, and mobile devices.

    At DataWeave, we analyzed discounting trends in the U.S. consumer electronics market during this year’s sales events. Using our AI-powered pricing intelligence platform, we tracked pricing and promotions for 22383 SKUs across Amazon, Walmart, Target, and Best Buy from November 10 to 29. We focused on the top 500 products ranked for each search keyword on each retail site, using targeted terms aligned with categories like “gaming” and “apple.” Here’s what we uncovered.

    Also check out our insights on discounts and pricing for health & beauty, grocery, apparel, and home & furniture categories this Black Friday.

    Retailers Battle It Out with Competitive Discounts

    Discount trends reveal clear leaders in terms of markdowns:

    • Walmart offered the deepest average absolute discounts at 36.9%.
    • Amazon and Target followed closely, highlighting a diverse range of deals designed to appeal to budget-conscious shoppers
    • Best Buy, the specialist consumer electronics retailer, offers the lowest discounts this Black Friday at 26.2%.
    Pricing Trends Across Leading Consumer Electronics Retailers - Black Friday Cyber Monday 2024

    Note: The Absolute Discount represents the reduction of the selling price compared to the Manufacturer’s Suggested Retail Price (MSRP). The Additional Discount reflects how much lower the selling price is during Black Friday compared to its price a week before the sale. This metric reveals the actual or effective value of the sale event, beyond the standard discounts typically offered.

    Subcategory Spotlight: Where the Best Deals Happened

    From audio & video to wearables, each retailer carved out competitive advantages across subcategories.

    Pricing Trends Across Leading Consumer Electronics Retailer Subcategories - Black Friday Cyber Monday 2024
    • Both Amazon and Walmart offered high discounts in audio & video and wearables, but Walmart led, with discounts up to 46.3%.
    • Best Buy, meanwhile, offered high absolute discounts on Mobile Devices(34%) and Storage (31%), followed by high discounts on wearables and Audio & Video.
    • Amazon maintained a balanced approach, excelling in audio & video and mobile devices.

    Brand-Level Insights: HP and Samsung Dominate

    The biggest winners this year were brands that strategically leveraged Black Friday discounts to boost visibility and sales:

    • HP took the top spot with average discounts of 36.9%, followed by Samsung at 31.4%.
    • Despite its premium reputation, Apple offered an average discount of 29.3%, signaling a shift in strategy to attract deal hunters.
    Pricing Trends Across Leading Consumer Electronics Brands - Black Friday Cyber Monday 2024

    Share of Search: Shifting Consumer Attention

    Search trends reveal how discounts shaped brand visibility:

    • Microsoft saw the largest spike in share of search (+8.6%), thanks to aggressive pricing on gaming consoles and accessories.
    • Marshall and Amazon also saw significant gains in visibility.
    • Surprisingly, HP experienced a sharp decline (-9.8%), indicating missed opportunities despite steep discounts.
    Visibility Trends Across Leading Consumer Electronics Brands - Share of Search - Black Friday Cyber Monday 2024

    Consumer Electronics: Lowest-Priced Retailer Analysis

    In the previous analysis, we focused on the top 500 products within each subcategory for each retailer, showcasing the discount strategies for their highlighted or featured items. However, to identify which retailer offered the lowest or highest prices for the same set of products, it’s necessary to match items across retailers. For this, we analyzed a separate dataset of 340 matched products across retailers to compare their pricing during Black Friday. This approach provides a clearer picture of price leadership and competitiveness across categories.

    Here are the key takeaways from this analysis.

    Category-Level Highlights

    Retailers Offering Most Value - Lowest Priced - Consumer Electronics - Black Friday 2024
    • Amazon leads with the highest average discount (41.35%), offering the most value to consumers. It is followed by Target (39.37%) and Walmart (36.15%).
    • Best Buy, the specialist consumer electronics retailer, ranks last with an average discount of 31.53%, emphasizing a less aggressive pricing strategy compared to competitors.

    Subcategory Highlights

    Lowest Priced Retailer Across Major Subcategories- Consumer Electronics - Black Friday 2024
    • Wearables: Amazon offers the steepest discounts (55.40%), followed by Best Buy (50.60%) and Walmart (45.75%).
    • Mobile Devices: Amazon also leads (37.94%), with Walmart (29.30%) in second place and Target trailing at 19.48%.
    • Gaming: Target takes the lead (37.47%), with Amazon and Best Buy offering similar discounts around 30%.
    • Computers: Target again emerges as the leader (39.18%), narrowly surpassing Walmart (36.13%).

    Brand Highlights

    Lowest Priced Retailer Across Leading Brands- Consumer Electronics - Black Friday 2024
    • Apple: Amazon dominates with 53.06%, closely followed by Walmart (50.55%), while Target and Best Buy hover around 43%.
    • Nintendo: Target edges out Amazon (37.62% vs. 36.54%), with Best Buy (33.21%) and Walmart (25.92%) trailing.
    • Beats by Dr. Dre: Amazon leads (46.07%), with Target (37.14%) as the runner-up. Best Buy and Walmart offer comparatively modest discounts around 25%.
    • Bose: Walmart emerges as the value leader (23.90%), surpassing Target (16.09%) and Best Buy (15.29%).
    • Cricut: Amazon sets a high benchmark (54.13%), with Target far behind (36.43%) for this viral portable printer brand. Best Buy (12.32%) and Walmart (10.79%) offer significantly lower discounts.

    What This Means for Retailers and Brands

    Retailers looking to stay competitive should focus on strategic discounting and enhanced brand visibility. Brands must align with consumer expectations by:

    • Leveraging platforms like DataWeave to analyze discount trends.
    • Optimizing pricing and assortment strategies for seasonal demand.

    For more insights into consumer electronics pricing, contact DataWeave to discover how our AI-powered solutions can drive success in today’s fast-paced market. Stay tuned for more category-specific analyses in the coming weeks!

  • The Apparel Market: A Closer Look at Black Friday Discounts

    The Apparel Market: A Closer Look at Black Friday Discounts

    As the holiday shopping season kicked off, savvy shoppers embraced the spirit of the season, drawn by enticing deals. The apparel category is forecasted as the second highest earning category (Source: Statista), expected to generate revenues up to $43.9 billion, closely following consumer electronics. To understand the pricing strategies of top retailers amidst the sale season, DataWeave analyzed the pricing trends for the Apparel category this Black Friday.

    We leveraged our AI-powered data platform to analyze the discounting across key retailers. Our analysis focused on the Apparel category, examining how Amazon, Walmart, Target, Saks Fifth Avenue, Nordstrom, Bloomingdales, Neiman Marcus and Macy’s differentiated themselves through their discounts.

    Also check out our in-depth insights on discounts and pricing for health & beauty, grocery, and home & furniture categories this Black Friday.

    Our Methodology

    For this analysis, we tracked the average discounts of apparel products among leading US retailers during the Thanksgiving weekend sale, including Black Friday. Our sample was chosen to encompass the top 500 ranked products in each product subcategory across during the sale.

    • Sample size: 37,666 SKUs
    • Retailers tracked: Amazon, Walmart, Target, Nordstrom, Macy’s, Bloomingdale’s, Saks Fifth Avenue, Neiman Marcus
    • Subcategories reported on: Footwear, Kid’s Clothing, Men’s Clothing, Women’s Clothing, Activewear, Plus Size Clothing, Accessories
    • Timeline of analysis: 10 to 29 November 2024

    We focused on the top 500 products ranked for each search keyword on each retail site, using targeted terms aligned with categories like “athleisure” and “plus size clothing”. Our methodology distinguished between standard discounts and Black Friday-specific ‘additional discounts’ or price reductions during the sale compared to the week before, to reveal true consumer value.

    Key Findings

    This year’s fashion discounts were unprecedented. Let’s take a look.

    Retailer Level Insights

    Discounts Across Leading Apparel Retailers - Black Friday 2024
    • Nordstrom leads with the highest average absolute discount at 59%, followed by Saks Fifth Avenue at 35.5% and Bloomingdale’s at 41.5%. Macy’s shows the lowest average discount at 24.1%, while Amazon has an average discount of 30.4%.
    • Amazon ranks lower in both average absolute and additional discounts compared to competitors, indicating a more conservative discounting strategy.

    Subcategory Analysis

    Discounts Across Leading Apparel Retailers - Subcategories - Black Friday 2024
    • Kids’ Clothing saw the deep discounts (up to 55% at Nordstrom), reflecting growing pressure on family budgets and heightened competition to attract budget-conscious parents.
    • Plus-Size Clothing emerged as a major focus, with Nordstrom leading at 53.22% average absolute discounts, signaling that retailers are increasingly prioritizing size inclusivity and appealing to a broader consumer base.
    • Footwear experienced robust discounting, particularly at Bloomingdale’s with 37% average absolute discounts, showing a competitive approach to attract customers looking for seasonal footwear deals.
    • Activewear displayed substantial discounts, with Walmart offering up to 41% on average, aligning with the trend of consumers looking for practical and comfortable attire during the winter season.

    Brand Level Insights

    Apparel brands, meanwhile, also offer telling insights.

    Discounts Across Leading Apparel Brands - Black Friday 2024
    • Top Discounting Brands: Aqua leads with an average absolute discount of 44.58%, followed by Boss at 42.33% and Burberry at 37.84%.
    • Lowest Discounts: Athletic Works shows the lowest average absolute discount at 31.23%, with a minimal additional discount of 3.73%.
    • Competitive Advantage: Brands like Ralph Lauren and Boss show strong discounts, indicating aggressive marketing during the sale.

    Share of Search Insights

    Visibility - Share of Search Trend Across Leading Apparel Retailers - Black Friday 2024
    • Top Gainers: Adidas and Nike each saw an increase of 1.20% in their share of search during Black Friday/Cyber Monday, highlighting their strong brand presence and consumer interest.
    • Top Losers: Reebok experienced a sharp decline, losing 2.60% in its share of search, while Levi’s also dropped by 0.60%.
    • Search Trends: The data suggests a strong consumer preference for activewear brands like Nike and Adidas and a decline in interest for traditional apparel brands like Levi’s.

    Who Offered Most Value This Black Friday

    In the previous analysis, we focused on the top 500 products within each subcategory for each retailer, showcasing the discount strategies for their highlighted or featured items. However, to identify which retailer offered the lowest or highest prices for the same set of products, it’s necessary to match items across retailers. For this, we analyzed a separate dataset of 418 matched products across Apparel specific retailers to compare their pricing during Black Friday. This approach provides a clearer picture of price leadership and competitiveness across categories.

    Here are the key takeaways from this analysis.

    Category-Level Analysis

    At the overall category level, Macy’s emerged as the lowest-priced retailer, offering the highest average discount of 28.72%, followed closely by Nordstrom (26.06%). The steep decline in average discounts from Saks Fifth Avenue (14.42%) and Neiman Marcus (7.93%) highlights a clear gap in discounting strategies.

    • Macy’s and Nordstrom are aggressively competitive on pricing in the overall apparel category, likely capturing consumer attention with substantial discounts.
    • Saks Fifth Avenue and Neiman Marcus may rely more on brand perception and luxury positioning rather than heavy discounting.
    Retailers Offering Most Value - Lowest Priced - Apparel - Black Friday 2024

    Subcategory-Level Analysis

    Lowest Priced Retailer Across Major Subcategories- Apparel - Black Friday 2024
    • Neiman Marcus tops the ranking with an impressive 60.85% average discount, outperforming Macy’s (52.86%) and Nordstrom (43.04%) for Men’s Clothing. We see a similar trend with Neiman Marcus offering more value across Women’s Clothing as well, compared to other retailers.
    • The competition in footwear was intense, with Neiman Marcus narrowly securing the top spot at 31.03%, slightly ahead of Saks Fifth Avenue (30.28%) and Macy’s (30.07%).
    • Saks Fifth Avenue led by a significant margin in the Activewear category, offering 39.89% average discounts, indicating a strong push in this growing segment.
    • Macy’s followed at 32.16% in Activewear, while Neiman Marcus and Nordstrom had comparatively lower discounts of 26.40% and 19.52%, respectively.

    Brand-Level Analysis

    Lowest Priced Retailer Across Leading Brands- Apparel - Black Friday 2024
    • Kate Spade New York: Neiman Marcus leads with the highest discount of 55.23%, reflecting strong price leadership in premium fashion, closely followed by Saks Fifth Avenue at 51.66%.
    • Coach: Neiman Marcus dominates with a significant 75.85% discount, showcasing an aggressive promotional strategy for this luxury brand.
    • Spanx: While Neiman Marcus leads with 28.22%, discounts across other retailers like Saks Fifth Avenue, Macy’s, and Nordstrom are clustered within a competitive range of 17–19%.
    • Montblanc: Macy’s takes the lead with 20.32%, signaling its competitiveness even in high-end accessories, with Saks Fifth Avenue and Nordstrom closely behind.
    • Ugg: Saks Fifth Avenue leads with 31.42%, focusing on maintaining price leadership for this popular brand, while other retailers remain competitive with discounts around 25–30%.

    What’s Next

    To win over price-conscious shoppers, retailers need to stay competitive and consistently offer the lowest prices.

    For a deeper dive into the world of competitive pricing intelligence and to explore how our solutions can benefit apparel retailers and brands, reach out to us today!

    Stay tuned to our blog for more insights on different categories this Black Friday and Cyber Monday.


  • Breaking Down Grocery Discounts This Black Friday

    Breaking Down Grocery Discounts This Black Friday

    As shoppers flocked online and to stores during Black Friday and Cyber Monday, the grocery category stood out as a key battleground for retailers. With inflation affecting consumer spending, discounted groceries have become a critical driver for both shopper savings and retailer competitiveness.

    In fact, according to the NRF, one of the top shopping destinations during Thanksgiving weekend were department stores (42%), online (42%),and grocery stores and supermarkets (40%). Clearly, consumers are looking to stock up in bulk on their groceries to maximize their savings.

    To understand the pricing dynamics in the grocery category, DataWeave analyzed grocery discounts across leading grocers, uncovering significant trends that shaped consumer choices during this holiday shopping period.

    Our research encompassed retailers like Amazon, Target, and Walmart, examining their discounting strategies across subcategories, alongside trends in share of search for leading CPG companies.

    Also check out our detailed analysis of discounts and pricing for health & beauty and home & furniture this Black Friday.

    Key Grocery Market Stats for Black Friday-Cyber Monday 2024

    • Retailer Discounts: Walmart offered the highest average absolute discount at 27.6%, followed by Amazon at 20.4% and Target at 14.0%
    • Subcategory Insights: Beverages Category at Walmart saw the deepest discounts, with an average of 33.4%
    • Top Gaining Brands: Cesar experienced the largest increase in share of search during the sales period (+3.89%)

    This blog will dive deeper into grocery discount trends and brand-level strategies, offering insights for retailers looking to stay competitive in the grocery sector.

    Our Methodology

    For this analysis, we tracked the average discounts offered by major U.S. grocery retailers during the Thanksgiving weekend, including Black Friday and Cyber Monday. We focused on key subcategories within the grocery segment, capturing trends in discounting strategies.

    • Sample Size: 18,324 SKUs
    • Retailers Tracked: Amazon, Walmart, Target
    • Subcategories Reported On: Fresh Produce, Dairy & Eggs, Pantry Essentials, Snacks, Frozen Foods, Meat & Seafood, Household Essentials, Beverages, Pet Products, Baby Products
    • Timeline of Analysis: November 10 to 29, 2024

    In the following insights, the Absolute Discount represents the reduction of the selling price compared to the Manufacturer’s Suggested Retail Price (MSRP). The Additional Discount reflects how much lower the selling price is during Black Friday compared to its price a week before the sale. This metric reveals the actual or effective value of the sale event, beyond the standard discounts typically offered.

    Key Findings

    Retailer-Level Insights

    Average Discounts Across Leading Grocery Retailers - Black Friday Cyber Monday 2024
    • Walmart emerged as the leader in grocery discounting, offering the highest average absolute (27.6%) and additional (18%) discounts.
    • Amazon adopted a mid-tier discounting strategy, with average absolute discounts of 20.4%.
    • Target, while more conservative, maintained competitiveness in select subcategories like baby products.

    Subcategory Insights

    Average Discounts Across Leading Grocery Retailer Subcategories - Black Friday Cyber Monday 2024
    • Pantry Essentials saw Walmart leading with an average discount of 31.2%, appealing to budget-conscious consumers stocking up for the holidays.
    • Fresh Produce showed consistent discounting across retailers, with Amazon slightly ahead at 27%.
    • Beverages stood out for significant discounting at Walmart, with an impressive 33.4% average discount.

    Brand-Level Insights

    Average Discounts Across Leading Grocery Brands - Black Friday Cyber Monday 2024
    • Lay’s led in absolute discounts (37.52%) and additional discounts (26.23%) showcasing aggressive pricing in the snacks subcategory.
    • Good & Gather maintained its competitive edge with strong discounts, appealing to price-conscious consumers seeking value.
    • Brands like Blue Buffalo (pet food brand) offered significant absolute discounts, but with a low additional discount of just 2%, the overall impact of the sale event on effective value was limited.

    Share of Search Insights

    Gains and Losses in Share of Search Across Leading Grocery Brands - Black Friday Cyber Monday 2024
    • Cesar (dog food brand), Tide (laundry staple) and Doritos saw significant gains in share of search, reflecting successful promotional strategies.
    • Brands like Pampers (baby diapers brand), Healthy Choice, (frozen foods brand) and Pedigree (pet food brand) experienced a decline, indicating less effective engagement during the sale period.

    Who offered the lowest prices?

    In the previous analysis, we focused on the top 500 products within each subcategory for each retailer, showcasing the discount strategies for their highlighted or featured items. However, to identify which retailer offered the lowest or highest prices for the same set of products, it’s necessary to match items across retailers. For this, we analyzed a separate dataset of 1433 matched products across retailers to compare their pricing during Black Friday. This approach provides a clearer picture of price leadership and competitiveness across categories.

    Here are the key takeaways from this analysis.

    Category-Level Analysis

    Retailers Offering Most Value - Lowest Priced - Grocery - Black Friday 2024
    • Walmart is the lowest priced retailer overall for the grocery category, with an impressive average discount of 44.60%. This significant discount advantage makes Walmart a leading option for value-seeking consumers.
    • Target follows with strong discounts of 36.73%, indicating solid pricing in comparison but less aggressive than Walmart.
    • Interestingly, Amazon was the most expensive in Grocery, with an average discount of only 6.3%.

    Subcategory-Level Analysis

    Lowest Priced Retailer Across Major Subcategories- Grocery - Black Friday 2024
    • Walmart leads in various subcategories such as Pet Products (21.12%), Dairy & Eggs (13.79%), Household Essentials (13.05%), Frozen Foods (15.07%), and Meat & Seafood (17.60%), showcasing its extensive value across the board.
    • Target excels in Beverages (14.58%) and Baby Products (15.00%) with competitive discounts, standing out in these specific subcategories.
    • Kroger provides notable value in Pantry Essentials (20.04%) and Fresh Produce (15.85%), although its overall average discount is lower than Walmart’s.
    • Amazon consistently ranks lower in terms of average discounts across most subcategories, highlighting it as less competitive for consumers seeking the lowest prices.

    Brand-Level Analysis

    Lowest Priced Retailer Across Leading Brands- Grocery - Black Friday 2024
    • Walmart also holds the top position for several key brands like Cheetos (14.92%) and Dannon (8.81%), making it the best option for consumers looking for budget-friendly choices across popular brands.
    • Target takes the lead for brands like Betty Crocker (25.20%) and Chobani (11.37%), showing that it can offer value for specific products.
    • Kroger maintains strong discounts for brands such as Delmonte (9.19%), but it does not outpace Walmart in the overall grocery brand comparison.
    • Amazon generally lags behind in average discounts for most brands, with Dannon (1.12%) and Chobani (2.43%) showing significantly lower discounts.

    Walmart is the lowest priced retailer in the grocery category and provides substantial value across a wide range of subcategories and popular brands. This ties in with Walmart’s ELDP pricing strategy. The retailer leads in overall average discounts and maintains its position as the go-to for price-conscious consumers. Target offers strong value in certain subcategories and brands but falls short of Walmart’s broad value based pricing advantages.

    What’s Next

    For grocery retailers, competitive pricing and targeted promotions are critical to driving sales during key shopping events. As consumers continue to prioritize value, staying ahead in the discounting game can significantly impact market share.

    For detailed insights into grocery discounting strategies and to explore how DataWeave’s solutions can help retailers optimize their pricing, contact us today!

    Stay tuned to our blog for further analyses of other categories during Black Friday and Cyber Monday.

  • Black Friday 2024: Home & Furniture Pricing Trends Analyzed

    Black Friday 2024: Home & Furniture Pricing Trends Analyzed

    The Home & Furniture category continues to thrive, propelled by consumer interest in creating personalized and functional living spaces. In 2023, the U.S. furniture and home furnishings market was valued at approximately $641.7 billion in 2023 and is estimated to grow at a CAGR of 5.1% from 2024 to 2032. Black Friday and Cyber Monday play a crucial role in fueling this growth, offering consumers a mix of premium and affordable options across subcategories.

    To better understand market trends and discount strategies this Black Friday, at DataWeave we tracked over 18,149 SKUs across major home & furniture retailers, including Amazon, Walmart, Target, Best Buy, Home Depot, and Overstock, from November 10 to 29, 2024. Using our AI-powered pricing intelligence platform, we focused on the top 500 products in subcategories like kitchenware, furniture, decor, lighting, outdoor items, and bedding.

    In our analysis, the Absolute Discount represents the reduction of the selling price compared to the Manufacturer’s Suggested Retail Price (MSRP). The Additional Discount reflects how much lower the selling price is during Black Friday compared to its price a week before the Black Friday sale. This metric reveals the actual or effective value of the sale event, beyond the standard discounts typically offered.

    Also check out our insights on discounts and pricing for the health & beauty category this Black Friday.

    Retailer Performance: Who Led the Discount Race?

    Retailers showed varying discount strategies for Home & Furniture products. Walmart emerged as the leader in absolute discounts (37.5%) while Amazon offered the highest additional discount of 14%. Best Buy maintained competitive pricing across all subcategories, while Overstock and Home Depot offered relatively modest discounts.

    Black Friday - Cyber Monday Trends Across Leading Home & Furniture Retailers

    Subcategories in Focus

    Breaking down the discounts by subcategory provides deeper insights into consumer priorities and retailer strategies:

    Black Friday - Cyber Monday Trends Across Leading Home & Furniture Subcategories
    • Kitchenware saw strong competition, with Walmart (30.40% absolute discounts) and Amazon (29% absolute discounts) dominating.
    • Lighting became a discount hotspot, with Walmart offering up to 45.8% in absolute discounts and 25.3% additional markdowns.
    • Furniture remained a core focus for Target, delivering an impressive 34% average absolute discount.
    • Bedding stood out at Walmart, where discounts peaked at 49.6%.

    Brand Spotlight: Who Stood Out?

    Among top-performing brands, furniture brand Costway offered the highest discounts, with an average of 48.4%. Meanwhile, Adesso (lighting solutions), Mainstays and Safavieh (both home furnishings brands) balanced discounts and premium appeal.

    Black Friday - Cyber Monday Trends Across Leading Home & Furniture Brands

    Search Visibility: The Winners and Losers

    Share of search dynamics revealed significant shifts in brand visibility during Black Friday:

    Black Friday - Cyber Monday Trends Across Leading Home & Furniture Brands - Share of Search and Visbility
    • Furniture brand Costway (+1.2%) and home improvement player Black+Decker (+1.5%) gained visibility.
    • On the flip side, premium brands like Safavieh known for rugs and home furnishings (-16.8%) and furniture brand Burrow ( -1.7%) saw declines.

    Who Offers the Lowest Prices?

    In the previous analysis, we focused on the top 500 products within each subcategory for each retailer, showcasing the discount strategies for their highlighted or featured items. However, to identify which retailer offered the lowest or highest prices for the same set of products, it’s necessary to match items across retailers. For this, we analyzed a separate dataset of 735 matched products across Home & Furniture specific retailers to compare their pricing during Black Friday. This approach provides a clearer picture of price leadership and competitiveness across categories.

    Here are the key takeaways from this analysis.

    Category-Level Highlights

    Retailers Offering Most Value - Lowest Priced - Home & Furniture - Black Friday 2024
    • Amazon emerges as the lowest-priced retailer across Home & Furniture categories, with the highest average discount of 27.50%, closely followed by Walmart (26.09%).
    • Overstock and Wayfair trail with average discounts of 22.93% and 20.71%, respectively, while Home Depot offers the least aggressive pricing at 18.14%. This is notable, as all 3 players are known specialists in the category.

    Subcategory Highlights

    Lowest Priced Retailer Across Major Subcategories- Home & Furniture - Black Friday 2024
    • Amazon stands out as the leader in multiple subcategories, including Appliances, Furniture, Decor, and Outdoor, offering competitive average discounts of around 26-29%.
    • Overstock leads in Bedding and Kitchenware, with strong average discounts of 24.26% and 20.72%, respectively.
    • Wayfair is notable for Lighting, with an average discount of 19.95%, and is also competitive in Outdoor and Furniture categories.
    • Walmart consistently ranks high in several subcategories like Appliances and Bedding, providing solid discounts of around 22-23%.

    What’s Next

    For home & furniture retailers, driving maximum value during mega sale events like Black Friday involves offering bundles and sets to meet customer demands and trend expectations. Gaining insights into competitor discounts and pricing can help furniture retailers get an edge amid this environment.

    Want to know how DataWeave’s intelligence platform can empower your business during peak sales events? Contact us to discover more about competitive insights, price intelligence, and data-driven decision-making.
    Stay tuned to our blog to see more coverage on Black Friday 2024.

  • Health & Beauty Deals on Black Friday 2024: Insights from Top Retailers and Brands

    Health & Beauty Deals on Black Friday 2024: Insights from Top Retailers and Brands

    The U.S. health and beauty retail sector shows remarkable resilience amid economic uncertainties, with the skincare market projected to hit $21.83 billion in 2024. Black Friday data reinforces this trend, with health and beauty products seeing a 14.6% surge in web traffic compared to last year.

    At DataWeave, we conducted an in-depth analysis of Black Friday discounting trends in the U.S. health and beauty sector. DataWeave’s AI-powered pricing intelligence platform was used to monitor pricing and discounts across Sephora, Ulta Beauty, Walmart, Target, and Amazon during Black Friday 2024. The study covered 19985 SKUs from November 10-29. We focused on the top 500 products ranked for each search keyword on each retail site, using targeted terms aligned with categories like “skincare” and “fragrance”.

    The results? Beauty leads across categories in discount depth this year, with some retailers offering significant markdowns.

    The Beauty Boom: More Than Just Looking Good

    If there’s one thing the pandemic taught us, it’s that self-care isn’t just a luxury – it’s a necessity. This Black Friday proved that beauty has become an indispensable part of consumers’ lives, with retailers offering unprecedented discounts and crafting strategic promotions to capture the growing demand.

    The Absolute Discount represents the reduction of the selling price compared to the Manufacturer’s Suggested Retail Price (MSRP). The Additional Discount reflects how much lower the selling price is during Black Friday compared to its price a week before the sale. This metric reveals the actual or effective value of the sale event, beyond the standard discounts typically offered.

    Average Discounts Across Leading Health & Beauty Retailers on Black Friday 2024

    Ulta Beauty led with 45% average discounts, followed by Sephora at 38.1% and Walmart at 35.2%. In terms of additional Black Friday discounts, Ulta maintained dominance at 35%, with Sephora following at 28%.

    Hair care emerged as the standout category, with Ulta Beauty offering up to 56% discounts, reflecting sustained demand for at-home beauty routines. Skincare saw fierce competition, with Sephora emphasizing premium discounts (37%) while Walmart focused on value pricing (32.5%).

    Average Discounts Across Leading Health & Beauty Retailer Subcategories on Black Friday 2024

    Fragrance and Makeup attracted consumers with targeted promotions from Walmart and Ulta Beauty, signaling strong demand for gifting items.

    Average Discounts Across Leading Health & Beauty Brands on Black Friday 2024

    Major beauty brands echoed the sentiment. Premium skincare brand Clinique leads with 50.6% average discounts. Meanwhile, drugstore staples like Revlon (29.1%) and Maybelline (24.4%) balanced accessibility and affordability, driving mass-market appeal. Popular beauty and makeup brand L’Oreal Paris also offered a modest 22.8% average discount, reinforcing its position as a value-oriented brand.

    Share of Search and Visibility Across Leading Health & Beauty Brands on Black Friday 2024

    The more interesting story? The massive shift in brand visibility, as our share of search rankings denote:

    • Shampoo and hair care brand Tresemmé saw an unexpected 5.5% jump in the share of search results
    • Beauty brand Herbal Essences gained 5.1% in share of search well

    Declines in share of search were noted for brands like L’Oreal Paris (-1.8%) and Pantene (-0.6%), indicating missed opportunities in promotional visibility.

    Insight: What’s driving this beauty boom? TikTok and social media continue to fuel beauty purchases, with viral products driving significant search and sales spikes. Plus, the “skinification” of hair care has turned basic shampoo shopping into a full-blown beauty ritual.

    Who Offered the Lowest Prices?

    In the previous analysis, we focused on the top 500 products within each subcategory for each retailer, showcasing the discount strategies for their highlighted or featured items. However, to identify which retailer offered the lowest or highest prices for the same set of products, it’s necessary to match items across retailers. For this, we analyzed a separate dataset of 1133 matched products across Health & Beauty specific retailers to compare their pricing during Black Friday. This approach provides a clearer picture of price leadership and competitiveness across categories.

    Here are the key takeaways from this analysis.

    Retailers Offering Most Value - Lowest Priced - Health and Beauty - Black Friday 2024
    • Bloomingdale’s emerges as the overall leader, offering the highest average discount of 14.87%, closely followed by Bluemercury (12.41%).
    • Ulta Beauty ranks third (10.94%), demonstrating competitiveness across key subcategories, while Sephora trails with the lowest average discount (7.33%), reflecting a more premium positioning.
    Lowest Priced Retailer Across Major Subcategories- Health and Beauty - Black Friday 2024
    • Ulta Beauty leads in Hair Care with the highest discount (22.62%), while Bluemercury dominates in Skin Care (13.81%), Makeup (22.98%), and Fragrance (10.6%).
    • Sephora consistently offers the lowest discounts across all subcategories, reflecting their premium positioning.
    Lowest Priced Retailer Across Leading Brands- Health and Beauty - Black Friday 2024
    • Bluemercury offers the lowest prices for luxury brands like Kiehl (27.02%) and Laura Mercier (34.87%), with Bloomingdale’s closely trailing.
    • Bloomingdale’s leads for Bumble and Bumble (13.59%) and Hourglass (23.41%), showcasing strong promotional efforts.
    • Sephora maintains a more restrained discount strategy, with notable leadership only for Estée Lauder (7.18%).
    • Ulta Beauty shines in offering the steepest discount for Briogeo (33.26%), emphasizing competitiveness in key brands.

    What’s Next for Holiday Discounting?

    For retailers, the message is clear: traditional holiday playbooks need a serious update. For shoppers, it means unprecedented opportunities to score deals in categories that traditionally held firm on pricing.

    Want to stay ahead of retail trends and optimize your holiday shopping strategy? DataWeave’s commerce intelligence platform helps brands and retailers strategically navigate these shifts. Contact us to learn more about how we can help you make data-driven decisions in this rapidly evolving retail landscape.

    Stay tuned to our blog for forthcoming analyses on pricing and discounting trends across a spectrum of shopping categories, as we continue to unravel the intricacies of consumer behavior and market dynamics.

  • Early Black Friday Deals Analyzed: How Top Retailers Stack Up on Discounts

    Early Black Friday Deals Analyzed: How Top Retailers Stack Up on Discounts

    Black Friday, once confined to a single weekend, has evolved into a shopping season that now stretches well before Thanksgiving. With inflation hovering around 3% and consumer confidence showing signs of recovery, retailers are adapting their promotional calendars to capture early-bird shoppers and maintain a competitive edge.

    Major retailers, including Amazon, Walmart, Target, and Best Buy, have capitalized on this trend by launching promotions weeks in advance, signaling the traditional holiday rush is now a month-long event. At DataWeave, we put these deals under a microscope.

    Our Methodology

    Using DataWeave’s advanced, AI-powered pricing intelligence platform, we tracked early Black Friday deals across Consumer Electronics, Home & Furniture, Health & Beauty, and Apparel categories. We monitored dedicated Black Friday deal pages on Amazon, Walmart, Target, Best Buy, Nordstrom, Neiman Marcus, and Sephora to gather and analyze discount data a week prior to Black Friday weekend.

    Who’s Offering the Best Deals Across Categories?

    Our pre- Black Friday analysis reveals a clear pattern of premium brands offering deeper discounts across categories ahead of the holiday. Here are some key findings around retail players:

    • Walmart emerges as the most aggressive discounter across categories, leading in Health & Beauty (57.07%), Apparel (48.97%), and Consumer Electronics (43.35%).
    • Amazon maintains consistent but lower discounts (28-29%) across categories, suggesting potential deeper cuts ahead.
    • Best Buy and Sephora, both category specialists, play it conservative compared to mass retail players.

    Let’s look at each category more closely to get a detailed snapshot of the deals this Thanksgiving week:

    Health & Beauty

    Our analysis reveals that it’s not electronics, but the health & beauty category that leads with the widest discount range pre Black Friday, making it the category to watch out for.

    • Walmart takes the lead with an aggressive 57.1% average discount in this category, capitalizing on its value-oriented reputation.
    • Beauty specialist Sephora holds modest beauty discounts (32.81%) compared to other retailers.
    • Amazon offers the broadest range of SKUs (571) in the category.
    Avg. Discounts Across Retailers Pre Black Friday 2024 - Health & Beauty

    Among the health & beauty brands we analyzed, cosmetics brand Tarte and viral K-Beauty skincare brand COSRX stand out with discounts above 40%, appealing to cost-conscious beauty enthusiasts.

    Brands with Highest Avg. Discounts Before Black Friday 2024 - Health & Beauty

    Consumer Electronics

    Our pre- Black Friday analysis reveals interesting insights about consumer electronics deals this season.

    • Walmart, once again, emerges as the frontrunner in the category with 43.4% average discounts.
    • Best Buy plays it conservative in electronics (30.75%), despite being a category specialist, but offers the most extensive SKU coverage (3030).
    • Amazon’s consistent 29.7% discount across 1,749 SKUs suggests they’re probably holding back their best deals for Prime members during Black Friday.
    Avg. Discounts Across Retailers Pre Black Friday 2024 - Consumer Electronics

    Brand-specific data for the category reveals significant deals on Speck (48.07%) and smart TV brand Insignia (39.22%), making accessories and mid-tier electronics attractive for early shoppers. Core computing (HP at 32.14%) and electronics brands maintain more conservative discounts. It remains to be seen if this changes on Black Friday or Cyber Monday.

    Brands with Highest Avg. Discounts Before Black Friday 2024 - Consumer Electronics

    Apparel

    Our analysis of the apparel category reveals several highlights:

    • In the apparel category too, Walmart dominates with an impressive 49% average discount, effectively targeting price-sensitive shoppers in the fashion segment.
    • Nordstrom and Neiman Marcus, both known for apparel, offer significant discounts at 43.2% and 37.8% respectively.
    • Amazon’s expansive SKU coverage (1344) is countered by a modest 29.5% discount, showing its focus on variety over depth of discounts.
    Avg. Discounts Across Retailers Pre Black Friday 2024 - Apparel

    Premium fashion brands dominate the highest discounts this Black Friday in the apparel category. Vince Camuto leads with over 45.1% average discount. Notably, Levi and Nike’s aggressive 44.43% and 43.50% discounts suggests significant inventory positions or intent to capture market share.

    Brands with Highest Avg. Discounts Before Black Friday 2024 - Apparel

    Home & Furniture

    Our analysis reveals an interesting trend across the category.

    • In the home & furniture category too, Walmart leads at 41.8% average discounts. Target follows closely, but with significantly lesser SKUs on offer.
    • Amazon’s 28.1% discount, though the lowest among major players, spans a substantial 1,982 SKUs, reinforcing its position as a marketplace for diverse needs.
    Avg. Discounts Across Retailers Pre Black Friday 2024 - Home & Furniture

    Top 3 Products With the Highest Discounts Across Retailers

    To provide a clearer picture of the early Black Friday landscape, we analyzed the top 3 products with the most substantial discounts in consumer electronics and health & beauty categories. These insights highlight how retailers are leveraging strategic discounts on high-value items to attract early shoppers.

    Top Discounted Products in Consumer Electronics

    Premium TVs dominate the discount scene, with LG’s 83″ OLED offering up to 44.5% off on Amazon, closely followed by a 44.4% discount on Best Buy, showcasing aggressive competition. The same product has much lower discounting on Walmart, but notably, the product is retailed at $3999.9, at least $1000 less than other retailers, highlighting Walmart’s commitment to offering lowest prices.

    Products With Highest Discounts Pre Black Friday 2024 - Consumer Electronics - TVs
    Products With Highest Discounts Pre Black Friday 2024 - Consumer Electronics - Playstation
    Products With Highest Discounts Pre Black Friday 2024 - Consumer Electronics - Digital Cameras

    Gaming consoles, like the PlayStation 5 Slim Bundle, show moderate discounts (ranging from 15% on Walmart and Target to 25% at Best Buy), appealing to tech-savvy shoppers.

    Notable competition is evident in price matching across major retailers, particularly in TVs and high-value electronics like the Nikon Z 8 camera, where Walmart offers the deepest discount at 13.75%, edging past Amazon and Best Buy.

    Top Discounted Products in Health & Beauty

    Viral skincare staples like Tatcha’s Water Cream show tight discounting consistency, with Walmart offering 19.47% off compared to Amazon’s 20% and Sephora’s 20.83%.

    Products With Highest Discounts Pre Black Friday 2024 - Health & Beauty - Tatcha Water Cream
    Products With Highest Discounts Pre Black Friday 2024 - Health & Beauty - Olaplex Hair Oil
    Products With Highest Discounts Pre Black Friday 2024 - Health & Beauty - Yves Saint Laurent Satin Lipstick

    Trending haircare brand Olaplex displays greater disparity, with Walmart leading with a 33.33% discount, surpassing Amazon and Sephora. Luxury brand, Yves Saint Laurent’s Satin Lipstick is one of the highest discounted items across retailers.

    Looking Ahead

    Our analysis suggests that while some early deals offer genuine value, particularly in premium beauty and high-end electronics, many retailers might be holding their best discounts for Black Friday.

    For shoppers, the key is being selective: jump on premium brand discounts now (since they’re likely to remain the same though the weekend), but wait on mid-range electronics and home goods where better deals are likely to emerge on Black Friday or Cyber Monday.

    For retailers, the imperative is clear: dynamic pricing intelligence is crucial for maintaining a competitive edge while protecting margins. Competitive insights will be critical as the holiday season progresses to balance market share against profitability.

    Stay tuned for our Black Friday Cyber Monday analysis next week, where we’ll track how these early discounts compare to the main event’s deals!

  • Redefining Product Attribute Tagging With AI-Powered Retail Domain Language Models

    Redefining Product Attribute Tagging With AI-Powered Retail Domain Language Models

    In online retail, success hinges on more than just offering quality products at competitive prices. As eCommerce catalogs expand and consumer expectations soar, businesses face an increasingly complex challenge: How do you effectively organize, categorize, and present your vast product assortments in a way that enhances discoverability and drives sales?

    Having complete and correct product catalog data is key. Effective product attribute tagging—a crucial yet frequently undervalued capability—helps in achieving this accuracy and completeness in product catalog data. While traditional methods of tagging product attributes have long struggled with issues of scalability, consistency, accuracy, and speed, a new thinking and fundamentally new ways of addressing these challenges are getting established. These follow from the revolution brought in Large Language Models but they fashion themselves as Small Language Models (SLM) or more precisely as Domain Specific Language Models. These can be potentially considered foundational models as they solve a wide variety of downstream tasks albeit within specific domains. They are a lot more efficient and do a much better job in those tasks compared to an LLM. .

    Retail Domain Language Models (RLMs) have the potential to transform the eCommerce customer journey. As always, it’s never a binary choice. In fact, LLMs can be a great starting point since they provide an enhanced semantic understanding of the world at large: they can be used to mine structured information (e.g., product attributes and values) out of unstructured data (e.g., product descriptions), create baseline domain knowledge (e.g, manufacturer-brand mappings), augment information (e.g., image to prompt), and create first cut training datasets.

    Powered by cutting-edge Generative AI and RLMs, next-generation attribute tagging solutions are transforming how online retailers manage their product catalog data, optimize their assortment, and deliver superior shopping experiences. As a new paradigm in search emerges – based more on intent and outcome, powered by natural language queries and GenAI based Search Agents – the capability to create complete catalog information and rich semantics becomes increasingly critical.

    In this post, we’ll explore the crucial role of attribute tagging in eCommerce, delve into the limitations of conventional tagging methods, and unveil how DataWeave’s innovative AI-driven approach is helping businesses stay ahead in the competitive digital marketplace.

    Why Product Attribute Tagging is Important in eCommerce

    As the eCommerce landscape continues to evolve, the importance of attribute tagging will only grow, making it a pertinent focus for forward-thinking online retailers. By investing in robust attribute tagging systems, businesses can gain a competitive edge through improved product comparisons, more accurate matching, understanding intent, and enhanced customer search experiences.

    Taxonomy Comparison and Assortment Gap Analysis

    Products are categorized and organized differently on different retail websites. Comparing taxonomies helps in understanding focus categories and potential gaps in assortment breadth in relation to one’s competitors: missing product categories, sizes, variants or brands. It also gives insights into the navigation patterns and information architecture of one’s competitors. This can help in making search and navigation experience more efficient by fine tuning product descriptions to include more attributes and/or adding additional relevant filters to category listing pages.

    For instance, check out the different Backpack categories on Amazon and Staples in the images below.

    Product Names and Category Names Differ on Different eCommerce Platforms - Here's an Amazon Example
    Product Names and Category Names Differ on Different eCommerce Platforms - Here's a Staples Example

    Or look at the nomenclature of categories for “Pens” on Amazon (left side of the image) and Staples (right side of the image) in the image below.

    Product Names and Category Names Differ on Different eCommerce Platforms -Here's how Staples Vs. Amazon Categories look for Pens

    Assortment Depth Analysis

    Another big challenge in eCommerce is the lack of standardization in retailer taxonomy. This inconsistency makes it difficult to compare the depth of product assortments across different platforms effectively. For instance, to categorize smartphones,

    • Retailer A might organize it under “Electronics > Mobile Phones > Smartphones”
    • Retailer B could use “Technology > Phones & Accessories > Cell Phones”
    • Retailer C might opt for “Consumer Electronics > Smartphones & Tablets”

    Inconsistent nomenclature and grouping create a significant hurdle for businesses trying to gain a competitive edge through assortment analysis. The challenge is exacerbated if you want to do an in-depth assortment depth analysis for one or more product attributes. For instance, look at the image below to get an idea of the several attribute variations for “Desks” on Amazon and Staples.

    With Multiple Attributes Named in a Variety of Ways, Attribute Tagging is Essential to Ensure Accurate Product Matching

    Custom categorization through attribute tagging is essential for conducting granular assortment comparisons, allowing companies to accurately assess their product offerings against those of competitors.

    Enhancing Product Matching Capabilities

    Accurate product matching across different websites is fundamental for competitive pricing intelligence, especially when matching similar and substitute products. Attribute tagging and extraction play a crucial role in this process by narrowing down potential matches more effectively, enabling matching for both exact and similar products, and tagging attributes such as brand, model, color, size, and technical specifications.

    For instance, when choosing to match similar products in the Sofa category for 2-3 seater sofas from Wayfair and Overstock, tagging attributes like brand, color, size, and more is a must for accurate comparisons.

    Attribute Tagging for Home & Furniture Categories Like Sofas Helps Improve Matching Accuracy
    Attribute Tagging for Home & Furniture Categories Like Sofas Helps Improve Matching Accuracy

    Taking a granular approach not only improves pricing strategies but also helps identify gaps in product offerings and opportunities for expansion.

    Fix Content Gaps and improve Product Detail Page (PDP) Content

    Attribute tagging plays a vital role in enhancing PDP content by ensuring adherence to brand integrity standards and content compliance guidelines across retail platforms. Tagging attributes allows for benchmarking against competitor content, identifying catalog gaps, and enriching listings with precise details.

    This strategic tagging process can highlight missing or incomplete information, enabling targeted optimizations or even complete rewrites of PDP content to improve discoverability and drive conversions. With accurate attribute tagging, businesses can ensure each product page is fully optimized to capture consumer attention and meet retail standards.

    Elevating the Search Experience

    In today’s online retail marketplace, a superior search experience can be the difference between a sale and a lost customer. Through in-depth attribute tagging, vendors can enable more accurate filtering to improve search result relevance and facilitate easier product discovery for consumers.

    By integrating rich product attributes extracted by AI into an in-house search platform, retailers can empower customers with refined and user-friendly search functionality. Enhanced search capabilities not only boost customer satisfaction but also increase the likelihood of conversions by helping shoppers find exactly what they’re looking for more quickly and with minimal effort.

    Pitfalls of Conventional Product Tagging Methods

    Traditional methods of attribute tagging, such as manual and rule-based systems, have been significantly enhanced by the advent of machine learning. While these approaches may have sufficed in the past, they are increasingly proving inadequate in the face of today’s dynamic and expansive online marketplaces.

    Scalability

    As eCommerce catalogs expand to include thousands or even millions of products, the limitations of machine learning and rule-based tagging become glaringly apparent. As new product categories emerge, these systems struggle to keep pace, often requiring extensive revisions to existing tagging structures.

    Inconsistencies and Errors

    Not only is reliance on an entirely human-driven tagging process expensive, but it also introduces a significant margin for error. While machine learning can automate the tagging process, it’s not without its limitations. Errors can occur, particularly when dealing with large and diverse product catalogs.

    As inventories grow more complex to handle diverse product ranges, the likelihood of conflicting or erroneous rules increases. These inconsistencies can result in poor search functionality, inaccurate product matching, and ultimately, a frustrating experience for customers, drawing away the benefits of tagging in the first place.

    Speed

    When product information changes or new attributes need to be added, manually updating tags across a large catalog is a time-consuming process. Slow tagging processes make it difficult for businesses to quickly adapt to emerging market trends causing significant delays in listing new products, potentially missing crucial market opportunities.

    How DataWeave’s Advanced AI Capabilities Revolutionize Product Tagging

    Advanced solutions leveraging RLMs and Generative AI offer promising alternatives capable of overcoming these challenges and unlocking new levels of efficiency and accuracy in product tagging.

    DataWeave automates product tagging to address many of the pitfalls of other conventional methods. We offer a powerful suite of capabilities that empower businesses to take their product tagging to new heights of accuracy and scalability with our unparalleled expertise.

    Our sophisticated AI system brings an advanced level of intelligence to the tagging process.

    RLMs for Enhanced Semantic Understanding

    Semantic Understanding of Product Descriptions

    RLMs analyze the meaning and context of product descriptions rather than relying on keyword matching.
    Example: “Smartphone with a 6.5-inch display” and “Phone with a 6.5-inch screen” are semantically similar, though phrased differently.

    Attribute Extraction

    RLMs can identify important product attributes (e.g., brand, size, color, model) even from noisy or unstructured data.
    Example: Extracting “Apple” as a brand, “128GB” as storage, and “Pink” as the color from a mixed description.

    Identifying Implicit Relationships

    RLMs find implicit relationships between products that traditional rule-based systems miss.
    Example: Recognizing that “iPhone 12 Pro” and “Apple iPhone 12” are part of the same product family.

    Synonym Recognition in Product Descriptions

    Synonym Matching with Context

    RLMs identify when different words or phrases describe the same product.
    Examples: “Sneakers” = “Running Shoes”, “Memory” = “RAM” (in electronics)
    Even subtle differences in wording, like “rose gold” vs “pink” are interpreted correctly.

    Overcoming Brand-Specific Terminology

    Some brands use their own terminologies (e.g., “Retina Display” for Apple).
    RLMs can map proprietary terms to more generic ones (e.g., Retina Display = High-Resolution Display).

    Dealing with Ambiguities

    RLMs analyze surrounding text to resolve ambiguities in product descriptions.
    Example: Resolving “charger” to mean a “phone charger” when matched with mobile phones.

    Contextual Understanding for Improved Accuracy and Precision

    By leveraging advanced natural language processing (NLP), DataWeave’s AI can process and understand the context of lengthy product descriptions and customer reviews, minimizing errors that often arise at human touch points. The solution processes and interprets information to extract key information to dramatically improve the overall accuracy of product tags.

    It excels at grasping the subtle differences between similar products, sizes, colors and identifying and tagging minute differences between items, ensuring that each product is uniquely and accurately represented in a retailer’s catalog.

    This has a major impact on product and similarity-based matching that can even help optimize similar and substitute product matching to enhance consumer search. At the same time, our AI can understand that the same term might have different meanings in various product categories, adapting its tagging approach based on the specific context of each item.

    This deep comprehension ensures that even nuanced product attributes are accurately captured and tagged for easy discoverability by consumers.

    Case Study: Niche Jewelry Attributes

    DataWeave’s advanced AI can assist in labeling the subtle attributes of jewelry by analyzing product images and generating prompts to describe the image. In this example, our AI identifies the unique shapes and materials of each item in the prompts.

    The RLM can then extract key attributes from the prompt to generate tags. This assists in accurate product matching for searches as well as enhanced product recommendations based on similarities.

    DataWeave's AI assists in extracting contextual attributes for accuracy in product matching

    This multi-model approach provides the flexibility to adapt as product catalogs expand while remaining consistent with tagging to yield more robust results for consumers.

    Unparalleled Scalability

    DataWeave can rapidly scale tagging for new categories. The solution is built to handle the demands of even the largest eCommerce catalogs enabling:

    • Effortless management of extensive product catalogs: We can process and tag millions of products without compromising on speed or accuracy, allowing businesses to scale without limitations.
    • Automated bulk tagging: New product lines or entire categories can be tagged automatically, significantly reducing the time and resources required for catalog expansion.

    Normalizing Size and Color in Fashion

    Style, color, and size are the core attributes in the fashion and apparel categories. Style attributes, which include design, appearance, and overall aesthetics, can be highly specific to individual product categories.

    Normalizing Size and Color in Fashion for Product Matching

    Our product matching engine can easily handle color and sizing complexity via our AI-driven approach combined with human verification. By leveraging advanced technology to identify and normalize identical and similar products from competitors, you can optimize your pricing strategy and product assortment to remain competitive. Using Generative AI in normalizing color and size in fashion is key to powering competitive pricing intelligence at DataWeave.

    Continuous Adaptation and Learning

    Our solution evolves with your business, improving continuously through feedback and customization for retailers’ specific product categories. The system can be fine-tuned to understand and apply specialized tagging for niche or industry-specific product categories. This ensures that tags remain relevant and accurate across diverse catalogs and as trends emerge.

    The AI in our platform also continuously learns from user interactions and feedback, refining its tagging algorithms to improve accuracy over time.

    Stay Ahead of the Competition With Accurate Attribute Tagging

    In the current landscape, the ability to accurately and consistently tag product attributes is no longer a luxury—it’s essential for staying competitive. With advancements in Generative AI, companies like DataWeave are revolutionizing the way product tagging is handled, ensuring that every item in a retailer’s catalog is presented with precision and depth. As shoppers demand a more intuitive, seamless experience, next-generation tagging solutions are empowering businesses to meet these expectations head-on.

    DataWeave’s innovative approach to attribute tagging is more than just a technical improvement; it’s a strategic advantage in an increasingly competitive market. By leveraging AI to scale and automate tagging processes, online retailers can keep pace with expansive product assortments, manage content more effectively, and adapt swiftly to changes in consumer behavior. In doing so, they can maintain a competitive edge.

    To learn more, talk to us today!

  • Mastering Grocery Pricing Intelligence: A Strategic Approach for Modern Retailers

    Mastering Grocery Pricing Intelligence: A Strategic Approach for Modern Retailers

    When egg prices surged 70% during the 2023 avian flu outbreak, grocery retailers faced a critical dilemma: maintain margins and risk losing customers, or absorb costs and watch profits evaporate. Similarly, rising olive oil and chocolate prices also had domino effects, cascading down from retailers to consumers. In each of these scenarios, those with sophisticated pricing intelligence systems adapted swiftly, finding the sweet spot between competitiveness and profitability. Others weren’t so fortunate.

    This scenario continues to play out daily across thousands of products in the grocery sector. From breakfast cereals to fresh produce to bottled water, retailers must orchestrate pricing across a variety of categories – each with its own competitive dynamics, margin requirements, and price sensitivity patterns.

    The Evolution of Grocery Pricing Intelligence

    Imagine these scenarios in the grocery industry:

    • Milk prices spike during a supply shortage.
    • Your competitor drops egg prices by 20%.
    • Fresh produce costs fluctuate with an unseasonable frost.

    For grocery retailers, these aren’t occasional challenges—they’re Tuesday. Reacting to each pricing crisis as it comes isn’t just exhausting—it’s a recipe for shrinking margins and missed opportunities.

    Think of it this way: If you’re constantly playing defense with your pricing strategy, you’re already two steps behind. Commoditized items like milk and eggs face intense price competition, while seasonal products and fresh produce demand constant attention. Simply matching competitor prices or adjusting for cost changes isn’t enough anymore. What’s needed is a proactive approach that anticipates market shifts before they happen and turns pricing challenges into competitive advantages. This is where price management comes in.

    Price management has transformed from simple competitor checks into a strategic power play that can make or break a retailer’s market position. Weekly manual adjustments have given way to a long-term strategic view, driven by data analytics and market intelligence. Here are the basics of how price management in grocery retail works today.

    Three Pillars of Grocery Price Management

    1. Smart Data Collection: Building Your Foundation

    The journey begins with comprehensive data collection and storage across your entire product ecosystem. This means:

    • Complete Coverage Of All SKUs Across All Stores: Tracking prices for all SKUs across all stores, with particular attention to high-velocity items and volatile categories.
    • Dynamic Monitoring: Tracking prices across different time frequencies as grocery prices are highly volatile for different categories. So daily tracking for volatile items like dairy and produce, and weekly for more stable categories may be needed.
    • Competitive Intelligence: Gathering data not just on prices, but on promotions, pack sizes, and private label alternatives.
    • Infrastructure to Support Large Volumes of Data: Partnering with external data and analytics providers to bridge the gap when retailers struggle with the scale of digital infrastructure these data sets require.

    2. Intelligent Data Refinement: Making Sense of the Numbers

    Raw data alone isn’t enough—it needs context and structure to become actionable intelligence. This is called Data Refinement—the process of establishing meaningful relationships within the data to facilitate the extraction of valuable insights. This refinement stage is closely tied to the data collection strategy, as the quality and depth of the insights derived depend on the accuracy and coverage of the collected data.

    Data refinement includes several key processes:

    Advanced Product Matching

    Picture this: You’re tracking a competitor’s pricing on organic apples. Simple, right? Not quite. Yes, Universal Product Codes (UPCs) and Price Lookup Codes (PLUs) are present in Grocery to standardize product identification across different retailers—unlike the fashion industry’s endless style variations. Still, product matching isn’t as straightforward as scanning barcodes.

    Grocery Pricing Intelligence data faces a challenge when product names, weights, and details differ

    Here’s the catch: many retailer websites don’t display them. Then there’s the private label puzzle—your “Store’s Best” organic apples need to match against competitors’ house brands, each with their own unique UPC. Throw in different sizes (4 Apples vs. 1Kg of Apples), regional product names (fancy naming for plain old arugula), and international brand variations (like the name for Sprite in the USA and China), and you’ve got yourself a complex matching challenge that would make conventional pricing intelligence providers sweat.

    Grocery Pricing Intelligence data faces a challenge when different naming conventions and languages are used in different geographies

    Custom Product Relationships for Consistent Pricing and Competitive Positioning

    Think like a shopper browsing the dairy aisle. You regularly buy your family’s favorite organic yogurt, the 24oz tub. But today, you notice the larger 32oz size is on sale – except the 24oz isn’t. As you stand there, confused, you wonder: Is the sale only for the bigger size? Did I miss a promotion? Should I buy the 32oz even though it’s more than I need?

    For shoppers, this inconsistent pricing across product variations creates a frustrating experience. Establishing clear relationships between related items in your catalog is essential for maintaining consistent pricing and a coherent competitive strategy.

    Grocery Pricing Intelligence data refinement involves Custom Product Relationships for Consistent Pricing and Competitive Positioning

    Start by linking products based on attributes like size, brand, and packaging. That way, when you adjust the price of the 32oz yogurt, the 24oz version automatically updates too – no more scrambling to ensure uniform pricing across your assortment. Similarly, products of the same brand but with flavor variations should be connected to keep pricing consistent.

    Taking this one step further, mapping your competitors’ exact and similar products is crucial for comprehensive competitive intelligence. Distinguishing between premium and private label tiers, national brands, and regional players gives you a holistic view of the landscape. With this understanding, you can hone your pricing strategies to maintain a clear, compelling position across your entire category lineup.

    Consistent pricing, whether across your own product variations or against competitors, provides clarity and accuracy in your overall competitive positioning. By establishing these logical connections, you avoid the customer confusion of seemingly random, inconsistent discounts – and ensure your pricing strategies work in harmony, not disarray.

    The Role of AI and Data Sciences in Data Refinement

    On the surface, linking products based on attributes like size, brand, and packaging seems like a no-brainer. But developing and maintaining the systems to accurately and automatically identify these connections? That’s a whole different animal.

    Think about it – you’re not just dealing with text-based product titles and UPCs. There are images, videos, regional variations, private labels, and a whole host of other data types and industry nuances to account for.

    Luckily, DataWeave is one of the few companies that’s truly cracked the code. Our multimodal AI models are trained to process all those diverse data formats – from granular product specs to zany regional produce names. And it’s not just about technology; we also harness the power of human intelligence.

    See, in the grocery world, category managers are the real decision makers. They know their shelves inside and out and can spot those tricky connections in product matching, especially when they are not UPC-based. That’s why DataWeave built in a Human-in-the-Loop (HITL) process, where their AI systems continuously learn from expert feedback. It’s a feedback loop that allows our customers to pitch in and keep product relationships accurate, reliable, and always adapting to new market realities.

    So while product mapping may seem straightforward on the surface, the reality is it takes some serious horsepower to do it right. Thankfully, DataWeave has both the technical chops and the grocery industry know-how to make it happen. Because when it comes to pricing intelligence, getting those product connections right is half the battle.

    3. Strategic Implementation: Turning Insights into Action

    The true value of pricing intelligence (PI) is realized through its strategic application. Although many view PI as a technical function, its strategic significance is increasing, particularly in the context of recent economic pressures like inflation. Here’s why:

    Tactical vs Strategic Use of Data: From Standard Reporting to Competitive Analysis

    Pricing intelligence has come a long way from the days of simply reacting to daily price changes. These days, it’s not just about firefighting—it’s about driving long-term strategy.

    You can use pricing data to make quick, tactical adjustments, like matching a competitor’s sudden price drop on milk. Or, you can leverage that same data to predict market trends, optimize your product lineup, and shape your overall pricing strategy. Retailers who take that strategic view can get out ahead of the curve, anticipating shifts instead of just chasing them.

    DataWeave supports both of these approaches. Our Standard Reporting tools give pricing managers the nitty-gritty details they need—current practices, historical patterns, and operational KPIs. It’s all the insights you’d expect for making those tactical, day-to-day tweaks.

    In addition, DataWeave offers something more powerful: Competitive analysis. This is where pricing intelligence becomes a true strategic weapon. By providing a high-level view of market positioning, competitor moves, and untapped opportunities, competitive analysis empowers leadership to make proactive, big-picture decisions.

    Armed with this broader perspective, retailers can start taking a more surgical approach. Maybe you need to adjust pricing zones to better meet customer demands. Or rethink your overall strategies to stay ahead of the competition, not just keep pace. It’s the difference between constantly putting out fires and systematically fortifying your entire pricing fortress.

    Beyond Pricing: Comprehensive Data for Broader Insights

    Pricing intelligence is just the tip of the iceberg. When you really start to refine and harness your data, the possibilities for grocery retailers expand far beyond simple price comparisons. Think about it – all that information you’re collecting on products, markets, and consumer behavior? That’s a goldmine waiting to be tapped. Sure, you can use it to keep a pulse on competitor pricing. But why stop there?

    What if you could leverage that data to optimize your product assortment, making sure you’re stocking the right mix to meet customer demands? Or tap into predictive analytics to get a glimpse of future market shifts, so you can get out ahead of the curve? How about using it to streamline your supply chain, identify availability inefficiencies, and get products to shelves faster?

    Sure, pricing intelligence will always be mission-critical. But when you couple it with these other data-driven insights, that’s when grocery retailing gets really interesting. It’s about evolving from a price-matching robot to a true strategic visionary, armed with the intelligence to take your business to new heights.

    Looking Ahead: The Future of Grocery Pricing Intelligence

    The grocery pricing landscape continues to evolve, driven by:

    • Integration of AI and machine learning for predictive pricing
    • Enhanced focus on omnichannel pricing consistency
    • Growing importance of personalization in pricing strategies

    Pricing intelligence isn’t just about having data—it’s about having the right data and knowing how to use it strategically. Success requires a comprehensive approach that combines robust data collection, sophisticated analysis, and strategic implementation.

    By embracing modern pricing intelligence tools and strategies, grocery retailers can navigate market volatility, maintain competitive positioning, and drive sustainable growth. The key lies in building a pricing ecosystem that’s both sophisticated enough to handle complex data and flexible enough to adapt to changing market conditions.

    Ready to transform your pricing strategy? Check out our grocery price tracker to get month-on-month updates on grocery prices in the real world. Contact us to learn how our advanced pricing intelligence solutions can help your business stay ahead in the competitive grocery market.

  • 10 SEO Tactics to Help Retail Brands Win More Search Visibility on Amazon

    10 SEO Tactics to Help Retail Brands Win More Search Visibility on Amazon

    Today, the first name that comes to anybody’s mind when they hear about online shopping is Amazon. In the US alone, Amazon accounted for over 37.6 percent of total online retail sales in 2023 with the second place Walmart not even managing to win double-digit numbers on the same scale.

    Amazon leads retail eCommerce in the USA

    With such a phenomenal market share, it is not surprising that any retail brand would want to have their products listed on Amazon for sale. However, as enticing as the potential exposure could be, the overwhelming presence of brands selling similar products on Amazon is so huge that getting fair visibility for your products may require some heavy-lifting support.

    Will the Same SEO You Use for Google Work with Amazon?

    Unfortunately, no, as Google and Amazon have different objectives when it comes to search rankings on their respective customer platforms. Google makes the lion’s share of its revenue from search advertising, whereas Amazon makes money when customers buy products listed on its platform by sellers.

    Relying on traditional search engine optimization (SEO) techniques may not get the desired results as they are more optimized for search engines like Google. Amazon embraces its unique DNA when it comes to product display rankings on its search option.

    How Does SEO Work in Amazon?

    Over the years, Amazon amassed data about shopping experiences that billions of customers globally had on its platform. With this data, they developed their custom search algorithm named A9. Contrary to the gazillion objectives that Google has for its intelligent search algorithms, Amazon has tasked A9 with just a simple straightforward target—when a customer keys in a search query, provide the best choice of products that they will most probably purchase, as search results.

    A9 works to fulfill the mission of guiding shoppers to the right product without worrying about semantics, context, intent, mind mapping, etc. of the search query in contrast to what Google does. As with Google search, Amazon does have paid advertising and sponsored results options such as Amazon PPC, Headline ads, etc. but their SEO algorithms are aware of how to support and boost search rankings of genuine products and brands that have taken an effort to follow best practices in Amazon SEO as well as have a great offering with attractive prices.

    As additional knowledge, Amazon also has clear guidelines on what it prioritizes for search rankings. Known in the SEO world as Amazon ranking signals, these are core factors that influence how a product is ranked for search queries. Some of the top Amazon ranking signals that carry heavy influence on search rankings include on-page signals, off-page signals, sales rank, best sellers rank, etc.

    What Brands Need to Strategize to Master the Amazon SEO Algorithms

    From a broad perspective, we can classify the actions brands need to take in this regard in 3 core stages:

    Pre-Optimization

    This deals with getting first-hand knowledge about both customers who are likely to purchase your product and the competitors who are vying for sales from these very same customers. Filtering your target customer or audience is essential to ensure that you get the most ROI from marketing initiatives and that sales cycles are accelerated. For example, if your product is a premium scented candle, there is no point in wasting advertising dollars trying to win attention from customers who are not likely to ever spend on luxury home décor items.

    Knowing how your competitors are performing on Amazon search, the keywords, and SEO strategies they have adapted is critical to ensure that you stay one step ahead.

    Product Listing Page Optimization

    This includes strategies that a brand can adopt so that its product description page gets the much-needed content optimizations to sync with Amazon’s A9 algorithm. It has a mix of keyword-integrated content, relevant images, descriptions in easy-to-understand language, localized content flavors to resonate with target buyers, etc. For example, a kitchen tool like a grater might be used for different kinds of food preparation techniques in different regions of the same country.

    Product Listing Optimization For Amazon SEO

    The brand must ensure that the description adequately localizes the linguistic or usage preference representation of the target audience. If the grater is used for grating coconut shells to extract the fibrous pulp in the Midlands and for grating ginger skin in the Far East, both use cases should be part of the product description if the target customers are from both regions.

    Sales Optimization

    This deals with options that have more sales strategies integrated into their core. For example, blogs on popular websites with the Amazon purchase link embedded in the content, collaboration with social media influencers, paid advertising on Amazon itself as well as on search engines, video ads, banner and display ads, etc.

    The key intent here is to drive organic and inorganic traffic to the Amazon product listing page and ultimately win sales.

    How Can Your Products Rank High in Amazon Search Results? Top 10 Tactics

    Now that you have a clear understanding of the strategies that help in mastering Amazon’s ranking algorithms, here are some great tips to help achieve higher search rankings for your products on Amazon search:

    1. Target Relevant Keywords

    You need to figure out the best keywords that match what customers put as queries into the Amazon search bar. Your brand needs to clearly understand customer behavior when they arrive on Amazon to search for a product or category of products. The best place to begin looking for the same would be on competitor pages on Amazon. The keywords that helped them rank well on Amazon can help you as well. Manually investigating such a large pool of competitors is nearly impossible but with the right tools, you can easily embrace capabilities to know which keywords can help you in mimicking the success of your competitors.

    2. Focus on Product Titles

    Every single part of the content in your brand’s Amazon storefront or product page needs dedicated focus. Beginning with the product titles, effort needs to be made to ensure that they include the brand name, key product category or features, and other relevant keyword information.

    Product Title Optimized for Amazon SEO

    In other words, product titles must be optimized for searchability. This searchability for product titles needs to be optimized for both mobile and desktop screens.

    3. Create Product Descriptions that Resonate with the Audience

    For product descriptions on your Amazon webpage, you need to figure out the optimal quality levels needed for the intended audience. Effective content can help achieve better search ranking visibility and convince the incoming traffic of shoppers to make a purchase. It is important to periodically review and modify your page content to suit the interests of visitors from both web and mobile devices.

    Product Description Optimized for Amazon SEO

    Leveraging solutions like DataWeave can help with regular content audits to ensure you are putting out the best product content that will delight shoppers and deliver on sales conversion targets.

    4. Use High-Quality Media Assets like Images and Videos

    Promoting your product doesn’t have to be restricted to just textual content in Amazon product description sections. You can use other multimedia assets of high quality. These include images, videos, brochure images, etc. Every content asset must aim to educate shoppers on why your product should be their number one choice. For example, look at this detailed product description for the viral K-Beauty product COSRX Mucin Essence.

    Product Description with Images Optimized for Amazon SEO

    Moreover, images can help attract more attention span from visitors, thereby increasing the probability of purchases.

    5. Strengthen the Backend Keywords As Well

    Amazon also supports hidden backend keywords that sellers add to their product listings. They help add more relevance to products similar to meta descriptions and titles in traditional SEO for search engines like Google. A typical backend keyword may comprise synonyms, misspelled keywords, textual variations, etc. However, knowing how to pick the right ones is crucial. By analyzing your keyword rankings against competitors and higher-ranking product results in search, the platform can help you consistently optimize your content backend to help grow visibility.

    6. Focus on Reviews and Ratings

    Reviews and ratings on product pages are key insights that help customers with their purchasing decisions. So, it is natural for brands to keep a close eye on how their products are faring in this regard. Reviews and ratings are a direct indication of the trustworthiness of your product. When previous buyers rate you high and leave favorable reviews on your product, it will directly promote trust and help you secure a better rapport with new customers.

    Reviews with Videos and Images Optimized for Amazon SEO
    Requesting reviews or leveraging user generated reviews and ratings to optimize Amazon SEO

    This upfront advantage can help boost sales conversions better. Leveraging solutions like DataWeave can help you understand the sentiments that customers have for your products by intelligently analyzing reviews and ratings.

    7. Implement Competitive Pricing Strategies

    The goal of most customers when shopping online is to get their desired product at the most affordable prices. The eCommerce price wars every year are growing in scale today and getting your product pricing right is crucial for sales. However, there is a need to gain comprehensive insights into how your competitors are pricing their offerings and how the market responds to specific price ranges. Solutions like DataWeave help your brand access specific insights into pricing. By analyzing competitor pricing, you can create a winning price model that is sustainable for your brand and favorable for target customers.

    8. Track Share of Search

    Content and other SEO activities will help improve your search rankings on Amazon. However, it is equally important to know how well your products are performing periodically against your competitors for the same set of specific keyword searches. You need to understand the share of search that your products are achieving to formulate improvement strategies. DataWeave’s Digital Shelf Analytics solution provides share of search insights helping you uncover deep knowledge on your discoverability on Amazon (and other marketplaces) for your vital search keywords.

    9. Ensure Stock Availability

    To achieve better ranking results, brands need to ensure that the relevant products matching the search keywords are available for quick delivery at the desired ZIP codes where users are more likely to search and order them. Out-of-stock items seldom show up high on search results. Certain products, especially if they’re popular, can get stocked out frequently in certain locations. Keeping a close eye on your stock availability across the map can help minimize these scenarios.

    10. Optimize Your Brand Presence

    While optimizing content and other key areas within the Amazon webpage for your product is critical, there are other avenues to help boost search rankings. One such option includes registering in the Amazon Brand Registry, which provides more beneficial features like protection against counterfeits and ensuring that your brand page is optimized according to Amazon storefront standards.

    The Bottom Line

    Winning the top spot in Amazon search ranking is crucial for brands that aim to capitalize on online sales revenue to grow their business. Knowing your workaround for Amazon’s proprietary SEO frameworks and algorithms is the first step to succeeding. The key element of success is your ability to gain granular insights into the areas we covered in this blog post such as competitor prices, sentiments of customers, market preferences, and content optimization requirements.

    This is where DataWeave’s Digital Shelf Analytics solution becomes the biggest asset for your eCommerce business. Contact us to explore how we can empower your business to build the most visible and discoverable Amazon storefront that guarantees higher search rankings and ultimately increased sales. Talk to us for a demo today.

  • Normalizing Size and Color in Fashion Using AI to Power Competitive Price Intelligence

    Normalizing Size and Color in Fashion Using AI to Power Competitive Price Intelligence

    Fashion is as dynamic a market as any—and more competitive than most others. Consumer trends and customer needs are always evolving, making it challenging for fashion and apparel brands to keep up.

    Despite the inherent difficulties fashion and apparel sellers face, this industry is one of the largest grossing markets in the world, estimated at $1.79 trillion in 2024. Global revenue for apparel is expected to grow at an annual rate of about 3.3% over the next four years. That means companies in this space stand to make significant revenue if they can competitively price their products, keep up with the competition, and win customer loyalty with consistent product availability.

    There are three main categories in fashion and apparel. These include:

    • Apparel and clothing (i.e., shirts, pants, dresses, and other apparel)
    • Footwear (i.e., sneakers, sandals, heels, and other products)
    • Accessories (i.e., bags, belts, watches, and so on)

    If you look at all of these product types across all sorts of retailers, there is a massive amount of overlapping data based on product attributes like style and size that are difficult to normalize.

    Fashion Attributes

    Style, color, and size are the main attribute categories in fashion and apparel. Style attributes include things like design, look, and overall aesthetics of the product. They’re very dependent on the actual product category of fashion as well. A shirt might have a slim fit attribute associated with it, whereas a belt might have a length. All these different attributes are usually labeled within a product listing and affect the consumer’s decision-making process:

    • Color (red, blue, sea green, etc.)
    • Pattern (solid, striped, checked, floral, etc.)
    • Material (cotton, polyester, leather, denim, silk, etc.)
    • Fit (regular, slim, relaxed, oversized, tailored, etc.)
    • Type (casual, formal, sporty, vintage, streetwear)

    Color Complexity in Fashion

    Color is perhaps the most visually distinctive attribute in fashion, yet it presents unique challenges for retailers. This is because color naming can vary across retailers and marketplaces. There are several major differences in color convention:

    • A single color can be labeled differently across brands (e.g., “navy,” “midnight blue,” “deep blue”)
    • Seasonal color names (e.g., “summer sage” vs. “forest green”)
    • Marketing-driven names (e.g., “sunset coral” vs. “pale orange”)
    Differences in color naming - challenges faced by fashion retail intelligence systems

    Size: The Other Critical Dimension

    Size in fashion refers to the dimensions or measurements that determine how fashion products fit. Depending on whether the product is a clothing item, shoes, or a hat, there will be different sizing options. Types of sizes include:

    • Standard sizes (XS, S, M, L, XL, XXL, XXL)
    • Custom sizes (based on brand, retailer, country, etc.)

    A single type of product may have different sizing labels. For instance, one pants listing may use traditional S, M, L, XL sizing, while another pants listing may use 24, 25, or 26, to refer to the waist measurement.

    Size Variations - challenges faced by fashion retail intelligence systems
    Size Variations - challenges faced by fashion retail intelligence systems
    Size Variations - challenges faced by fashion retail intelligence systems

    Size is a dynamic attribute that changes based on current trends. For example, there has recently been a significant shift towards inclusive sizing. Size inclusivity refers to the practice of selling apparel in a wide range of sizes to accommodate people of all body types. Consumers are more aware of this trend and are demanding a broader range of sizing offerings from the brands they shop from.

    In the US market, in particular, some 67% of American women wear a size 14 or above and may be interested in purchasing plus-size clothing. There is a growing demand in the plus-size market for more options and a wider selection. Many brands are considering expanding their sizes to accommodate more shoppers and tap into this growing revenue channel.

    Pricing Based on Size and Color

    Many fashion products are priced differently based on size and color. Let’s take a look at an example of what this can look like.

    Different colors may retail at different price points.

    A popular beauty brand (see image) is known for its viral lip tint. While most of the color variants are priced at $9.90 on Amazon, a specific colorway option, featuring less pigmented options, is priced at $9.57. This price differential is driven by both material costs and market demand.

    Different colorways (any of a range of combinations of colors in which a style or design is available) of the same product often command different prices also. This is based on:

    • Dye costs (some colors require more expensive processes)
    • Seasonal demand (traditional colors vs. trend colors)
    • Exclusivity (limited edition colors)

    An example of price variations by size is a women’s shirt that is being sold on Amazon as shown below. For this product, there are no style attributes to choose from. The only parameter the shopper has to select is the size they’d like to purchase. They can choose from S to XL. On the top, we can see that the product in size S is ₹389. Below, the size XL version of this same shirt is ₹399. This price increase is correlated to the change in size.

    Different sizes may retail at different price points.
    Different sizes may retail at different price points.

    So why are these same products priced differently? In an analysis of One Six, a plus-size clothing brand, several reasons for this difference in plus-size clothing were determined.

    • Extra material is needed, hence an increase in production costs
    • Extra stitching costs, hence an increase in production costs
    • Production of plus-size clothing often means acquiring specialized machinery
    • Smaller scale production runs for plus-size clothing means these initiatives often don’t benefit from cost savings

    Some sizes are sold more than others, meaning that in-demand sizes for certain apparel can affect pricing as well. Brands want to be able to charge as much as possible for their listing without risking losing a sale to a competitor.

    The Competitive Pricing Challenge: Normalizing Product Attributes Across Competitors in Apparel and Fashion

    There are hundreds of possible attribute permutations for every single apparel product. Some retailers may only sell core sizes and basic colors; some may sell a mix of sizes for multiple style types. Most retailers also sell multiple color variants for all styles they have on catalog. Other retailers may only sell a single, in-demand size of the product. Also, when other retailers are selling the product, it’s unlikely that their naming conventions, color options, style options, and sizing match yours one-for-one.

    In one analysis, it was found that there were 800+ unique values for heel sizes and 1000+ unique values for shirts and tops at a single retailer! If you’re looking to compare prices, the effort involved in setting up and managing lookup tables to identify discrepancies when one retailer uses European sizes and another uses USA sizes, for example, is simply too onerous to contemplate doing. Colors only add to the complexity – as similar colors may have new names in different regions and locations as well!

    Even if you managed to find all the discrepancies between product attributes, you would still need to update them any time a competitor changed a convention.

    Still, monitoring your competitors and strategically pricing your listings is essential to maintain and grow market share. So what do you do? You can’t simply eyeball your competitor’s website to check their pricing and naming conventions. Instead, you need advanced algorithms to scan the entire marketplace, identify individual products being sold, and normalize their data and attributes for analysis.

    Getting Color and Size Level Pricing Intelligence

    With DataWeave, size and color are just two of several dimensions of a product instead of an impossible big data problem for teams. Our product matching engine can easily handle color and sizing complexity via our AI-driven approach combined with human verification.

    This works by using AI built on more than 10 years of product catalog data across thousands of retail websites. It matches common identifiers, like UPC, SKU code, and other attributes for harmonization before employing a large language model (LLM) prompts to normalize color variations and sizing to a single standard.

    The data flow DataWeave uses for product sizing and color normalization

    For example, if a competitor has the smallest size listed as Sm but has your smallest listing identified as S, DataWeave can match those two attributes using AI. Similar classification can be performed on color as well.

    Complex LLM prompts are pre-established so that this process is fast and efficient, taking minutes rather than weeks of manual effort.

    Harmonizing products along with their color and sizing data across different retailers for further analysis has several benefits. Most importantly, product matching helps teams conduct better competitive analysis, allowing them to stay informed about market trends, competitors’ offerings, and how those competitors are pricing various permutations of the same product. It helps ensure that you’re offering the most competitive assortment of sizing in several colors to win more market share as well. Overall, it’s easier for teams to gain insights and exploit their findings when all the data is clean and available at their fingertips.

    Product Matching Size and Color in Apparel and Fashion

    Color and size are crucial attributes for retailers and brands in the apparel and fashion industry. It adds a level of complexity that can’t be overstated. While it’s a necessity to win consumers (more colors and sizes will mean a wider potential reach), the more permutations you add to your listing, the more complicated it will be to track it against your competition. However, This challenge is worth undertaking as long as you have the right solutions at your disposal.

    With a strategy backed by advanced technology to discover identical and similar products across the competitive landscape and normalize their color and sizing attributes, you can ensure that you are competitively pricing your products and offering the best assortment possible. Employing DataWeave’s AI technology to find competitor listings, match products across variants, and track pricing regularly is the way to go.

    Interested in learning more about DataWeave? Click here to get in touch!

  • Mastering Fuel Price Competitiveness: How First-Party Data Outperforms Third-Party in Pricing Accuracy

    Mastering Fuel Price Competitiveness: How First-Party Data Outperforms Third-Party in Pricing Accuracy

    Fuel retailers today operate in a highly competitive and volatile market. Consumer behavior is increasingly driven by price sensitivity, particularly in industries like fuel where small changes in price can significantly influence where consumers choose to fill up. The stakes are even higher when you consider the razor-thin margins many fuel retailers work with, making every cent count.

    For years, retailers have relied on third-party apps and services to provide them with location-based competitive fuel price data. These services collect pricing data based on customer transactions. While these platforms offer a convenient way for consumers to find cheaper fuel prices, their value to retailers is limited. The data they provide is often riddled with inaccuracies, lags, and incomplete coverage, leaving retailers vulnerable to missed pricing opportunities.

    In this rapidly shifting landscape, retailers need data that is not only accurate but also real-time. Solving this involves directly tapping into retailers’ own data sources (first-party or 1P data) —such as websites and apps. This is believed to be the most comprehensive and reliable source of fuel price data in the market.

    To validate this hypothesis, we conducted a comprehensive analysis comparing first-party and third-party (3P) fuel price data. Our analysis compared pricing (at the same time of the day) across more than 40 gas stations—including major players like Circle K, Costco, Speedway, and Wawa. The data was captured several times a day for over a week.

    Accurate Pricing Matters More Than Ever

    Our analysis revealed that nearly a quarter (24.4%) of the fuel pricing data provided by third-party sources was inaccurate when compared to first-party data. On average, these inaccuracies amounted to a price difference of 10.9%.

    Such discrepancies, though seemingly minor, can significantly affect consumer behavior. Inaccurate prices could drive customers to competitors who are listed with lower prices—even if the real difference is negligible. For fuel retailers, this leads to lost revenue, missed opportunities, and reduced market share.

    First-party vs Third-party Fuel Price Comparison

    The implications are clear: relying on third-party competitive data alone puts retailers at risk. With inaccurate data, retailers may fail to adjust their prices in time to respond to market changes, losing customers to competitors.

    The Core Challenges of Third-Party Data

    Third-party data comes with inherent limitations. The way this data is collected presents significant challenges for fuel retailers looking to optimize pricing strategies. Here are the main issues:

    • Inconsistent Data Frequency: Third-party pricing data is often gathered through customer card transactions. As a result, pricing data updates only when and where transactions occur. This can lead to irregular data availability, particularly in stations with lower transaction volumes. For instance, in rural areas or during off-peak hours, fewer transactions lead to fewer updates. Retailers are left with outdated data, making it difficult to keep pace with real-time price fluctuations.
    • Limited Geographic Coverage: Regions with lower transaction volumes are particularly affected by data gaps. While urban centers may enjoy more frequent updates, rural and less-frequented stations often suffer from a lack of data. This limited geographic coverage creates blind spots, making it impossible for retailers in these regions to stay competitive.
    • Potential Data Inaccuracies Across Fuel Types: Our analysis showed that inaccuracies in third-party pricing data were most pronounced for Unleaded fuel, with errors occurring nearly 80% of the time. While Diesel prices fared slightly better, inaccuracies were still frequent. This inconsistency across fuel types further complicates the challenge for retailers relying on third-party data.
    First-party vs Third-party Fuel Price Comparison by Fuel Type

    Leveraging First-Party Data

    At DataWeave, our Fuel Pricing Intelligence solution leverages real-time 1P data directly from fuel retailers’ websites and mobile apps, ensuring that retailers always have access to the most up-to-the-minute and accurate pricing information.

    Here’s why first-party data stands out:

    • Real-Time Updates: Our solution provides near-instantaneous updates across more than 30,000 ZIP codes, ensuring that retailers always have the most up-to-date pricing information. This real-time accuracy is essential for making dynamic pricing adjustments in a highly competitive market.
    • Wide Geographic Coverage: DataWeave’s first-party solution captures data across a broad geographic range, ensuring no blind spots in coverage. Retailers in rural or less-frequented areas benefit from the same level of insight as their urban counterparts, giving them the ability to optimize pricing in real-time.
    • Complementary to Existing Solutions: For retailers already using third-party data, DataWeave’s first-party solution can complement and enhance their current systems. By filling in data gaps and providing more frequent updates, our solution ensures that retailers are never left in the dark when it comes to competitive pricing.

    Retailer-Wise Variances

    Among the retailers analyzed, we found that some were more affected by third-party data inaccuracies than others. Speedway and Wawa, for instance, experienced inaccuracies in up to 28% of third-party price data. In contrast, Circle K exhibited fewer discrepancies, but even they were not immune to the challenges posed by third-party data.

    For their competition, relying on third-party data alone presents a significant risk. By switching to first-party data sources, or complementing their existing third-party data with DataWeave’s first-party solution, retailers can ensure they stay competitive in the eyes of price-sensitive consumers.

    First-party vs Third-party Fuel Price Comparison by Retailer

    In an industry as price-sensitive as fuel retail, accurate data is a strategic asset. Leveraging first-party data allows fuel retailers to:

    • Maximize Revenue: By using real-time, accurate data, retailers can avoid under- or over-pricing their fuel, ensuring they capitalize on high-demand periods while minimizing losses during low-demand times.
    • Enhance Margins: First-party data provides the precision needed to fine-tune margins, ensuring profitability even in fiercely competitive markets.
    • Boost Customer Retention: Competitive pricing fosters customer loyalty. With better data, retailers can maintain customer trust and retention, even during volatile market shifts.

    Shift into High Gear with DataWeave

    As the fuel retail industry becomes increasingly competitive, the need for accurate, real-time pricing data has never been more important. DataWeave’s Fuel Pricing Intelligence solution empowers retailers with the insights they need to stay ahead of the competition, optimize pricing strategies, and boost profitability.


    With first-party data, fuel retailers can eliminate the blind spots and inaccuracies associated with third-party sources. This shift toward data-driven pricing strategies ensures that every price adjustment is backed by real-time insights, giving retailers the edge they need to succeed.

    To learn more, talk to us today!

  • Mastering Retail Media Metrics: A Deep Dive into Share of Media

    Mastering Retail Media Metrics: A Deep Dive into Share of Media

    Brands are investing millions of dollars in digital retail media to make their products stand out amid unrelenting competition.

    The ad spend on digital retail media worldwide was estimated at USD 114.4 billion in 2022, and the current projections indicate that it will grow to USD 176 billion by 2028. This amounts to a 54% increase in just six years.

    The current surge in digital retail media advertising has led brands to find an effective way to monitor the efficacy of their ad spend. While Share of Search has long been used to measure brand visibility effectively, the metrics often missed tracking ads on retail sites.

    DataWeave’s Share of Media solution helps solve this problem.

    What is the Share of Media?

    At DataWeave, Share of Media is a metric used to measure a brand’s presence in sponsored listings and banner ads on eCommerce platforms. It captures how often a brand appears in paid promotions compared to competitors, offering insights into advertising visibility and effectiveness.

    These days most marketplaces seamlessly blend banner ads and sponsored listings into organic search results. Let’s take a closer look.

    Banner Advertising

    Banner advertising strategically places creative banners across websites—often at the top, bottom, or sides. Some eCommerce platforms also integrate these banners into product search listings.

    Banner Advertising on Amazon_Share of Media Analytics to win the digital shelf

    What makes banner ads so special is the unique ability to allow marketers to use various types of media in a single ad, such as images, auto-play videos, and animations. Brands can also present curated collections of products. This flexibility provides marketers with creative opportunities to differentiate from competitors, capture customer interest, and encourage conversions.

    Sponsored Listings

    Sponsored listings are paid placements within search engine results or eCommerce platforms. They are usually marked as ‘sponsored’ or ‘ad,’ and they often appear at the top of search results and alongside organic product listing results.

    Sponsored Product Listings on Amazon_Share of Media Analytics to win the digital shelf

    Unlike organic search results, sponsored listings are prioritized based on the advertiser’s bid amount and relevance to users’ search queries.

    Sponsored listings offer a strategic advantage by enabling businesses to connect directly with consumers who are actively searching for their products. This targeted approach ensures that marketing efforts are focused on individuals with high intent of making a purchase, maximizing the potential return on investment.

    The Power of Banner Ads and Sponsored Listings

    Banner ads and sponsored listings are great choices for boosting customer engagement and product sales. Here are four key advantages they offer:

    • Enhanced Visibility: Digital retail media strategically places your brand where it will stand out—outshining competitors and grabbing the attention of high-purchase-intent consumers.
    • Precision in Reach: These ads target specific keywords or categories, allowing for highly focused advertising based on demographics and search intent.
    • Minimal Conversion Friction: Smooth transitions from ads to a brand’s native store or product listing on the marketplace keep conversion friction to a minimum.
    • Brand Awareness and Recall: Consistent exposure to your brand through banner ads and sponsored product listings can leave lasting impressions and build brand recognition.

    The bottom line is that it’s increasingly important for brands to monitor their Share of Media.

    How to Monitor Your Brand’s Share of Media

    DataWeave’s Digital Shelf Analytics (DSA) platform extends beyond the traditional Share of Search metrics and provides robust support for monitoring the Share of Media.

    DataWeave monitors the Share of Media in two ways: keywords and product categories. Users can view Share of Media insights through aggregated views, trend charts, and detailed tables. The views are designed to show brand visibility and the overall competitive landscape. For example, the screenshot below, taken from DataWeave’s dashboard, showcases the Share of Media across keywords, categories, and retailers.

    Share of Media by Keyword

    The Share of Media metric captures a brand’s advertising presence within search listings for a designated keyword. This provides a comprehensive view of a brand’s visibility and promotional efforts across retail platforms, helping brands validate and gauge the effectiveness of their ad spend.

    For example, the screenshot below shows the trend of manufacturer’s Share of Media by keyword—‘baby food.’

    Share of media by keyword_Share of Media Analytics to win the digital shelf

    Share of Media by Category

    The Share of Media metric measures the presence of brands’ banner ads and sponsored listings across product categories on retail sites. This helps brands see which product categories require more investment, making it easier for them to spend their ad budget wisely.

    The screenshot below illustrates manufacturers’ Share of Media by category across retailers.

    Share of Media: An Essential Ecommerce Metric

    As retail media continues to evolve, our analytics must follow—after all, knowledge is a competitive advantage. In the dynamic world of eCommerce, where competition is fierce and consumer attention is scarce, understanding your share of media is crucial.

    Analyzing the Share of Media can give brands a competitive edge. By regularly monitoring and analyzing this metric, you can make data-driven decisions to improve your brand’s visibility, attract more customers, and ultimately drive sales growth. With a deeper understanding of their target audience and market dynamics, brands can refine promotional efforts to drive more effective results and optimize return on ad spend (ROAS).

    For more information on how Digital Shelf Analytics can enhance your brand’s digital shelf presence, request a demo or contact us at contact@dataweave.com.

  • The Complete Guide to Competitive Pricing Strategies in Retail and E-commerce

    The Complete Guide to Competitive Pricing Strategies in Retail and E-commerce

    Your budget-conscious customers are hunting for value and won’t hesitate to switch brands or shop at other retailers.

    In saturated and fiercely competitive markets, how can you retain customers? And better yet, how can you attract more customers and grow your market share? One thing you can do as a brand or retailer is to set the right prices for your products.

    Competitive or competition-based pricing can help you get there.

    So what exactly is competitive pricing? Let’s dive into this strategy, its advantages and disadvantages, and how it can be used to stay ahead of the competition.

    What is Competitive Pricing?

    Competitive or competition-based pricing is a strategy where brands and retailers set product prices based on what their competitors charge. This method focuses entirely on the market landscape and sets aside the cost of production or consumer demand.

    It is a good pricing model for businesses operating in saturated markets, such as consumer packaged goods (CPGs) or retail.

    Competitive Pricing Models

    Competitive pricing isn’t a one-size-fits-all strategy. The approach includes various pricing models that can be customized to fit your business goals and market positioning.

    Here’s a closer look at five of the most common competition-based pricing models:

    Price Skimming

    If you have a new product entering the market, you can initially set a high price. Price skimming allows you to maximize margins when competition is minimal.

    This strategy taps into early adopters’ willingness to pay a premium for new project categories. As competitors enter the market, you can gradually reduce the price to maintain competitiveness.

    Premium Pricing

    Premium pricing lets you position your product as high-quality or luxurious goods.

    When you charge more than your competitors, you’re not just selling a product—you’re selling status and an experience. This strategy is effective when your offering is of superior quality or has unique features that justify a higher price point.

    Price Matching

    Price matching—also known as parity pricing—is a defensive pricing tactic.

    By consistently matching your competitors’ prices, you can retain customers who might otherwise, be tempted to switch to an alternative.

    This approach signals your customers that they don’t need to look elsewhere for what they need and can feel comfortable remaining loyal to your brand.

    Penetration Pricing

    Penetration pricing is when you set a low price for a new product to gain market share quickly. The opposite of price skimming, this strategy can be particularly effective in price-sensitive or highly competitive industries.

    By attracting customers early, you can also deter some competitors from entering the market. This bold move can establish your product as a market leader from the get-go.

    Loss Leader Pricing

    Loss leader pricing is a strategic sacrifice that can lead to greater gains in the long run.

    By offering a product at a low price—sometimes even below cost—you can attract new customers to your brand and strengthen your current customers’ loyalty.

    Eventually, you can cross-sell other higher-margin products to your loyal customer base to cover the loss from your loss leader pricing and increase sales of other more profitable products.

    Key Advantages of Competitive Pricing

    Although it’s not the only pricing strategy available, competitive pricing has some significant advantages.

    It is Responsive

    Agility is synonymous with profit in industries where consumer preferences and market conditions shift rapidly.

    Competitive pricing allows you to adapt quickly—if a competitor lowers their prices, you can respond promptly to maintain your positioning.

    It is Simple to Execute and Manage

    Competitive pricing is straightforward, unlike cost-based pricing, which requires complex calculations and spans various factors and facets.

    By closely monitoring competitors’ prices and adjusting your prices accordingly, you can implement this pricing strategy with relative ease and speed.

    It Can Be Combined with Other Pricing Strategies

    Competitive pricing is not a standalone strategy—it’s a versatile approach that can easily be combined with other pricing strategies. For example, say you want to use competitive pricing without losing money on a product. In this case, you could use cost-plus pricing to determine a base price that you won’t go below, then use competitive pricing as long as the price stays above your base price.

    Key Disadvantages of Competitive Pricing

    While competition-based pricing has its advantages, it’s not without its pitfalls. Here are some potential disadvantages of competitive pricing.

    It De-emphasizes Consumer Demand

    If you focus solely on what competitors are charging, you could overlook consumer demand.

    For example, you could underprice items that consumers could be willing to purchase for more. Or, you might overprice items that consumers perceive as low-value, which can reduce sales.

    You Risk Price Wars

    If you and your competition undercut each other for customer acquisition and loyalty, you will eventually erode profit margins and harm the industry’s overall profitability. It’s a slippery slope where everyone loses in the end.

    There’s Potential for Complacency

    When you base your prices on beating those of competitors, you might neglect to differentiate your offerings through innovation and product improvements. Over time, this can weaken your brand’s position and lead to a loss of market share. Staying competitive means more than just matching prices—it means continuously evolving and adding value for the consumer.

    4 Tips for a Successful Competitive Pricing Strategy in Retail

    Here are four competition-based pricing tips for retailers:

    Retailer Tip #1. Know Where to Position Your Products in the Market

    For competitive pricing to work, you must understand your optimal product positioning in the overall market. To gain this understanding, you must regularly compare your offerings and prices with those of your key competitors, especially for high-demand products.

    Then, you can decide which competition-based pricing model is suitable for you.

    Retailer Tip #2. Price Dynamically

    Dynamic pricing is a tactic with which you automatically adjust prices on your chosen variables, such as market conditions, competitor actions, or consumer demand.

    When it comes to competitive pricing, a dynamic pricing system can track your competitors’ price changes and update yours in lockstep.

    Price-monitoring tools like DataWeave allow you to stay ahead of the game with seasonal and historical pricing trend data.

    Retailer Tip #3. Combine Competitive Pricing with Other Pricing Strategies

    Competitive pricing can be powerful, but it doesn’t have to stand alone. You can enhance its benefits with complementary marketing tactics.

    To illustrate, you can bundle products to offer greater value than what your competitors are offering. You can also leverage loyalty programs to offer exclusive discounts or rewards so customers keep returning, even when your competitors offer them lower prices.

    Retailer Tip #4. Stay in Tune with Consumer Demand

    Competition-based pricing aligns you with your competitor, but don’t lose sight of what your customers want. Routinely test your pricing strategy against consumer behavior to ensure that your prices reflect the actual value of your offerings.

    5 Tips for a Successful Competitive Pricing Strategy for Consumer Brands

    If you’re thinking about how to create a competitive pricing strategy for your brand, consider these five tips:

    Brand Tip #1. Identify Competing Products for Accurate Comparisons

    The first step in competitive pricing is to know the value of what you’re selling and how it compares to that of your competitors’ products. This extends to private-label products, similar but not identical products, and use-case products.

    Product matching ensures your pricing decisions are based on accurate like-for-like comparisons, allowing you to compete effectively.

    Brand Tip #2. Understand Your Product’s Relative Value

    Knowing how your product competes on value is key to setting the right price. If your product offers higher value, price it higher; if it offers less, price it accordingly. This ensures your pricing strategy reflects your product’s market placement.

    Brand Tip #3. Consider Brand Perception

    Even if your product is virtually the same as a competitor’s, your brand’s perceived value may be different, which plays a crucial role in pricing.

    If your brand is perceived as premium, you can justify higher prices. Conversely, if customers perceive you as a value brand, your pricing should reflect affordability.

    Brand Tip #4. Leverage Value-Based Differentiation

    When your prices are similar to competitors’, you must differentiate your products by expressing your product value through branding, packaging, quality, or something else entirely.

    This differentiation will compel consumers to choose your product over other similarly priced options.

    Brand Tip #5. Stay Vigilant with Price Monitoring

    Your competitors will update their pricing repeatedly, and you will, too.

    It can be difficult and time-consuming to monitor your competitive pricing, so you’ll need a system like DataWeave to monitor competitors’ pricing and manage dynamic pricing changes.

    This vigilance ensures your brand remains competitive and relevant in real time.

    4 Essential Capabilities You Need to Implement Successful Competition-Based Pricing

    You’ll need four key capabilities to implement a competitive pricing strategy effectively.

    AI-Driven Product Matching

    Product matching means you’ll compare many products (sometimes tens or hundreds) with varying details across multiple platforms. Accurate product matching at that scale requires AI.

    For instance, AI can identify similar smartphones to yours by analyzing features like screen size and processor type. DataWeave’s AI product matches start with 80–90% matching accuracy, and then human oversight can fine-tune the data for near-perfect matches.

    You can make informed pricing decisions once you know which competing products to base your prices on.

    Accurate and Comprehensive Data

    A successful competition-based pricing strategy depends on high-quality, comprehensive product and pricing data from many retailers and eCommerce marketplaces.

    By tracking prices on large online platforms and niche eCommerce sites across certain regions, you’ll gain a more comprehensive market view, which enables you to make quick and confident price changes.

    Normalized Measurement Units

    Accurate price comparisons are dependent on normalized unit measurements.

    For example, comparing laundry detergent sold in liters to laundry detergent sold in ounces requires converting either or both products to a common base like price-per-liter or price-per-ounce.

    This normalization ensures accurate pricing analysis.

    Timely Actionable Insights

    Timely and actionable pricing insights empower you to make informed pricing decisions.

    With top-tier competitive pricing intelligence systems, you get customized alerts, intuitive dashboards, and detailed reports to help your team quickly act on insights.

    In Conclusion

    Competitive pricing or competition-based pricing is a powerful strategy for businesses navigating crowded markets, but you must balance competitive pricing with your brand’s unique value proposition.

    Competitive pricing should complement innovation and customer-centric strategies, not replace them. To learn more, talk to us today!

  • DataWeave’s AI Evolution: Delivering Greater Value Faster in the Age of AI and LLMs

    DataWeave’s AI Evolution: Delivering Greater Value Faster in the Age of AI and LLMs

    In retail, competition is fierce, and in its ever-evolving landscape, consumer expectations are higher than ever.

    For years, our AI-driven solutions have been the foundation that empowers businesses to sharpen their competitive pricing and optimize digital shelf performance. But in today’s world, evolution is constant—so is innovation. We now find ourselves at the frontier of a new era in AI. With the dawn of Generative AI and the rise of Large Language Models (LLMs), the possibilities for eCommerce companies are expanding at an unprecedented pace.

    These technologies aren’t just a step forward; they’re a leap—propelling our capabilities to new heights. The insights are deeper, the recommendations more precise, and the competitive and market intelligence we provide is sharper than ever. This synergy between our legacy of AI expertise and the advancements of today positions DataWeave to deliver even greater value, thus helping businesses thrive in a fast-paced, data-driven world.

    This article marks the beginning of a series where we will take you through these transformative AI capabilities, each designed to give retailers and brands a competitive edge.

    In this first piece, we’ll offer a snapshot of how DataWeave aggregates and analyzes billions of publicly available data points to help businesses stay agile, informed, and ahead of the curve. These fall into four broad categories:

    • Product Matching
    • Attribute Tagging
    • Content Analysis
    • Promo Banner Analysis
    • Other Specialized Use Cases

    Product Matching

    Dynamic pricing is an indispensable tool for eCommerce stores to remain competitive. A blessing—and a curse—of online shopping is that users can compare prices of similar products in a few clicks, with most shoppers gravitating toward the lowest price. Consequently, retailers can lose sales over minor discrepancies of $1–2 or even less.

    All major eCommerce platforms compare product prices—especially their top selling products—across competing players and adjust prices to match or undercut competitors. A typical product undergoes 20.4 price changes annually, or roughly once every 18 days. Amazon takes it to the extreme, changing prices approximately every 10 minutes. It helps them maintain a healthy price perception among their consumers.

    However, accurate product matching at scale is a prerequisite for the above, and that poses significant challenges. There is no standardized approach to product cataloging, so even identical products bear different product titles, descriptions, and attributes. Information is often incomplete, noisy, or ambiguous. Image data contains even more variability—the same product can be styled using different backgrounds, lighting, orientations, and quality; images can have multiple overlapping objects of interest or extraneous objects, and at times the images and the text on a single page might belong to completely different products!

    DataWeave leverages advanced technologies, including computer vision, natural language processing (NLP), and deep learning, to achieve highly accurate product matching. Our pricing intelligence solution accurately matches products across hundreds of websites and automatically tracks competitor pricing data.

    Here’s how it works:

    Text Preprocessing

    It identifies relevant text features essential for accurate comparison.

    • Metadata Parsing: Extracts product titles, descriptions, attributes (e.g., color, size), and other structured data elements from Product Description Pages (PDP) that can help in accurately identifying and classifying products.
    • Attribute-Value Normalization: Normalize attributes names (e.g. RAM vs Memory) and their values (e.g., 16 giga bytes vs 16 gigs vs 16 GB); brand names (e.g., Benetton vs UCB vs United Colors of Benetton); mapping category hierarchies a standard taxonomy.
    • Noise Removal: Removes stop words and other elements with no descriptive value; this focuses keyword extraction on meaningful terms that contribute to product identification.

    Image Preprocessing

    Image processing algorithms use feature extraction to define visual attributes. For example, when comparing images of a red T-shirt, the algorithm might extract features such as “crew neck,” “red,” or “striped.”

    Image Preprocessing using advanced AI and other tech for product matching in retail analytics.

    Image hashing techniques create a unique representation (or “hash”) of an image, allowing for efficient comparison and matching of product images. This process transforms an image into a concise string or sequence of numbers that captures its essential features even if the image has been resized, rotated, or edited.

    Before we perform these activities there is a need to preprocess images to prepare them for downstream operations. These include object detection to identify objects of interest, background removal, face/skin detection and removal, pose estimation and correction, and so forth.

    Embeddings

    We have built a hybrid or a multimodal product-matching engine that uses image features, text features, and domain heuristics. For every product we process we create and store multiple text and image embeddings in a vector database. These include a combination of basic feature vectors (e.g. tf-idf based, colour histograms, share vectors) to more advanced deep learning algorithms-based embeddings (e.g., BERT, CLIP) to the latest LLM-based embeddings.

    Classification

    Classification algorithms enhance product attribute tagging by designating match types. For example, the product might be identified as an “exact match”, “variant”, “similar”, or “substitute.” The algorithm can also identify identical product combinations or “baskets” of items typically purchased together.

    What is the Business Impact of Product Matching?

    • Pricing Intelligence: Businesses can strategically adjust pricing to remain competitive while maintaining profitability. High-accuracy price comparisons help businesses analyze their competitive price position, identify opportunities to improve pricing, and reclaim market share from competitors.
    • Similarity-Based Matching: Products are matched based on a range of similarity features, such as product type, color, price range, specific features, etc., leading to more accurate matches.
    • Counterfeit Detection: Businesses can identify counterfeit or unauthorized versions of branded products by comparing them against authentic product listings. This helps safeguard brand identity and enables brands to take legal action against counterfeiters.

    Attribute Tagging

    Attribute tagging involves assigning standardized tags for product attributes, such as brand, model, size, color, or material. These naming conventions form the basis for accurate product matching. Tagging detailed attributes, such as specifications, features, and dimensions, helps match products that meet similar criteria. For example, tags like “collar” or “pockets” for apparel ensure high-fidelity product matches for hard-to-distinguish items with minor stylistic variations.

    Attributes that are tagged when images are matched for retail ecommerce analytcis.

    Including tags for synonyms, variants, and long-tail keywords (e.g., “denim” and “jeans”) improves the matching process by recognizing different terms used for similar products. Metadata tags categorize similar items according to SKU numbers, manufacturer details, and other identifiers.

    Altogether, these capabilities provide high-quality product matches and valuable metadata for retailers to classify their products and compare their product assortment to competitors.

    User-Generated Content (UGC) Analysis

    Customer reviews and ratings are rich sources of information, enabling brands to gauge consumer sentiment and identify shortcomings regarding product quality or service delivery. However, while informative, reviews constitute unstructured “noisy” data that is actionable only if parsed correctly.

    Here’s where DataWeave’s UGC analysis capability steps in.

    • Feature Extractor: Automatically pulls specific product attributes mentioned in the review (e.g., “battery life,” “design” and “comfort”)
    • Feature Opinion Pair: Pairs each product attribute with a corresponding sentiment from the review (e.g., “battery life” is “excellent,” “design” is “modern,” and “comfort” is “poor”)
    • Calculate Sentiment: Calculates an overall sentiment score for each product attribute
    The user generated content analysis framework used by DataWeave to calculate sentiment.

    The final output combines the information extracted from each of these features, which looks something like this:

    • Battery life is excellent
    • Design is modern
    • Not satisfied with the comfort

    The algorithm also recognizes spammy reviews and distinguishes subjective reviews (i.e., those fueled by emotion) from objective ones.

    DataWeave's image processing tool also analyses promo banners.

    Promo Banner Analysis

    Our image processing tool can interpret promotional banners and extract information regarding product highlights, discounts, and special offers. This provides insights into pricing strategies and promotional tactics used by other online stores.

    For example, if a competitor offers a 20% discount on a popular product, you can match or exceed this discount to attract more customers.

    The banner reader identifies successful promotional trends and patterns from competitors, such as the timing of discounts, frequently promoted product categories or brands, and the duration of sales events. Ecommerce stores can use this information to optimize their promotion strategies, ensuring they launch compelling and timely offers.

    Other Specialized Use Cases

    While these generalized AI tools are highly useful in various industries, we’ve created other category—and attribute-specific capabilities for specialty goods (e.g., those requiring certifications or approval by federal agencies) and food items. These use cases help our customers adhere to compliance requirements.

    Certification Mark Detector

    This detector lets retailers match items based on official certification marks. These marks represent compliance with industry standards, safety regulations, and quality benchmarks.

    Example:

    • USDA Organic: Certification for organic food production and handling
    • ISO 9001: Quality Management System Certification

    By detecting these certification marks, the system can accurately match products with their certified counterparts. By identifying which competitor products are certified, retailers can identify products that may benefit from certification.

    Image analysis based product matching at DataWeave also detects certificate marks.

    Nutrition Fact Table Reader

    Product attributes alone are insufficient for comparing food items. Differences in nutrition content can influence product category (e.g., “health food” versus regular food items), price point, and consumer choice. DataWeave’s nutrition fact table reader scans nutrition information on packaging, capturing details such as calorie count, macronutrient distribution (proteins, fats, carbohydrates), vitamins, and minerals.

    The solution ensures items with similar nutritional profiles are correctly identified and grouped based on specific dietary requirements or preferences. This helps with price comparisons and enables eCommerce stores to maintain a reliable database of product information and build trust among health-conscious consumers.

    Image processing for product matching also extracts nutrition table data at DataWeave.

    Building Next-Generation Competitive and Market Intelligence

    Moving forward, breakthroughs in generative AI and LLMs have fueled substantial innovation, which has enabled us to introduce powerful new capabilities for our customers.

    How Gen AI and LLMs are used by DataWeave to glean insights for analytics

    These include:

    • Building Enhanced Products, Solutions, and Capabilities: Generative AI and LLMs can significantly elevate the performance of existing solutions by improving the accuracy, relevance, and depth of insights. By leveraging these advanced AI technologies, DataWeave can enhance its product offerings, such as pricing intelligence, product matching, and sentiment analysis. These tools will become more intuitive, allowing for real-time updates and deeper contextual understanding. Additionally, AI can help create entirely new solutions tailored to specific use cases, such as automating competitive analysis or identifying emerging market trends. This positions DataWeave to remain at the forefront of innovation, offering cutting-edge solutions that meet the evolving needs of retailers and brands.
    • Reducing Turnaround Time (TAT) to Go-to-Market Faster: Generative AI and LLMs streamline data processing and analysis workflows, enabling faster decision-making. By automating tasks like data aggregation, sentiment analysis, and report generation, AI dramatically reduces the time required to derive actionable insights. This efficiency means that businesses can respond to market changes more swiftly, adjusting pricing or promotional strategies in near real-time. Faster insights translate into reduced turnaround times for product development, testing, and launch cycles, allowing DataWeave to bring new solutions to market quickly and give clients a competitive advantage.
    • Improving Data Quality to Achieve Higher Performance Metrics: AI-driven technologies are exceptionally skilled at cleaning, organizing, and structuring large datasets. Generative AI and LLMs can refine the data input process, reducing errors and ensuring more accurate, high-quality data across all touchpoints. Improved data quality enhances the precision of insights drawn from it, leading to higher performance metrics like better product matching, more accurate price comparisons, and more effective consumer sentiment analysis. With higher-quality data, businesses can make smarter, more informed decisions, resulting in improved revenue, market share, and customer satisfaction.
    • Augmenting Human Bandwidth with AI to Enhance Productivity: Generative AI and LLMs serve as powerful tools that augment human capabilities by automating routine, time-consuming tasks such as data entry, classification, and preliminary analysis. This allows human teams to focus on more strategic, high-value activities like interpreting insights, building relationships with clients, and developing new business strategies. By offloading these repetitive tasks to AI, human productivity is significantly enhanced. Employees can achieve more in less time, increasing overall efficiency and enabling teams to scale their operations without needing a proportional increase in human resources.

    In our ongoing series, we will dive deep into each of these capabilities, exploring how DataWeave leverages cutting-edge AI technologies like Generative AI and LLMs to solve complex challenges for retailers and brands.

    In the meantime, talk to us to learn more!

  • Less is More in Holiday Pricing: The Case for a Simple, Stable Approach This Holiday Season

    Less is More in Holiday Pricing: The Case for a Simple, Stable Approach This Holiday Season

    With pricing making headlines more frequently than ever, now is the perfect moment for retailers to take a step back and rethink their holiday strategy. The heightened focus on pricing—driven by economic uncertainties, inflationary pressures, and fluctuating supply chain dynamics—presents a unique opportunity for retailers to not only meet customer expectations but to exceed them by rebuilding trust. In today’s climate, where consumer confidence is often fragile, the perception of fair pricing can be a significant differentiator. This is especially true during the holiday season when shoppers are more budget-conscious, and every dollar counts.

    Rather than focusing on the price of individual items, consumers are increasingly concerned with the total amount they spend at checkout. This means the overall basket cost, rather than the price tag on a single product, holds greater sway in determining whether a customer feels they’ve gotten a good deal. Retailers who can maintain steady, predictable basket pricing—despite external pressures such as supply chain disruptions or increased competition—will stand out as reliable and customer-centric.

    Pricing Strategy for the Holiday Season

    Your pricing strategy sets the tone for fostering and maintaining customer trust during the busy holiday season. From establishing initial prices to managing markdowns, having a stable, well-thought-out plan is crucial to balancing profitability with customer satisfaction. Below are several guiding principles to help you navigate this critical time frame:

    holiday-pricing-considerations

    Anchor Your Prices Early on Key Holiday Items

    Identify the products that are likely to drive traffic and sales during the holiday period and set your prices strategically early on. Use these prices as a ceiling that you won’t exceed, allowing customers to trust that they’re getting consistent value. By establishing this anchor price, you create a sense of stability in an otherwise fluctuating market, helping your customers feel confident that they won’t face price hikes on essential holiday items.

    Prepare for Competitive Moves

    The holiday season is notorious for aggressive pricing tactics by competitors, so you’ll need to remain agile. Be prepared to make strategic price reductions when necessary, but ensure you stay below your anchored price to avoid eroding trust. Monitoring competitors closely and adjusting your strategy without undermining your overall value proposition will be key to maintaining a competitive edge.

    To accomplish this, having reliable and timely competitor pricing data is essential. A sophisticated pricing intelligence platform like DataWeave’s can get the job done, which is equipped to handle the scale and speed demanded during the fast-paced holiday season.

    Collaborate with Vendors on Promotions

    Strong vendor relationships are crucial during the holiday season. By working closely with your suppliers, you can develop compelling promotions that not only attract customers but also ensure you have adequate inventory levels to support any reduced pricing strategies. Vendors may offer additional incentives or discounts during this period, and leveraging those to provide deeper savings can help retailers pass along better deals to customers without sacrificing margin.

    Pre-Holiday Markdowns

    Pre-holiday markdowns are an essential tool to clear out older inventory and make room for newer, more seasonal items. Get ahead of these markdowns by tracking trends and data from previous years. This will allow you to anticipate demand and address any overstocking issues early, ensuring that your shelves are stocked with the right products at the right time.

    Post-Holiday Markdowns

    Once the holiday rush subsides, differentiating between products is crucial. For “In and Out” items, which are seasonal or limited-time offers, your goal should be to clear through inventory as quickly as possible to free up valuable shelf space for upcoming product cycles. For products that are part of your regular planogram, the focus should shift to adjusting inventory levels back down to non-holiday norms, ensuring you’re not left with excess stock that could tie up cash flow in the slower months ahead.

    Manage Markdowns at the Store/Item Level

    Not all stores or products will move at the same pace, so it’s essential to manage markdowns on a granular level. Each store has different inventory turnover rates, and customer demand may vary from one location to another. Tailoring markdown strategies to the specific needs of individual stores and products allows for greater flexibility and ensures you’re maximizing sell-through while minimizing excess stock.

    Managing the Rest of the Assortment

    While holiday-specific items will undoubtedly capture much of the attention from customers due to the increased volume and seasonal demand, it’s essential to remember that the rest of the customer’s basket—comprised of non-holiday items—plays a pivotal role in their overall shopping experience. Retailers often focus heavily on optimizing prices for holiday items, but maintaining a consistent and customer-friendly pricing strategy across the entire assortment is equally important. Neglecting non-holiday items can erode trust and diminish the effectiveness of the overall holiday pricing strategy. Customers shop holistically, and their perception of your brand is shaped by the totality of their shopping experience, not just individual product categories.

    While holiday promotions may attract traffic, it’s the consistency and transparency of your broader pricing strategy that will strengthen trust and encourage repeat business. After all, the holiday season is not just about winning a single transaction—it’s about building relationships that extend well into the new year.

    A few critical factors to consider for your non-holiday assortment:

    Minimize Price Increases Unless Absolutely Necessary

    The holiday season is a delicate time when customers are highly sensitive to pricing. Sudden, unexpected price hikes, especially on everyday, non-seasonal items, can quickly erode the trust you’ve worked hard to build. Customers may forgive small fluctuations, but if they perceive a retailer is taking advantage of holiday demand or inflationary pressures to unnecessarily raise prices, that goodwill can evaporate. By maintaining steady pricing, you reinforce the idea that your brand prioritizes fairness over opportunism, especially in a period marked by heightened scrutiny around pricing practices.

    Evaluate Price Gaps Between Product Tiers

    A key element of pricing strategy that retailers should focus on is maintaining appropriate price gaps between product tiers, such as private label and national brands. Ensuring that the price difference between these tiers remains clear and consistent helps reinforce a value proposition for both types of customers: those who seek premium national brands and those who are value-oriented and gravitate toward private label options. If the price gap becomes too narrow, customers may be confused about the differentiation between products, leading to dissatisfaction or lost sales.

    Ensure Accurate Value Sizing

    One of the most effective ways to gain customer trust is through clear, transparent pricing, particularly when it comes to value sizing. Misleading unit pricing, whether intentional or accidental, can quickly frustrate customers, making them feel that they are being deceived. Ensure that unit pricing is visible, logical, and consistent across all product categories, allowing customers to make informed choices without feeling overwhelmed or misled. By offering transparency in this area, you can foster a sense of fairness and accountability, further building your reputation as a customer-first retailer.

    Maintain Price Links Across Your Assortments

    Consistency in pricing across various categories and product lines is crucial to managing customer expectations. Pricing disparities between similar products or across different stores in your chain can create confusion and frustration, leading to negative perceptions of your brand. Customers expect a seamless shopping experience, and this includes consistency in pricing, no matter what they buy or where they buy it. Establishing and maintaining price links within your assortment will ensure that your broader pricing strategy remains aligned with customer expectations, reinforcing reliability.

    Trust is Your Greatest Currency

    In a retail environment where customers are constantly bombarded with news about inflation, price hikes, and economic instability, trust is your greatest asset. Negative perceptions surrounding pricing, whether it’s from the media or personal experiences, can make customers wary and hesitant. By committing to a stable, transparent, and fair pricing strategy—not just for holiday items but across the entire assortment—you can differentiate yourself in the market and foster long-term loyalty. Stability and consistency in your pricing model allow customers to feel confident that they’re getting good value every time they shop with you, regardless of external economic pressures.

    It’s important to prioritize the customer relationship above all else, even if that means sacrificing some immediate short-term gains. Retailers who opt for quick wins through aggressive price changes may see a temporary boost in profits but risk damaging long-term customer loyalty. On the other hand, by focusing on providing a consistent and fair experience, you position your brand as a reliable choice, one that customers will return to not just during the holidays but throughout the entire year.

    In a season where every retailer is vying for the same holiday dollar, your approach to pricing must stand out by emphasizing trust, loyalty, and customer satisfaction. Pricing transparency and fairness are key differentiators, especially in an environment where many retailers will be tempted to capitalize on increased demand by raising prices or reducing promotions. Instead, leading with trust and focusing on stability will allow you to rise above the noise and deliver a superior customer experience.

    In Summary: Stability Wins

    This holiday season, the winning strategy isn’t about pushing for the highest possible margins or taking advantage of seasonal demand spikes. It’s about the bigger picture—building lasting customer relationships that extend well beyond the holidays. By prioritizing consistency in your pricing, maintaining transparency across your assortment, and leading with trust, you’ll not only achieve success during the holiday period but also set the stage for long-term customer loyalty.

    In short, stability wins. Prioritize the customer experience, remain consistent in your approach, and lead with trust. Doing so will ensure that your customers not only choose you during the holidays but continue to choose you long into the future.

    To learn more, reach out and chat with us today!

  • Back-to-School 2024 Pricing Strategies: What Retailers and Brands Need to Know

    Back-to-School 2024 Pricing Strategies: What Retailers and Brands Need to Know

    As summer winds down, families across the US have been gearing up for the annual back-to-school shopping season. The back-to-school season has always been a significant event in the retail calendar, but its importance has grown in recent years. With inflation still impacting many households, parents and guardians are more discerning than ever about their purchases, seeking the best value for their money.

    The National Retail Federation has forecasted that this season could see one of the highest levels of spending in recent years, reaching up to $86.6 billion. As shoppers eagerly stock up on back-to-school and back-to-college essentials, it’s crucial for retailers and brands to refine their pricing strategies in order to capture a larger share of the market.

    To understand how retailers are responding to the back-to-school rush this season, our proprietary analysis delves into pricing trends, discount strategies, and brand visibility across major US retailers, including Amazon, Walmart, Kroger, and Target. By examining 1000 exactly matching products in popular back-to-school categories, our analysis provides valuable insights into the pricing strategies adopted by leading retailers and brands this year.

    Price Changes: A Tale of Moderation

    The most notable trend in our analysis is the much smaller annual price increases this year, in contrast to last year’s sharp price hikes. This shift is a reaction to growing consumer frustration about rising prices. After enduring persistent inflation and steep price growth, which peaked last year, consumers have become increasingly frustrated. As a result, retailers have had to scale back and implement more moderate price increases this year.

    Average Price Increases Across Retailers: Back-to-School 2022-24

    Kroger led the pack with the highest price increases, showing a 5.3% increase this year, which follows a staggering 19.9% rise last year. Walmart’s dramatic price increase of 14.9% is now followed by a muted 3.1% hike. Amazon and Target demonstrated a similar pattern of slowing price hikes, with increases of 2.3% and 2.7% respectively in the latest period. This trend indicates that retailers are still adjusting to increased costs but are also mindful of maintaining customer loyalty in a competitive market.

    Average Price Increases Across Categories 2022-24: Back-to-School USA

    When examining specific product categories, we observe diverse pricing trends. Electronics and apparel saw the largest price increases between 2022 and 2023, likely due to supply chain disruptions and volatile demand. However, the pace of these increases slowed in 2024, indicating a gradual return to more stable market conditions. Notably, backpacks remain an outlier, with prices continuing to rise sharply by 22%.

    Interestingly, some categories, such as office organization and planners, experienced a price decline in 2024. This could signal an oversupply or shifting consumer preferences, presenting potential opportunities for both retailers and shoppers.

    Brand Visibility: The Search for Prominence

    In the digital age, a brand’s visibility in online searches can significantly impact its success during the back-to-school season. Our analysis of the share of search across major retailers provides valuable insights into brand prominence and marketing effectiveness.

    Share of Search of Leading Brands Across Retailers During Back-to-School USA 2024

    Sharpie and Crayola emerged as the strongest performers overall, with particularly high visibility on Target. This suggests strong consumer recognition and demand for these traditional school supply brands. BIC showed strength on Amazon and Target but lagged on Kroger, while Pilot maintained a more balanced presence across most retailers.

    The variation in brand visibility across retailers also hints at potential partnerships or targeted marketing strategies. For instance, Sharpie’s notably high visibility on Target (5.16% share of search) could indicate a specific partnership.

    Talk to us to get more insights on the most prominent brands broken down by specific product categories.

    Navigating the 2024 Back-to-School Landscape

    As we look ahead to the 2024 back-to-school shopping season, several key takeaways emerge for retailers and brands:

    1. Price sensitivity remains high, but the rate of increase is moderating. Retailers should carefully balance the need to cover costs with maintaining competitive pricing.
    2. Strategic discounting can be a powerful tool, especially for lesser-known brands looking to gain market share. However, established brands would need to rely more on quality, visibility, and brand loyalty.
    3. Online visibility is crucial. Brands should invest in strong SEO and retail media strategies, tailored to different retail platforms.
    4. Category-specific strategies are essential. What works for backpacks may not work for writing instruments, so a nuanced approach is key.
    5. Retailers and brands should be prepared for potential shifts in consumer behavior, such as increased demand for value-priced items or changes in category preferences.

    By staying attuned to these trends and remaining flexible in their strategies, businesses can position themselves for success in the competitive back-to-school retail landscape of 2024. As always, the key lies in understanding and responding to consumer needs while maintaining a keen eye on market dynamics.

    Stay tuned to our blog to know more about how retailers can stay aware of changing pricing trends. Reach out to us today to learn more.

  • The Essential Price Management Framework for Retailers

    The Essential Price Management Framework for Retailers

    As a leader with over 20 years of experience leading pricing strategy at a major US grocery chain, I deeply understand the complexities pricing teams face when trying to derive, quantify, and execute corporate pricing initiatives.

    Providing insights into the competitive marketplace in order to ensure the overall success of directed pricing strategies is more than simple reporting.

    That’s what many teams get wrong.

    Reporting is a post-mortem, which is a valuable exercise, but not one that will help you achieve your pricing goals all by itself. After all, your pricing goals can change due to a number of reasons: macroeconomic challenges, regional competition, corporate objectives, along with several other factors.

    Pricing teams need a well-defined process to devise and implement their pricing strategies. This process needs to holistically examine your product base to provide robust price management. It also needs to be backed up by technology powered by the latest advancements because you can be sure your competition is already thinking that way.

    Let’s break down an effective and modern price management process for retailers.

    Data Collection

    The first aspect of any effective price management framework for retailers is a clearly defined product data collection. You need to understand your collection in terms of who to collect pricing data from, what data to collect, where to collect it from, and how often.

    • The who: Consists of both primary competition and others you’d like to keep tabs on
    • The what: Can range from targeted single items like Key Value Items (KVIs) or total portfolio
    • Where: Can range from targeted locations within your market or the total competitive network
    • How often: To be able to support your price management process and for reporting purposes, determining a cadence is essential.

    Data is power and the more data you can acquire, the more insights you’ll gain. Make sure that your collection data is well thought out ahead of time. Leaning on a price management framework built for retailers that can aggregate all your data into representative prices can help.

    For example, if you have multiple competitive stores in a single market, flattening pricing data into a defined representative price will help speed up your analysis. Don’t get confined to a single store when a comprehensive assortment view across your target markets will provide a more accurate understanding.

    Data Refinement

    Competitive Matched Items

    Next, you need to examine your competitive-matched items. These are the products that you want to be priced in direct response to your competitors’ pricing. The goal is to remain closely aligned with their prices so as not to lose market share while simultaneously achieving your corporate strategies.

    Your price management system needs to help you manage your overlapping items. Trying to do so manually will be inefficient and is almost impossible to execute across 100% of your product catalog. 

    The mapping needs to go beyond exact UPC / PLU matches to encompass other match criteria. It needs to be able to incorporate any number of derivatives, including competitor-specific item codes like Amazon’s ASINs or Target’s DPCIs. This will help you overcome the challenge of mapping exact items to a competitor when the competitor’s site doesn’t showcase a UPC. It will also help you map your own private-label items to your competitor’s private-label counterparts.

    A good price management framework will also help you match the same items but with dissimilar sizes (e.g., Cheerios 18 OZ vs. Cheerios 20 OZ), either by letting you match directly within acceptable tolerances or by enabling you to compare prices on a per-unit basis. 

    We need to leverage GenAI to help facilitate matches beyond UPC / PLU exact matches, such as Exact Item with no Competitor Code, Exact Item with Competitive Specific Codes, Similarity Matching on Private Label, Similarity Matching on Size all need to leverage it.

    If you’re playing in a vertical that doesn’t always have a unifying code (restaurants, apparel, etc.) you’ll need to leverage the latest GenAI tools to map items together for price management. The variables are simply too numerous and complex to do manually.

    Unmatched Items and Internal Portfolio

    Not every product will be included in your competitive-matched items collection. Competitive matches in your internal portfolio offer a proxy for building clear and concise price management strategies that are in line with your corporate initiatives.

    However, your unmatched items still need to be factored into your price strategy. If you only manage your competitively priced items, you won’t have a holistic viewpoint of your total product catalog and pricing. It’s critical to ensure that internal portfolio items are effectively mapped and grouped in order to extend overall price management.

    Here are three things you need to consider when managing the pricing of your internal product portfolio. A smart price management framework is your best bet for achieving these results:

    • Value Size Groupings
      Value size groupings allow for the same branded items of different sizes to be priced accordingly to ensure price parity. You don’t want to sell a private label gallon of milk for $4.00 while the half gallon is at $1.75, for example. You need certain mechanisms in place to alert you when price parity is off. This is especially true when some of your items are competitively matched, and others are not.
    • Relationships between Brands
      Relationships between brands are also critical to ensure price parity. There should be well-defined relationships between like-sized products that are from different brands. This will ensure that your private label program is priced ‘at a value’ compared with their national branded counterparts. You need to maintain the balance between different private label tiers along with different national brand tiers.
    • Price Links
      Price Links are also critical to keeping up to date from a consumer perspective. Your customers expect that certain items should be priced together and will be put off if they are not. For example, if you sell an item in different sizes or flavors and scents, their prices should be logically linked.

    For your internal portfolio, there may be items that don’t have a competitive match or simply don’t fall into one of your internal portfolio groupings. These are unique items to your banner and should be considered margin drivers for your brand.

    Leveraging Data for Action

    Now that you have a complete line of sight into both competitively matched items and internal mappings, you can move to fully leveraging your data. Figuring out how to utilize these competitive insights to understand where your price positioning is compared with your competition can be a challenge without a playbook. An effective price management framework will help guide you to the best insights and help you understand how it relates to your corporate strategy.

    If you don’t have a well-defined corporate pricing strategy (competitive or margin) or you need to update it to be more modern, the data sets provided by a price management framework can help you ascertain where you are in your pricing journey. They can also help you identify options for where you want to go.

    Here are some other ways a price management framework can help you improve your pricing strategy:

    • Utilize Competitive Data
      Get competitive insights, identify competitive price zones, and understand your competitors’ pricing philosophy. Figure out if they’re using strategies like:
      • High-Low
      • Everyday Low Price (EDLP)
      • Cost Plus
    • Unravel Competitor Strategy
      See if you can unlock what your competition has planned for pricing strategy and promotions. Try relating what you see in corporate filings and tie back to what you see in your competitive data sets.
    • Assortment Analysis
      Try looking at the data not only from a pricing perspective but also from a competitive assortment, promotion, and supply chain perspective.
    • Proactive Alerts
      Establish alerts for your internal portfolio to ensure that you don’t exceed your tolerance based on price moves.

    Leveraging a Price Management Framework Designed for Retailers

    A price management system designed specifically for you as a retailer is a game changer. An effective one can be configured specifically for the price owners, whether you have a dedicated team for this function or the price is owned by the category management team.

    For category managers, standard reporting offers a clear view of pricing performance and trends. Beyond that, competitive intelligence becomes crucial—using data from various sources like collected pricing data, market filings, social media insights, etc. to provide the senior leadership team with a deeper understanding of competitor strategies and actions. This empowers informed decision-making at the highest levels.

    With these price management insights, retailers can gain a holistic view of the competitive marketplace, uncover gaps and opportunities, and scale their business more effectively. As someone with experience on the retailer’s side of the market, I know first-hand how valuable these insights can be.

    We’d love to talk with you if you’re interested in learning more about DataWeave’s AI-powered price intelligence solution for retailers. Click here to schedule an introductory conversation.

  • Do Amazon’s Competitors Lower Prices During Prime Day?

    Do Amazon’s Competitors Lower Prices During Prime Day?

    As the retail landscape continues to evolve, events like Amazon Prime Day have become more than just shopping extravaganzas—they’ve transformed into strategic battlegrounds where retailers assert their market positions and brand identities. Prime Day 2024 was no exception, serving as a crucial moment for retailers to showcase their pricing prowess, customer loyalty programs, and category expertise.

    In an era where consumer expectations for deals are at an all-time high, the impact of Prime Day extends far beyond Amazon’s ecosystem. Retailers like Walmart, known for its “everyday low prices,” Target with its emphasis on style and value, and Best Buy, the electronics specialist, have all adapted their strategies to compete. These companies didn’t just react to Prime Day; they proactively launched their own pre-emptive sales events, with Target Circle Week, Walmart July Deals and more, effectively extending the shopping bonanza and challenging Amazon’s dominance.

    For Prime Day, we analyzed over 47,000 SKUs across major retailers and product categories to publish insights on Amazon’s pricing strategies as well as the performance of leading consumer brands. Here, we go further to delve into the discounts offered (or not offered) by Amazon’s competitors during Prime Day. Our analysis reveals that some retailers chose to compete on price during the sale for certain categories, while others did not.

    Below, we highlight our findings for each product category. The Absolute Discount is the total discount offered by each retailer during Prime Day compared to the MSRP. These are the discounts consumers are familiar with, displayed on retail websites prominently during sale events. The Additional Discount, on the other hand, is the reduction in price during Prime Day compared to the week prior to the sale, revealing the level of price markdowns by the retailer specific to a sale event.

    Consumer Electronics

    In the Consumer Electronics category, Best Buy stood out as a strong competitor, offering an Additional Discount of 5.9%—the highest among all competitors analyzed. This is unsurprising, as Best Buy is well-known for its focus on consumer electronics and is likely aiming to reinforce its reputation for offering attractive deals in order to maintain its strong consumer perception in the category.

    Discounts offered on the Consumer Electronics category across retailers during Amazon Prime Day USA 2024

    Walmart was a close second with a 4.3% Additional Discount while Target reduced its prices by only 2% during the sale.

    Apparel

    In the Apparel category, Walmart’s Additional Discount was 3.1%, demonstrating its willingness to be priced competitively on a small portion of its assortment during the sale, without compromising much on margins.

    Discounts offered on the Apparel category across retailers during Amazon Prime Day USA 2024

    Target, on the other hand, opted out of competing with Amazon on price during the sale, choosing instead to maintain its Absolute Discount level of around 11%.

    Home & Furniture

    The Home & Furniture category showcased diverse strategies from retailers. Specialty furniture retailers such as Overstock and Home Depot provided Additional Discounts of 3.9% and 2.5%, respectively, compared to Amazon’s 6.9%. This indicates a clear intent to maintain market share and remain top-of-mind for consumers despite Amazon’s competitive pricing.

    Discounts offered on the Home & Furniture Category Across Retailers during Amazon Prime Day USA 2024

    Although Target didn’t significantly lower its prices during the sale, its Absolute Discount remains substantial at 18.9%. This suggests that Target’s markdowns were already steep before the event, which could explain the lack of further reductions during the sale.

    Health & Beauty

    The Health & Beauty category saw minimal participation from Amazon’s competitors, with the exception of Sephora, which reduced prices by 3.7% during Prime Day.

    Discounts offered on the Health & Beauty Category Across Retailers during Amazon Prime Day USA 2024

    Ulta Beauty chose not to adjust its prices, likely reflecting its strategy to uphold a premium brand image. Walmart, on the other hand, offered a modest Additional Discount of 2% on select items. Given Walmart’s generally affordable product range, its total discount remained relatively low, around 3.5%.

    In Conclusion

    During Prime Day, Walmart was the only major retailer that made an effort to compete, albeit modestly. Target, on the other hand, largely chose not to offer any additional markdowns. However, several category-specific retailers, such as Best Buy in Consumer Electronics, Overstock and Home Depot in Furniture, and Sephora in Health & Beauty, aimed to retain market share by providing notable discounts.

    What this means for consumers is that even on Amazon’s Prime Day, it’s not a bad idea to compshop to identify the best deal.

    For retailers, the key takeaway is the importance of quickly analyzing competitor pricing and making agile, data-driven decisions to improve both revenues and margins. By utilizing advanced pricing intelligence solutions like DataWeave, retailers can optimize their discount strategies, better navigate pricing complexities, and drive revenue growth — all while staying prepared for major shopping events and beyond.

    Reach out to us today to learn more!

  • A Guide to Digital Shelf Metrics for Consumer Brands

    A Guide to Digital Shelf Metrics for Consumer Brands

    Our world is increasingly going online. We work online, socialize online, and shop online every day. As a consumer brand, you need to ensure complete awareness of your brand’s online presence across eCommerce platforms, search engines, and media.

    Only by deeply understanding the customer journey can you ensure that your product is reaching your ideal customers and maximizing your brand’s market share. You need data to intrinsically understand your customer journey and make changes where you’re lacking.

    As the old adage goes: ‘You can’t manage what you don’t measure.’

    You need digital shelf metrics to measure and start benchmarking your buyer’s journey. To find several of these types of key performance indicators (KPIs), you need a digital shelf analytics solution. These platforms allow you to track various metrics along the path to purchase from the awareness stage to the post-purchase phase across the entire internet, helping to inform online and offline sales strategies.

    Digital shelf analytics will help you gain insights into how your brand is doing versus the competition, which areas are lagging behind in historical performance, and what activities are driving sales. There are innumerable ways in which you can leverage these valuable insights. But how do you know which KPIs to start tracking with your digital shelf analytics solution?

    Here, we’ve summarized the top metric types your peers report, track and base their decisions on.

    With these KPIs in hand, consumer brands like yours can ensure that their products are consistently visible and appealing to their target audience across online marketplaces, ultimately enhancing conversion rates, market share, and profitability.

    Read this guide to learn more about the top digital shelf metrics consumer brands are tracking and how to use them in your own strategy.

    1. Share of Search

    Share of Search (SoS) is a KPI in digital shelf analytics that measures how frequently a consumer brand’s products appear in search results on eCommerce platforms relative to the competition for specific keywords. A good digital shelf analytics solution will be able to show this metric across all the top marketplaces and retailers, such as Amazon and Walmart, but also more niche marketplaces for industry-specific selling.

    This metric provides brands with a quantifiable way to measure how frequently their products are being “served up” to customers on online marketplaces. Essentially, it measures visibility and discoverability.

    Share of Search exmple_Digital Shelf Metrics

    With Share of Search on DataWeave, you can slice and dice your data in innumerable ways. These are a few important views you can see:

    • Aggregated SoS
    • Organic and Sponsored SoS scores
    • SoS scores across brands, retailers, keywords, cities
    • Historical SoS score trends

    Once you have benchmarked your SoS and category presence relative to your competition, you need to start interpreting the data. Here are some questions you can ask yourself to help interpret your findings:

    Share of Search exmple_Digital Shelf Metrics
    • Which of my key categories have the lowest SoS score?
    • Which products feature low on search results because they are out of stock?
    • Are my competitors’ products faring better due to sponsored searches?
    • Is my SoS low due to poor content quality?

    With insights in hand, you will know which actions to take to drive the biggest impact. For example, you could increase sponsored search results or improve organic reach by optimizing product pages.

    Understanding your SoS is essential to maximizing the awareness phase of your customer journey. It will help you improve your brand visibility and increase product conversions through better search and category presence.

    2. Share of Media

    Share of Media (SoM) is a KPI that is just as impactful, if not more so, than the SoS metric. However, only a limited number of brands track it or use it to drive strategic action. This makes it a perfect opportunity for brands looking to get an edge on the competition.

    But what is SoM in digital shelf analytics? Essentially, it’s a way of measuring retail media advertising activities like brand-sponsored banners, listings, videos, ads, and promotions that sometimes blend into search results. The main types of retail media advertising exist in two categories: banner advertising and sponsored listings.

    Banner advertising involves strategically placing designed banners within websites and search listings. These banners raise brand awareness and drive traffic to online storefronts.

    Sponsored listings are paid placements within search results on search engines or eCommerce platforms. They are prioritized based on the total bid amount and the product’s relevance. These paid listings are marked with “sponsored” or “ad.”

    Sponsored listings on an Amazon webpage

    It’s important to run these types of advertising campaigns on eCommerce platforms to gain customer visibility. In fact, “some 57% of US consumers started their online shopping searches on Amazon as of Q2 2023.” If you aren’t showing up, paying for placement can help.

    These listings serve to enhance your brand’s overall visibility, help you gain more precise reach, increase conversions, and drive better brand awareness and recall with your customers.

    These efforts aren’t free, however, so measuring their effectiveness is critical not only to gain all the listed benefits but to also not waste your valuable marketing budget. The SoM KPI can help a consumer brand answer questions like:

    • Where are the opportunities to increase paid ads?
    • Which categories could benefit from a promotional boost or a strategic and streamlined allocation of ad spend?
    • Which of my competitors have active banners and what is their share of media by keyword?
    • How has my ad spend trended historically in comparison to my competitor?
    Analytics Dashboard on Dataweave

    DataWeave’s digital shelf analytics (DSA) is among the first providers to offer Share of Media KPI tracking and analysis. This is because it requires advanced, multi-modal AI to gather, view, and aggregate listings that encompass text, images, and video. With Share of Media tracking facilitated by DataWeave, consumer brands can track and analyze the effectiveness of their own promotional investments as well as those of their competitors.

    3. Content Quality

    The content quality metric measures how well your product content adheres to the retailer’s specific guidelines, which are in place to steer traffic and sales on their sites.

    With the help of a DSA platform’s AI and ML capabilities, you can measure different elements of your product detail pages (PDPs), such as titles, descriptions, images, videos, and even customer reviews. You need to know which elements are missing, where they are missing, and which ones are negatively affecting sales so you can take corrective action.

    Did you know that the average cart abandonment rate is 69.99%? The quality of your content can significantly impact this number. Ensuring that your content is high-quality will help influence product discoverability, customer engagement, and conversion rates. It will also help position you ahead of the competition. If your content quality is poor, you may find yourself with lower search rankings, a higher return rate, and more abandoned carts.

    Here are some questions you can answer with the help of the content quality digital shelf metric:

    • Is my product content at a retail site exactly what was syndicated?
    • Are there any retailer initiated changes to my product content?
    • Are my product content updates reflected on the retailer platforms?
    • How well does my product content comply with the retailer guidelines?
    • How do I optimize my product content for enhanced discoverability and conversion?

    DataWeave’s content quality digital shelf analysis helps consumer brands ensure that product content on eCommerce platforms is high-quality and benchmark their product listings against the competition. It does this through a combination of AI-driven quality analysis and by presenting brands with actionable recommendations. These optimized suggestions are based on the top-performing products so you can focus your valuable time on the areas that will drive the biggest impact.

    4. Pricing & Promotions

    Your customers can easily shop around to find the best price for the product you’re selling. If your competitor is selling it cheaper, you’ll lose that sale.

    That’s why it’s essential to understand the pricing and promotional landscape for each of your products and categories. This can be a challenge, especially if it’s a common product or comes in multiple pack sizes or variants.

    It’s equally important to track pricing and promotions even at individual, physical stores. Doing so will allow you to remain competitive and responsive to local market dynamics by tailoring your pricing strategies based on regional competition. You don’t want your products to be overpriced (lost sales) or underpriced (lost profit) in specific markets.

    Harmonizing insights when operating an omnichannel consumer brand is extremely difficult without the aid of a digital shelf analytics solution. Insights need to be aggregated between desktop sites, mobile sites, and mobile applications, as well as from physical storefronts.

    Questions you can answer with the help of the pricing & promotions digital shelf metric include:

    • How do my product prices and promotions compare to my competitors?
    • How consistent is my product pricing across retail websites?
    • How does my product pricing vary across regions, ZIPs, and stores?
    • How do price changes influence my sales numbers?
    • Are there regional differences in pricing and promotion effectiveness?

    DataWeave’s digital shelf analytics platform stands out with its sophisticated location-aware capabilities, which enable the aggregation and analysis of localized pricing and promotions. The platform defines locations based on a range of identifiers, such as latitudes and longitudes, regions, states, ZIP codes, or specific store numbers.

    The platform can also extract promotional information, such as credit card-based or volume-based promotions. You can see variances across retailers, split by price groups, brands, and competitors. DataWeave specializes in enabling brands to conduct in-depth analyses across a wide array of attributes so you can answer just about any pricing or promotional question you have.

    Digital shelf pricing insights via Dataweave

    5. Availability

    The availability KPI in digital shelf analytics measures the in-stock and availability rates for a brand’s products across eCommerce and physical locations. Similar to the pricing and promotions metric, it relies heavily on location awareness, down to individual stores. Measuring both online availability and offline in-stock rates will help you understand the big picture and take more informed replenishment action.

    When you start leveraging the availability KPI with the help of digital shelf analytics, you can improve inventory management, boost product discoverability, increase the frequency with which your online product listings convert, and generally drive more sales. This KPI is essential for ensuring your customers can always find and buy the products they want.

    With the availability KPI, you can start answering questions like:

    • What is my overall in-stock rate?
    • Which of my products frequently go out of stock?
    • How does product availability vary across different regions and stores?
    • What is the impact of availability on my conversion rates?
    • Are there any seasonal trends in product availability that I need to address?
    • How quickly are we resolving stockout issues across different locations?
    • What are my biggest opportunities to reduce stockouts?

    DataWeave enables consumer brands to track their product availability metric through automated data collection from various eCommerce platforms in conjunction with physical in-stock rates. The platform provides granular, store-level insights so you can understand regional stock variations and optimize inventory distribution. By tracking historical availability data, you can identify seasonal patterns and predict future demand to pre-empt stockout issues. All of this can be configured with automatic notifications to alert you when there has been a stockout event or when a low stock threshold has been passed, facilitating timely replenishment.

    Graph showing availability across locations

    6. Ratings & Reviews

    The final KPI in our guide is the ratings & reviews digital shelf metric. Consumers rely heavily on genuine feedback from their peers and refer to star ratings, posted comments, and uploaded pictures to inform their buying decisions. This KPI analyzes the impact of customer feedback and reviews on your products’ performance across eCommerce platforms so you can measure overall brand perception and isolate areas of opportunity.

    This metric does something other digital shelf metrics don’t; it can inform your product strategy. It can help you identify repeat complaints that your product team can address with the manufacturer or use for the design of future products.

    Some questions you can answer with this powerful KPI include:

    • What is the overall customer sentiment towards my products based on ratings and reviews?
    • Which product features are frequently mentioned positively or negatively by customers?
    • How do my product ratings and reviews compare to those of my competitors?
    • Are there common issues or complaints that need to be addressed to improve customer satisfaction?
    • Which products have the highest and lowest ratings, and why?

    With DataWeave’s digital ratings and reviews feature, you can keep a pulse on customer sentiment to take short-term action as well as decide long-term strategy. You can leverage reviews to influence product perception, refine products, and enhance overall customer satisfaction.

    DataWeave’s Digital Shelf Metrics

    Each one of these metrics is interconnected and collectively influences a brand’s success. For instance, improving content quality and earning higher ratings can significantly enhance your product’s visibility in search results, thereby boosting the Share of Search digital shelf metric. By focusing on a comprehensive approach that integrates these metrics, brands can ensure their products are consistently visible, competitively priced, well-reviewed, and readily available.

    DataWeave gives consumer brands the means to execute a holistic digital shelf strategy. From a single portal, track and improve digital shelf metrics like Share of Search, Share of Media, Pricing and promotions, Availability, and Ratings and Reviews.

    Our solutions help audit and optimize the most critical KPIs that drive sales and market share for brands so you can stay competitive in a dynamic digital landscape and foster long-term customer satisfaction.

    Ready to get started? Schedule a call with a specialist to see how it can work for your brand.

  • How Digital Shelf Analytics Can Fix Common Revenue Growth Management Challenges for Consumer Brands

    How Digital Shelf Analytics Can Fix Common Revenue Growth Management Challenges for Consumer Brands

    As consumer goods brands increasingly turn to eCommerce marketplaces as a source of profitable growth, it becomes harder for teams to grapple with the complexity of revenue growth management.

    This complexity emerges from multiple fonts: there are hundreds, and even thousands, of competitors to consider when formulating strategies for managing pricing, promotion, and assortment changes. The world is currently experiencing a period of unprecedented supply chain instability, shifting more consumers away from traditional retail and into eCommerce shopping. And finally, consumer buying patterns, preferences, and trends are constantly shifting.

    Revenue growth management (RGM) and net revenue management (NRM) were once less complex processes; but that is no longer the case. Now, some 80% of consumer brand CEOs report that they “aren’t satisfied with their RGM results.”

    Gathering data, analyzing it, and acting on it quickly stand out as major challenges that businesses must overcome to grow their market share, earn more profits, and capitalize on market shifts in real time. In this article, we’ll dive into RGM and NRM, the obstacles business teams face, and explore how using technology for digital shelf analytics can help bridge the gap.

    What is Net Revenue Management (NRM) or Revenue Growth Management (RGM)?

    Every consumer goods company aims to increase profits and grow market share. This requires a concerted effort in RGM and net revenue management (NRM) strategy. Whether a company has a specific team dedicated to this task or relies on the abilities of business analysts or merchandisers, this function is crucial.

    It’s worth mentioning that though the terms NRM and RGM are often used interchangeably, there are subtle differences. While both net revenue management and revenue growth management focus on maximizing overall revenue for the brand, NRM typically has a narrower focus and is specific to optimizing profitability through product pricing, promotion, product mix, and cost management. RGM strategies are a bit broader and tend to look at the top line to grow market share and expand the customer base.

    The Challenges Revenue Teams Face

    Differentiating between ‘good growth’ and ‘bad growth’ is central to NRM and RGM. Net revenue management and revenue growth management teams need the data and tools in place to determine if growth in one area is coming at the expense of another so as not to cannibalize business. Tracking and analyzing extensive data to successfully take action on opportunities and determine whether strategies are working as intended consumes a tremendous amount of mental bandwidth. The fact that these decisions are incredibly time-sensitive only compounds the issue.

    To cope, many teams in charge of NRM or RGM employ digital shelf analytics strategies to help speed up data aggregation and analysis to make sure they’re capitalizing on potential opportunities.

    eCommerce has added a whole new layer of complexity to consumer goods sales. Instead of a few relatively stable prices at big-box stores, a single item for sale may experience high price volatility, with dozens of minute pricing changes occurring online each day. In some cases, consumers become blind to price volatility, letting brands increase prices, but consumer sentiment, the overall price elasticity of the product, and dozens of other factors go into determining the final price of an online product. Net revenue teams need to modernize and adapt to changing eCommerce environments to competitively price, promote, and grow their revenue.

    Here are the top three challenges standing in the way of net revenue management and revenue growth management teams and solutions to address these issues.

    Challenge 1: Incomplete or Inaccurate Data

    Incomplete and inaccurate data are critical for Net Revenue Management and Revenue Growth Management teams to get under control when attempting to modernize in a digital-centric selling environment. As more competitors enter the market, many brands find it hard to make strategic decisions without the complete picture.

    Data may be incomplete or inaccurate because a brand is analyzing only part of the market, such as Amazon or another enterprise-scale eCommerce marketplace. Additionally, they might not be analyzing all types of online media, such as branded ads, sponsored search listings, or sponsored category listings.

    Most importantly, another pitfall is the lack of hyperlocal data. Generalized data across regions, states, ZIPs, and stores can skew the decision-making process and result in poor outcomes.

    Overcoming Incomplete or Inaccurate Data

    In order to get the full picture, consumer brands need to ensure they have a view of the entire competitive landscape across their channels. This includes gathering data down to the case pack, the unique product identifier, and the geography, including ZIP and store. They also need the respective MSRP by SKU, the unit normalized price, and the selling price at a specific moment in time. This is done by aggregating brick-and-mortar store information available online, such as when stores list curbside pickup SKUs and pricing online.

    Individual teams cannot manually gather all this detailed data. The growth in eCommerce means there is simply too much data to find and aggregate. Instead, they can employ digital shelf technology to get more data from more sites. Teams can leverage AI to better match product listings, ads, and even visuals to avoid missing data on listings that lack common attributes, such as UPCs for normalization.

    To add to this, advanced pricing intelligence systems can cache URLs to help teams audit and verify their data, avoiding delays and confusion when ad hoc requests arise.

    Challenge 2: Difficulty in Making Sense of the Competitive Landscape

    Once net revenue management and revenue growth management teams have gathered all of the available data, it’s time to make sense of it. This is a monumental challenge, and ends up being the stage where most NRM and RGM teams flounder. Disparate marketplaces include different product attributes and images. This makes it extremely complicated to sync competitors’ data to ready it for analysis, especially if this analysis is carried out manually in Excel. These are some of the attributes that teams need to harmonize in order to make sense of the competitive landscape:

    • Product identifiers (UPC, SKU, Internal Code)
    • Size, case, pack, volume, bundled offerings
    • Language
    • Currency
    • Stock Status (Whether the product is available or not)
    • Platform-specific attributes such as ‘Amazon’s Choice,’ ‘Best Seller,’ etc.

    Teams also need to group and classify various categories of promotions. These can include sponsored listings, banner ads, coupons, bank offers, and others. Each of these categories needs to be tracked separately. This vast array of data points across hundreds of sites creates a big data problem for teams.

    Making Sense of the Competitive Landscape

    The best way to overcome this challenge is to task a digital shelf analytics system with gathering and harmonizing data automatically across the consumer goods competitive landscape. Competitive and market intelligence tools can help break down an overwhelming amount of data, matching similar products across competing brands and analyzing their various strengths and weaknesses. Once the technology matches complex product attributes and identifiers, it becomes easier for teams to gain insights and exploit findings. In a sense, the data needs to be cleaned before analysis can occur.

    Technology can gather data in multiple ways, and the best systems employ several methods to get the best matches. Data consumption modes include API integrations, CSV and Excel file uploads, and proprietary scrapers that view websites independently of direct inputs. Having all the data in a single place helps net revenue management and revenue growth management teams gain indicative insights on product popularity, pricing, and sales, on their own and competitor products.

    Challenge 3: Lack of Timely Visibility

    The final challenge that many net revenue management and revenue growth management teams face is something of a ‘silent killer’ — timeliness. Even if they successfully gather data across the entire competitive landscape and harmonize that data into a format for easy analysis, a lack of timeliness can render even the best actions irrelevant.

    Speed is of the utmost importance when there are market changes. If a product goes viral and competitors raise prices in response to increased demand, without timely visibility, the trend may be over before a consumer goods brand can successfully increase its prices for the duration of the trend. This can mean lost margins.

    Another example is analyzing data and incorporating lagging promotional and sales data into analyses. This can skew pricing strategies because timely data is not accessible to inform decision-making. Many teams waste time firefighting due to a lack of timely pricing and promotional intelligence data.

    Get Near Real-Time Insights for Faster Decision Making

    Using technology that allows for net revenue management and revenue growth management teams at consumer goods brands to establish update frequencies can be a game changer. Teams can set update frequencies based on their need. They can set up the system to check a fast-moving product daily, while a slow-moving item might only need to be checked weekly, monthly, or even quarterly. This allows teams to focus on the highest-impact products first and address the largest exceptions before they lose out on an opportunity. Managing exceptions with a digital shelf analytics platform saves teams significant time instead of poring over low-impact changes in the data.

    Digital Shelf Analytics for Net Revenue Management

    Modernizing a consumer goods brand’s net revenue management or revenue growth management processes requires advanced digital shelf analytics. DataWeave provides consumer goods companies with the technology they need for quick and accurate pricing, promotional, and assortment intelligence. By tracking over 200 million products each day, users can be sure they get the widest and most timely view of the competitive landscape. DataWeave’s deep industry knowledge is baked into every aspect of its platform.

    Learn more by requesting a demo today!

  • Amazon Prime Day Pricing Trends 2024: Deals and Discounts Galore Across Categories

    Amazon Prime Day Pricing Trends 2024: Deals and Discounts Galore Across Categories

    Amazon Prime Day 2024 has once again shattered records, with more items sold during the two-day event than any previous Prime Day. Prime members worldwide saved billions across all categories, while independent sellers moved an impressive 200 million items.

    At DataWeave, we conducted an extensive analysis of the discounts offered by Amazon across major categories. By examining over 47,000 SKUs, we’ve uncovered compelling insights into pricing strategies, competitive positioning, and emerging trends in the eCommerce space.

    Since products on Amazon and other eCommerce websites are often sold at discounts even on normal days not linked to a sale event, we delved into the real value that Prime Day offers to shoppers by focusing on price reductions or the Additional Discount during the sale compared to the week before. As a result, our approach highlights the genuine benefits of the event for shoppers who count on lower prices during the sale. At the same time, our report also includes the Absolute Discounts offered during Prime Day, which represents the total markdown relative to the MSRP.

    Amazon’s Cross-Category Discount Strategy

    Our analysis reveals that the Electronics category saw the highest discounts with an average absolute discount of 20.4% and additional discounts on Prime Day amounting to 10.4%. Meanwhile the Home & Furniture had the lowest discount at 13.1%.

    Discounts offered Across Key Categories on Amazon Prime Day USA 2024

    The Health & Beauty category saw significant additional discounts during Prime Day, at 9.26%. The Apparel category offered attractive absolute (16.10%) and additional (8.90%) discounts.

    Category Deep Dive

    Consumer Electronics

    Still the star of the show, the electronics category saw the highest markdowns this Prime Day with absolute discounts at 20.40% and across 14.61% of their inventory.

    Discounts offered on Consumer Electronics Subcategories During Amazon Prime Day USA 2024.

    Across Electronics subcategories, Earbuds had the highest markdowns at 34.80%, followed closely by Wireless Headphones at 30.60% and Headphones at 29.00%, with steep additional discounts during Prime Day as well. Apple AirPods Pro, for example, retailed at $168 (down from $249) at a 32% discount.

    Discounts offered on Consumer Electronics Subcategories During Amazon Prime Day USA 2024 Featuring Apple Air Pods

    Meanwhile, smartphones had the lowest markdowns at 9.30%, followed by Laptops at 10.50%. Laptops also had the lowest additional discount during Prime Day at just 1.28%, significantly lower than other subcategories. Speakers (20.80%), Drones (19.10%), and Smartwatches (25.00%) offered moderate to high markdowns.

    Notably, all Amazon products including Kindle, Echo, Echo Earbuds, Alexa, Fire TV, Fire TV Stick, and Fire Tablets, were aggressively discounted upwards of 30% this Prime Day. These products also came with the label “Climate Pledge Friendly.”

    Sustainability Features For Amazon Products During Prime Day USA 2024

    These aspects indicate Amazon’s push to promote its own ecosystem of products to the top, as well as cater to changing consumer preferences.

    Apparel

    Discounts offered this Prime Day increased from 13.2% in 2023 to 16.1% in 2024.

    Discounts offered on Apparel Subcategories During Amazon Prime Day USA 2024

    Amid apparel subcategories, Amazon appears to be pushing Women’s apparel categories more aggressively, particularly in Tops, Shoes, and Athleisure.

    Women’s Shoes lead with the highest discounts at 26.50%, followed by Women’s Tops at 22.50% and Men’s Shoes at 22.80%. Women’s Tops also maintained the highest additional discount at 15.27%, followed by Women’s Athleisure at 13.03% and Men’s Swimwear at 12.44%.

    Similar to 2023, Men’s Innerwear offered significantly lower discounts, with only 1% absolute discount and 0.72% additional discount. Women’s Innerwear also shows low discounts at 3.20% absolute and 2.23% additional.

    Health & Beauty

    Amid health & beauty subcategories, Moisturizes witnessed the highest markdowns at 20.10%, followed by Make Up at 18.90%. The Moisturizer subcategory also offers highest additional discounts at 12.20%, followed closely by Sunscreen at 10.25% and Beard Care at 10.22%.

    Discounts offered on Health & Beauty Subcategories During Amazon Prime Day USA 2024

    The Toothpaste subcategory has the lowest discounts, at 10.90%. The lower discounts on everyday essentials like this might indicate a steady demand or an attempt to maintain margins on frequently purchased items.

    Most Health & Beauty subcategories fall in the 15-18% range for actual discounts and 8-10% range for additional discounts. Electric Toothbrush (16.90% actual, 9.91% additional) and Shampoo (16.50% actual, 8.78% additional) represent the middle of the pack. There were a few highly attractive deals though, such as the Philips Sonicare toothbrush retailing at $122.96 (down from $199.99), with a 39% discount.

    Discounts offered on Health & Beauty Subcategories During Amazon Prime Day USA 2024 Featuring A Philips Electric Toothbrush

    Amazon also offered significant discounts on Open Box products (products that are returned, but unused, out of mint condition boxes) to Prime members.

    Home & Furniture

    This category saw the lowest discounts for this Prime Day event at 13.1%. Across subcategories, Rugs lead with the highest average discount at 21.50%, closely followed by Luggage at 20.90%. Amazon seems to be pushing decorative and organizational items (Rugs, Bookcases) more aggressively, possibly due to higher margins. Rugs also stood out as the subcategory with the highest additional discount of 11.54%.

    Discounts offered on Home & Furniture Subcategories During Amazon Prime Day USA 2024

    Sofas have the lowest additional discount at 2.76%, followed by Dining Tables at 3.21%. Items like Cabinets (15.80% absolute, 6.66% additional) and Coffee Tables (14.40% absolute, 6.25% additional) represent the middle range of discounts.

    Watch Out For More

    As the holiday season approaches, it’s clear that the retail landscape continues to evolve. While Amazon remains a formidable force, there are opportunities for savvy competitors to carve out their niches and attract deal-hungry shoppers. By analyzing these trends and adjusting strategies accordingly, retailers can position themselves for success in the high-stakes world of summer sales events.

    Stay tuned to our blog for more insights on how Amazon’s competitors reacted to Prime Day, and how leading brands across categories fared in terms of their pricing and their visibility during the sale event. Reach out to us today to learn more.

  • Cracking the Code: How Retailers Can Adapt to Plummeting Egg Prices in 2024

    Cracking the Code: How Retailers Can Adapt to Plummeting Egg Prices in 2024

    Virtually every cuisine in the world uses eggs. They’re in your breakfast, lunch, dinner, and dessert — which is perhaps why the global egg market is expected to generate $130.70 billion in revenue in 2024 and is projected to grow to approximately $193.56 billion by 2029.

    More specifically, the United States is the fourth-largest egg producer worldwide. The country’s egg market is projected to generate $15.75 billion in 2024 and increase to $22.51 billion by 2029.

    This growth is driven by several factors, most notably:

    • Health-consciousness among consumers: Consumers value eggs for their essential nutrients and rich protein content.
    • Demand for convenience foods: Consumers’ preferences are shifting toward quick and easy foods, which drives demand for shell eggs and pre-packaged boiled or scrambled eggs.
    • Population Growth: A growing worldwide population increases the demand for eggs.
    • Affordability and accessibility: Eggs are an affordable and accessible nutrient-dense food source for many.

    Despite these factors contributing to the U.S. egg market’s growth, recent times have seen egg prices fall dramatically.

    Based on a sample of 450 SKUs, DataWeave discovered that egg prices in the U.S. fell by 6.7% between April 2023 and April 2024, dipping to its lowest (-12.6%) in December 2023.

    Egg Price Chart: Egg Prices USA Going Down 98.95% between April 2023 and April 2024

    So, what’s causing the decrease in egg prices?

    The Rise and Fall of Egg Prices: A Recent History

    In 2022, avian influenza severely impacted the United States. The disease affected wild birds in nearly every state and devastated commercial flocks in approximately half of the country.

    The 2022 incident was the first major outbreak since 2015 and led to the culling of more than 52.6 million birds, mainly poultry, to prevent the disease from spreading uncontrollably.

    With almost 12 million fewer egg-laying hens, the United States produced around 109.5 billion eggs in 2022 — a drop of nearly two billion from the previous year.

    Consequently, the cost of eggs soared, peaking at $4.82 a dozen — more than double the price of eggs in the previous year.

    The avian flu continues to affect egg-laying hens and other poultry birds across the United States. As of April 2024, farms have killed a total of 85 million poultry birds in an attempt to contain the disease.

    Despite the disease’s effects, production facilities have made significant efforts to repopulate flocks, leading to a steady increase in supply – and a much anticipated decrease in egg prices.

    According to the U.S. Bureau of Labor Statistics, there was an increase in producer egg prices in 2022, reaching a peak in November 2022, at which point they began to fall.

    Retailer’s egg prices followed suit. The egg price chart below depicts retailers’ declining egg prices over one year, from April 2023 to April 2024, with Giant Eagle showing the most significant price reductions and Walmart the least.

    Egg Price Chart Featuring Leading Retailers 2023-2024

    What Does the Future Hold for Egg Prices?

    The USDA reported recent severe avian flu outbreaks in June 2024. These outbreaks are estimated to have affected 6.23 million birds.

    With a reduction in egg-laying hens, egg prices are likely to increase — time will tell.

    Nonetheless, the annual per capita consumption of eggs in the U.S. is projected to reach 284.4 per person in 2024 from 281.3 per person in 2023. So for now, producers and retailers can rest assured of the growing demand for eggs.

    How Can Retailers Adapt to the Unpredictability of Egg Prices?

    Egg prices were down to $2.69 for a dozen in May 2024. However, they are still significantly higher than consumers were used to just a few years ago—eggs were, on average, $1.46 a dozen in early 2020.

    Additionally, while the avian flu puts pressure on producers, inflation and supply chain disruptions exert pressure on retailers.

    With such challenging egg market conditions, what can retailers do to maintain customer loyalty amid reduced consumer spending while maintaining profitability?

    1. Give the Customer What They Want: Increase Offerings of Organic, Cage-Free, and Free-Range Eggs

    As mentioned, Data Bridge Market Research’s trends and forecast report highlighted a significant increase in consumer health consciousness. Additionally, animal welfare increasingly influences consumers’ purchasing decisions when buying meat and dairy products.

    DataWeave data shows that the prices of organic, cage-free, and free-range eggs—such as those by brands like Happy Eggs and Marketside—have fallen less than those of non-organic, caged egg brands.

    Egg Price Chart Featuring Leading Egg Brand Prices 2023-2024

    2. Increase Private-Label Offerings

    Private labels typically offer retailers higher margins than national brands. These margins can shield consumers from sudden wholesale egg price swings, helping to preserve brand trust and consumer loyalty without sacrificing profitability.

    Moreover, eggs are particularly suited to private labeling, given their uniform appearance and taste and the lack of product innovation opportunities.

    Undoubtedly, this is why sales of private-label eggs dwarf sales of national egg brands in the United States. Statista reports that across three months in 2024, private label egg sales amounted to $1.55 billion U.S. dollars, while the combined sales of the top nine national egg brands totaled just $617.88 million U.S. dollars.

    3. Price Intelligently

    With the current and predicted fluctuations in egg prices over the foreseeable future, price competitiveness is paramount to margin management and customer loyalty.

    This is especially true when lower prices are the primary factor influencing the average consumer’s choice of supermarket for daily essentials purchases.

    AI-driven pricing intelligence tools like DataWeave give retailers valuable highly granular and reliable insights on competitor pricing and market dynamics. In today’s data-motivated environment, these insights are necessary for competitiveness and profitability.

    Final Thoughts

    Egg prices have fluctuated significantly due to the impact of avian flu. Despite recent price drops, future egg price increases are possible due to ongoing outbreaks. Retailers should adapt to unstable egg prices by increasing organic, free-range, cage-free, and private-label egg offerings while leveraging AI-driven pricing tools to maintain margins and customer loyalty.

    Speak to us today to learn more!

  • How Healthy is Your Assortment?

    How Healthy is Your Assortment?

    In 2025, both consumers and retailers continue to prioritize better health – albeit with evolving definitions and expectations.

    The pandemic fundamentally transformed how consumers approach wellness, with this shift becoming entrenched in shopping behaviors years later. As shopping habits have permanently altered, retailers now face increased pressure to rapidly adapt their assortments with in-demand health and wellness products that enhance customer experience across various channels – online and offline.

    Let’s explore how leading retailers are keeping consumers – and their own bottom lines – healthy by responding effectively to market trends to drive online sales and market share.

    Health & Wellness Influence The Product Mix Across Categories

    Consumption habits have changed dramatically since the onset of the pandemic. A McKinsey study shows that 82% and 73% of US, and UK consumers respectively now consider health & wellness a top priority. Typically shoppers adjust grocery shopping and meal planning at the start of the year, with many focusing on fresh, organic, and nutrient-rich foods.

    The influential health and wellness mega-trend spans diverse retail channels, including grocery, pharmacy and mass. It extends across numerous categories like:

    • Food and beverage (natural, organic, vegan, plant-based food)
    • Health and personal care
    • Beauty
    • Cleaning products
    • Fitness equipment 
    • Athleisure (apparel)
    • Consumer electronics like health wearables.

    Today’s health movement is so powerful and compelling that retailers have revised their business strategies to better serve health-conscious consumers. For instance, drugstores are reinventing themselves as healthcare destinations, with CVS and Kroger expanding into personalized care delivery and value-based clinics to enhance their health offerings.

    Major retailers like Amazon, Walmart, and Target report robust sales in health and wellness categories. For example, Walmart saw a 4.6% increase in comparable sales in early 2024, driven significantly by grocery, consumables, and health-related products.

    New product categories are gaining traction:

    • Functional foods and beverages are seeing unprecedented growth, with Target launching over 2,000 wellness items in the category, including exclusive products priced under $10.
    • Personalized nutrition and mental health products are surging, including tailored dietary solutions and stress-reducing items.
    • Health wearables and wellness tech continue to rise in popularity, with over 150 new wellness tech items launched at Target this year, including innovative red-light therapy devices.
    • Transparency and sustainability certifications like organic, non-GMO, and vegan labels are increasingly driving purchasing decisions.
    • Clinically proven benefits offered by health & wellness products are gaining traction among Gen Z.

    Retail’s Survival Of The Fittest Moves Online

    As the omnichannel retail sector continues to grow, more shoppers now make purchase decisions within minutes using just a few clicks rather than physically visiting brick-and-mortar stores. In some cases, AI agents like Operator from Chat-GPT or Gemini (Google’s Chatbot) even make personalized, curated lists and reduce the time taken to make purchase decisions. Traditional retail paradigms are rapidly becoming obsolete as consumers grow savvier, more empowered, and better informed than ever before.

    To stay competitive, more retailers are embracing AI-driven data insights to adjust their assortments to reflect consumer demand for health and wellness products.

    According to industry experts, data insights have emerged as a critical retail strategy that continues to gain momentum. This is because retailers can no longer afford to guess how to approach their omnichannel strategy. They need the accuracy, clarity, and efficiency of data insights to guide their assortment and pricing decisions to outmaneuver competitors, maximize sales, and win market share as shopping evolves online.

    Among its retail best practices, Bain & Company recommends retailers “lead with superior assortments that use a customer-centric lens to reduce complexity and increase space for the products customers love.” Insights can help retailers discover the optimal mix of national brands, private labels, limited-time offers, and value-added bundles.

    “Lead with superior assortments …
    increase space for the products consumers love    “
    ~ Bain & Company

    Determining the optimal mix of products also includes bestsellers and unique items that help retailers distinguish their offerings. Assortment insights help retail executives track competitors’ assortment changes and spot gaps in their own product assortment to adapt to emerging consumer trends and in-demand products.

    Why Effective Assortment Planning Matters

    Assortment planning sits at the heart of retail success, directly influencing profitability, customer satisfaction, and competitive differentiation. In today’s health-conscious market, getting your assortment right means:

    • Meeting Customer Expectations: Today’s health-conscious consumers expect relevant, high-quality products that match their wellness goals. A well-planned assortment signals that a retailer understands its customers’ evolving needs.
    • Optimizing Inventory Investment: Strategic assortment planning ensures capital is allocated to products with the highest return potential while minimizing investments in slow-moving items.
    • Creating Competitive Advantage: A distinctive assortment that includes popular health and wellness products alongside unique offerings helps retailers stand out in a crowded marketplace.
    • Reducing Lost Sales: Effective assortment planning minimizes the risk of stockouts on high-demand health and wellness items, preventing customers from shopping elsewhere.
    • Supporting Omnichannel Strategies: Well-executed assortment planning ensures consistency across physical and digital touchpoints, creating a seamless customer experience.
    • Improving Operational Efficiency: A thoughtfully curated assortment reduces complexity throughout the supply chain, from procurement to warehouse management to in-store operations.

    As health and wellness continues to drive consumer spending, retailers who excel at assortment planning can capitalize on these trends more effectively than their competitors, turning market insights into tangible business results.

    AI-Powered Assortment Analytics Driving Retail Success

    The synergy of AI and data analytics into retail assortment planning is changing how businesses approach inventory management. Retailers using AI-driven predictive analytics have achieved a 36% SKU reduction while increasing sales by 1-2%, showcasing the efficiency of data-driven approaches according to a McKinsey report.

    Retailers face several challenges that can hinder strategic assortment planning:

    • Limited Understanding of Competition: Retailers struggle to gain comprehensive insights into their product assortments relative to competitors, often lacking visibility into their strengths and weaknesses across categories.
    • Data Overload: Assortment planning involves handling vast amounts of data, making it challenging for category managers to extract actionable insights without user-friendly tools and visualization.
    • Cross-Channel Consistency: With omnichannel retailing, ensuring consistency across physical stores, e-commerce, and other channels is complex. Misalignment can lead to customer dissatisfaction and loss of loyalty.
    • Adapting to Changing Market Trends: Identifying top-selling products and tracking consumer preferences is challenging. Balancing the right mix of products is crucial; without analytics, retailers risk lost sales or excess slow-moving inventory.
    • Scalability and Efficiency: As retailers expand into new markets or categories, scaling their assortment planning processes efficiently becomes a challenge. Legacy systems and manual methods often fail to support the agility needed for quick decision-making at scale.

    DataWeave’s Assortment Analytics helps retailers address these challenges by providing a robust, easy-to-use platform that delivers actionable insights into product assortments and competitive positioning. With AI-driven, contextual insights and alerts, retailers can effortlessly identify high-demand, unique products, capitalize on catalog strengths, optimize pricing and promotions, improve stock availability, and refine assortments to maintain a competitive edge.

    Beyond Data: Actionable Insights That Drive Results

    DataWeave’s platform provides a comprehensive, insight-led view into assortments through several key dimensions:

    • Stock Insights: Monitor stock changes across retailers to stay updated on availability.
    • Category and Sub-Category Insights: Analyze assortment changes, identify newly introduced or discontinued categories, and track leading retailers in specific segments.
    • Brand Insights: Identify newly introduced, missing, or discontinued brands, as well as leading brands within chosen categories.
    • Product Insights: Identify bestsellers and evaluate their impact on your portfolio, analyzing pricing and promotions.
    • Personalized Recommendations: Receive suggestions tailored to your behavior and user profile to refine decision-making.
    • User-Configured Alerts: Stay informed with alerts designed to highlight significant changes or opportunities.

    The platform addresses data overload by providing an intuitive, insight-driven view of your assortment. Category managers gain a comprehensive, bird’s-eye perspective of key changes within specified timeframes, allowing them to focus on what matters most.

    Preparing for the Future of Retail Health

    To avoid supply chain bottlenecks, inventory shortages, and out-of-stock scenarios, retailers are strategically using data insights to anticipate fluctuations in demand and proactively plan how to manage disruptions that could affect their assortments.

    For variety that satisfies consumers’ diverse product needs, retailers are using data insights to determine whether to collaborate with nimble suppliers to promptly fill any gaps.

    To further strengthen their assortments’ attractiveness, retailers are using AI-powered pricing analytics to offer the right product at the right price. These analytics help retailers know exactly how they compare to rivals’ pricing moves with relevant data so they can keep up with market fluctuations and stay competitive by earning consumer engagement, sales, and trust.

    To Conclude…

    Like nourishing habits that improve consumers’ health, data insights improve retailers’ e-commerce health. Advanced assortment and pricing analytics, powered by artificial intelligence, help retailers make better decisions faster to boost their agility, outmaneuver rivals, and fuel online growth.

    In a retail landscape where consumer preferences for health and wellness continue to evolve rapidly, the retailers who thrive will be those who leverage data and AI to understand, anticipate, and meet these changing demands with the right products at the right time. Reach out to us to know more.

  • How Retailers and Brands Can Navigate Skyrocketing Olive Oil Prices in 2024

    How Retailers and Brands Can Navigate Skyrocketing Olive Oil Prices in 2024

    Olive oil, renowned for its complex flavor and myriad health benefits, holds a significant place in the global market, valued at $14.64 billion in 2023. It is anticipated to reach $19.77 billion by 2032, with a steady compound annual growth rate (CAGR) of 3.42%.

    This growth is fueled by:

    • Increased consumer demand for healthier oils.
    • Olive oil’s rising popularity in skincare products.
    • Greater retail availability.

    Interestingly, this market expansion occurs alongside rising olive oil prices, mainly due to a notable decrease in production. Eight European Union countries, which are the main producers, saw a dramatic drop in output from an average of 2.17 million tons to just 1.50 million tons in 2022—a 30.88% decline. Unfortunately, this drop in production comes as no surprise.

    Erratic weather patterns, rising temperatures, and exacerbating drought conditions in the Mediterranean basin have taken their toll. These climate changes disrupt the growing cycles of olive trees, leading to poorer crop yields and lower-quality olives.

    In the US, where olive oil constitutes 19% of all cooking oils sold and 40% of sales value due to its premium pricing, the market is expected to grow at an impressive CAGR of 11.31% between 2024 and 2032. This forecast is significant despite a recent dip in domestic consumption, which may further decline due to economic pressures. As a result, consumers must make difficult choices as they battle inflation, shrinkflation, and thin budgets.

    DataWeave’s Analysis of Rising Olive Oil Prices

    At DataWeave, we utilized our advanced AI-powered data aggregation and analysis platform to scrutinize the pricing trends of olive oils across key US retailers over the past year. Our analysis covered 130+ SKUs from major chains including Walmart, Kroger, Giant Eagle, and Target.

    The data revealed a notable escalation in olive oil prices, with consumers facing a sharp 25.8% increase from April 2023 to April 2024.

    This trend of rising costs was consistent across all analyzed retailers. Specifically, Walmart and Giant Eagle each reported a substantial 30% increase in their olive oil prices over the past year. In contrast, Target and Kroger experienced somewhat more modest hikes, at 20% and 15% respectively.

    Further investigation into individual brands within our sample highlighted that no brand is immune to the impacts of the ongoing supply shortages. Walmart’s own Great Value brand saw an exceptional 60% surge in prices. Other prominent olive oil brands such as Carapelli, Terra Delysia, and Bertolli also faced significant price increases, ranging from 20% to 50%.

    This across-the-board rise in prices underscores the widespread effect of supply constraints on the olive oil market, affecting both premium and private label brands alike.

    What Strategies Can Retailers and Brands Employ?

    In a market where consumer preferences and price sensitivities are rapidly evolving, retailers and brands must adopt versatile strategies without compromising on profit margins.

    Diversifying Brand Selection

    Retailers can enhance their appeal by offering a diverse range of olive oil brands, thereby stimulating competition among brands based on price, quality, innovation, and customer satisfaction. A well-curated selection that includes well-known brands like Filippo Berio and Bertolli, alongside emerging labels such as Terra Delyss, and premium options like Carapelli, allows retailers to meet a wide array of consumer preferences and budgets.

    For premium outlets, it might be beneficial to introduce more economical options than typically offered to attract budget-conscious consumers. Employing advanced assortment intelligence tools can provide retailers with crucial data, helping them make informed decisions about which brands to stock and promote, ensuring they meet consumer demand effectively while managing inventory costs.

    Data-driven Pricing

    With rising olive oil prices, competitive pricing is more crucial than ever. Retailers must strive to balance competitiveness with margin preservation. It’s essential for retailers to not just passively respond to market price increases but to actively ensure that their offerings are competitively priced relative to the market.

    This involves using sophisticated pricing intelligence tools, such as those provided by DataWeave, which track market trends and competitor pricing actions. These tools enable retailers to implement dynamic pricing strategies that respond promptly to market conditions and consumer demand shifts, helping to optimize sales and profitability.

    Diversifying Sourcing

    The traditional powerhouses of olive oil production, Spain and Italy, are now facing stiff competition from countries like Turkey and Tunisia. This shift is influenced by various factors, including currency fluctuations and changing trade policies, such as the imposition of tariffs on European olive oils by significant importers like the US. Retailers can take advantage of these changes by diversifying their sourcing strategies to include olive oil from non-traditional regions.

    The 2022/2023 season saw remarkable production levels from countries outside the Mediterranean basin, with Iran and China setting new production records. By broadening their supply chains to incorporate these emerging markets, retailers can benefit from lower production costs and introduce unique products to their consumers, enhancing both competitiveness and profit margins.

    Double Down on Private Labels

    Large retailers have successfully used their scale to develop strong private-label brands that can buffer consumers from price hikes in the olive oil market. By focusing on expanding and promoting their private-label offerings, retailers can provide cost-effective alternatives to national brands.

    Private labels generally have lower price points, making them particularly attractive during times of economic pressure and market volatility. Additionally, the development of private labels allows retailers to control more of their supply chain, from pricing to packaging, enabling them to offer high-quality products at competitive prices, thereby retaining customer loyalty and enhancing market share.

    Navigating Market Pressures

    High olive oil prices impact the entire supply chain, presenting varied challenges and opportunities:

    • Producers benefit from higher revenues but face increased pressure to maintain quality and yields in challenging climates. Adapting to these conditions with sustainable practices is crucial.
    • Exporters and Importers navigate tighter margins and greater risks due to tariffs and volume restrictions, requiring agility and strategic planning to adapt to market changes.
    • Retailers must carefully balance competitive pricing with rising procurement costs, affecting consumer affordability and potentially leading to shifts in buying patterns.
    • Consumers may seek cheaper alternatives or reduce their olive oil consumption, which influences overall market demand and pricing stability.

    These dynamics underscore the necessity for retailers and brands to adopt innovative and proactive strategies to navigate the volatile olive oil market effectively. By focusing on adaptive pricing, diversified sourcing, and customer engagement, businesses can enhance their resilience and secure long-term success in this competitive landscape.

    To learn more, talk to us today!

  • Using Siamese Networks to Power Accurate Product Matching in eCommerce

    Using Siamese Networks to Power Accurate Product Matching in eCommerce

    Retailers often compete on price to gain market share in high performance product categories. Brands too must ensure that their in-demand assortment is competitively priced across retailers. Commerce and digital shelf analytics solutions offer competitive pricing insights at both granular and SKU levels. Central to this intelligence gathering is a vital process: product matching.

    Product matching or product mapping involves associating identical or similar products across diverse online platforms or marketplaces. The matching process leverages the capabilities of Artificial Intelligence (AI) to automatically create connections between various representations of identical or similar products. AI models create groups or clusters of products that are exactly the same or “similar” (based on some objectively defined similarity criteria) to solve different use cases for retailers and consumer brands.

    Accurate product matching offers several key benefits for brands and retailers:

    • Competitive Pricing: By identifying identical products across platforms, businesses can compare prices and adjust their strategies to remain competitive.
    • Market Intelligence: Product matching enables brands to track their products’ performance across various retailers, providing valuable insights into market trends and consumer preferences.
    • Assortment Planning: Retailers can analyze their product range against competitors, identifying gaps or opportunities in their offerings.

    Why Product Matching is Incredibly Hard

    But product matching stands out as one of the most demanding technical processes for commerce intelligence tools. Here’s why:

    Data Complexity

    Product information comes in various (multimodal) formats – text, images, and sometimes video. Each format presents its own set of challenges, from inconsistent naming conventions to varying image quality.

    Data Variance

    The considerable fluctuations in both data quality and quantity across diverse product categories, geographical regions, and websites introduce an additional layer of complexity to the product matching process.

    Industry Specific Nuances

    Industry specific nuances introduce unique challenges to product matching. Exact matching may make sense in certain verticals, such as matching part numbers in industrial equipment or identifying substitute products in pharmaceuticals. But for other industries, exactly matched products may not offer accurate comparisons.

    • In the Fashion and Apparel industry, style-to-style matching, accommodating variants and distinguishing between core sizes and non-core sizes and age groups become essential for accurate results.
    • In Home Improvement, the presence of unbranded products, private labels, and the preference for matching sets rather than individual items complicates the process.
    • On the other hand, for grocery, product matching becomes intricate due to the distinction between item pricing and unit pricing. Managing the diverse landscape of different pack sizes, quantities, and packaging adds further layers of complexity.

    Diverse Downstream Use Cases

    The diverse downstream business applications give rise to various flavors of product matching tailored to meet specific needs and objectives.

    In essence, while product matching is a critical component in eCommerce, its intricacies demand sophisticated solutions that address the above challenges.

    To solve these challenges, at DataWeave, we’ve developed an advanced product matching system using Siamese Networks, a type of machine learning model particularly suited for comparison tasks.

    Siamese Networks for Product Matching

    Our methodology involves the use of ensemble deep learning architectures. In such cases, multiple AI models are trained and used simultaneously to ensure highly accurate matches. These models tackle NLP (natural language processing) and Computer Vision challenges specific to eCommerce. This technology helps us efficiently narrow down millions of product candidates to just 5-15 highly relevant matches.

    The Tech Powering Siamese Networks

    The key to our approach is creating what we call “embeddings” – think of these as unique digital fingerprints for each product. These embeddings are designed to capture the essence of a product in a way that makes similar products easy to identify, even when they look slightly different or have different names.

    Our system learns to create these embeddings by looking at millions of product pairs. It learns to make the embeddings for similar products very close to each other while keeping the embeddings for different products far apart. This process, known as metric learning, allows our system to recognize product similarities without needing to put every product into a rigid category.

    This approach is particularly powerful for eCommerce, where we often need to match products across different websites that might use different names or images for the same item. By focusing on the key features that make each product unique, our system can accurately match products even in challenging situations.

    How Siamese Networks Work?

    Imagine having a pair of identical twins who are experts at spotting similarities and differences. That’s essentially what a Siamese network is – a pair of identical AI systems working together to compare things.

    How it works:

    • Twin AI systems: Two identical AI systems look at two different products.
    • Creating ‘fingerprints’ or ‘embedding’: Each system creates a unique ‘fingerprint’ of the product it’s looking at.
    • Comparison: These ‘fingerprints’ are then compared to see how similar the products are.

    Architecture

    The architecture of a Siamese network typically consists of three main components: the shared network, the similarity metric, and the contrastive loss function.

    • Shared Network: This is the ‘brain’ that creates the product ‘fingerprints’ or ‘embeddings.’ It is responsible for extracting meaningful feature representations from the input samples. This network is composed of layers of neural units that work together. Weight sharing between the twin networks ensures that the model learns to extract comparable features for similar inputs, providing a basis for comparison.
    • Similarity Metric: After the shared network processes the inputs, a similarity metric is employed. This decides how alike two ‘fingerprints’ or ‘embeddings’ are. The selection of a similarity metric depends on the specific task and characteristics of the input data. Frequently used similarity metrics include the Euclidean distance, cosine similarity, or correlation coefficient, each chosen based on its suitability for the given context and desired outcomes.
    • Loss Function: For training the Siamese network, a specialized loss function is used. This helps the system improve its comparison skills over time. It guides and trains the network to generate akin embeddings for similar inputs and disparate embeddings for dissimilar inputs.

      This is achieved by imposing penalties on the model when the distance or dissimilarity between similar pairs surpasses a designated threshold, or when the distance between dissimilar pairs falls below another predefined threshold. This training strategy ensures that the network becomes adept at discerning and encoding the desired level of similarity or dissimilarity in its learned embeddings.

    How DataWeave Uses Siamese Networks for Product Matching

    At DataWeave, we use Siamese Networks to match products across different retailer websites. Here’s how it works:

    Pre-processing (Image Preparation)

    • We collect product images from various websites.
    • We clean these images up to make them easier for our AI to understand.
    • We use techniques like cropping, flipping, and adjusting colors to help our AI recognize products even if the images are slightly different.

    Training The AI

    • We show our AI system millions of product images, teaching it to recognize similarities and differences.
    • We use a special learning method called “Triplet Loss” to help our AI understand which products are the same and which are different.
    • We’ve tested different AI structures to find the one that works best for product matching, including ResNet, EfficientNet, NFNet, and ViT. 

    Image Retrieval 

    • Once trained, our AI creates a unique “fingerprint” for each product image.
    • We store these fingerprints in a smart database.
    • When we need to find a match for a product, we:
      • Create a fingerprint for the new product.
      • Quickly search our database for the most similar fingerprints.
      • Return the top matching products.

    Matches are then assigned a high or a low similarity score and segregated into “Exact Matches” or “Similar Matches.” For example, check out the image of this white shoe on the left. It has a low similarity score with the pink shoe (below) and so these SKUs are categorized as a “Similar Match.” Meanwhile, the shoe on the right is categorized as an “Exact Match.”

    Similarly, in the following image of the dress for a young girl, the matched SKU has a high similarity score and so this pair is categorized as an “Exact Match.”

    Siamese Networks play a pivotal role in DataWeave’s Product Matching Engine. Amid the millions of images and product descriptions online, our Siamese Networks act as an equalizing force, efficiently narrowing down millions of candidates to a curated selection of 10-15 potential matches. 

    In addition, these networks also find application in several other contexts at DataWeave. They are used to train our system to understand text-only data from product titles and joint multimodal content from product descriptions.

    Leverage Our AI-Driven Product Matching To Get Insightful Data

    In summary, accurate and efficient product matching is no longer a luxury – it’s a necessity. DataWeave’s advanced product matching solution provides brands and retailers with the tools they need to navigate this complex landscape, turning the challenge of product matching into a competitive advantage.

    By leveraging cutting-edge technology and simplifying it for practical use, we empower businesses to make informed decisions, optimize their operations, and stay ahead in the ever-evolving eCommerce market. To learn more, reach out to us today!

  • Why Strategic Competitive Insights Are Key to Optimizing Your Product Assortment

    Why Strategic Competitive Insights Are Key to Optimizing Your Product Assortment

    For retailers, the breadth and relevance of their product assortment are critical for success. Amid a crowded market filled with countless products clamoring for consumer attention, retailers must find innovative ways to distinguish themselves. While pricing undeniably impacts purchasing decisions, the diversity and distinctiveness of a retailer’s product range can provide a crucial competitive advantage.

    Creating an attractive and profitable assortment that resonates with your target audience requires more than intuition; it demands deep insights into both your own and your competitors’ offerings. A well-curated assortment aligned with current trends can drive higher conversions and foster customer loyalty. However, achieving this perfect balance is a formidable challenge without the right insights.

    This is where a data-driven strategy becomes essential, enabling you to curate a product mix that captivates and converts.

    However, retailers often encounter significant challenges when attempting to strategically plan their assortments:

    • Limited Competitive Insights: Gaining a clear understanding of your competitors’ assortment strengths and weaknesses across various categories is challenging. Without this visibility, it’s difficult to know where you have an edge or where you might be falling behind.
    • Tracking Demand Patterns: Identifying top-sellers and monitoring shifts in consumer demand can be a struggle. Without the ability to easily detect trends or changes in demand, you risk missing opportunities to stock trending items.

    Attempting to navigate these challenges manually is not only arduous but also susceptible to substantial errors.

    How Assortment Analytics Solutions Help

    The ideal Assortment Analytics solution must offer a fact-based approach to:

    • Identify Strengths and Weaknesses: Understand how your assortment measures up against the competition.
    • Stay Trend-Responsive: Keep your product mix fresh and aligned with the latest consumer trends.
    • Boost Conversions: Create a relatively unique, customer-focused assortment that enhances conversions.

    Many retailers attempt to analyze competitor assortments using manual, in-house methods, which inevitably leads to significant blind spots:

    • Variations in product classifications and taxonomies across competitors make meaningful comparisons challenging.
    • Gathering complete and accurate data across a vast competitive landscape is difficult.
    • Inconsistent titles and descriptions hinder reliable product matching without AI assistance.
    • Capturing and comparing detailed product attributes efficiently is nearly impossible without advanced tools.

    To overcome these challenges, retailers need a scalable, accurate Assortment Analysis solution designed specifically for the complexities of modern retail needs.

    DataWeave’s Assortment Analytics Solution

    DataWeave addresses these challenges by providing retailers with a robust platform to gain actionable insights into their product assortments and the competitive landscape. Leveraging advanced analytics and AI-driven algorithms, Assortment Analytics empowers retailers to make informed assortment management decisions, optimize their product offerings, and stay competitive.

    Armed with our insights, retailers can lead with their strengths and stock unique and in-demand products in their assortment. Further, by recognizing the strengths in their product catalog, they can craft effective pricing strategies and optimize their logistics, creating a more competitive and appealing shopping experience for their customers. Here are a few capabilities of DataWeave’s solution:

    In-Depth Competitive Analysis Across Retailers

    The solution offers detailed competitive analysis, revealing insights into competitors’ assortments. It maps competitor products to a common taxonomy, making comparisons accurate and meaningful. Retailers can visualize assortments at granular levels like category, sub-category, and product type.

    The data for these insights is collected at configurable intervals, typically monthly or quarterly, and is consumed not only via dashboard summaries but also raw data files to enable in-depth analysis. Retailers have the flexibility to choose specific competitors, brands, products, and categories for tracking, allowing for a tailored and strategic approach to assortment optimization.

    Brand and Category Views to Assess Your Portfolio

    The solution provides a comprehensive evaluation of your product assortment through brand and category views. In brand views, your portfolio is assessed against competitors at the brand level, highlighting:

    • Newly Introduced Brands: Insights into recently introduced brands, revealing shifts in the brand landscape.
    • Absence or Limited Presence: Identification of brands lacking representation or with minimal presence compared to competitors, indicating areas for improvement.
    • Strong Presence and Exclusivity: Recognition of brands where you excel, including exclusive offerings, showcasing your competitive edge.

    Identifying Top-Selling Competitive Products To Boost Assortment Strategy

    Beyond just comparing assortment numbers, the DataWeave solution surfaces insights into which competitor products are actually performing well. It equips category and assortment managers with indicators that assess competitor products in terms of their popularity and shelf velocity.

    It analyzes metrics like pricing fluctuations, ratings, customer reviews, search rankings, and replenishment rates to pinpoint hot sellers you may want to stock. With these insights, merchandizing managers can pinpoint top-selling products among competitors, enabling informed decisions to enhance their assortment in comparison.

    Sophisticated Attribute Tagging and Analysis

    Using AI-powered attribute tagging, the solution simplifies granular product analysis within specific categories. An Apparel retailer, for instance, can filter the data to compare assortments based on attributes like material, pattern, color, etc.

    Retailers can select attributes relevant to their products and gain detailed insights. These custom filter attributes dynamically populate the panel, facilitating targeted data exploration. Category and merchandizing managers can delve into critical details swiftly, enabling strategic decision-making and comprehensive competitive analysis within their categories.

    You can capitalize on opportunities by stocking in-demand, on-trend items and address assortment gaps quickly. At the same time, you can double down on your strengths by enhancing your exclusive or top-performing product sets.

    In summary, DataWeave’s Assortment Analytics solution provides an invaluable competitive edge. The insights enable evidence-based decisions to attract more customers, encourage bigger baskets, and maximize the value of every assortment choice.

    To learn more, read our detailed product guide here or get on a exploratory call with one of our experts today!

  • 5 Must-Have Capabilities of Your Ideal Competitive Pricing Intelligence Solution

    5 Must-Have Capabilities of Your Ideal Competitive Pricing Intelligence Solution

    In the cutthroat world of retail, where razor-thin margins and fierce competition reign supreme, pricing becomes your secret weapon to driving sales. The magic bullet unlocks sales, attracts customers, and ultimately fuels your bottom line. But with ever-changing market trends and competitor tactics shifting constantly, effective pricing strategies become even more crucial.

    A recent Bain & Company study highlights this very point. 78% of respondents acknowledged that their pricing decisions could be improved, leaving significant revenue untapped. John Furner, President and CEO of Kroger, echoes this sentiment. In a press release announcing a new pricing strategy, he emphasized their commitment to “providing our customers with predictable, affordable prices on the products they need most.” This focus on transparent and consistent pricing reflects the growing importance of building trust with customers, where value goes beyond just the lowest price tag.

    The right pricing strategy can unlock a treasure trove of benefits for retailers, including attracting new customers, boosting sales, and ultimately increasing their bottom line.

    But here’s the challenge: keeping pace with market trends and competitor strategies requires constant vigilance. This is where an advanced, user-centric pricing intelligence tool comes into play. Retailers need a platform specifically designed to address their unique challenges. It should empower them to protect margins, create a seamless pricing process, and attract and retain price-sensitive customers. To help you navigate this landscape, we’ve identified the must-have capabilities of a pricing intelligence solution that will transform your pricing strategy and propel your business toward long-term success.

    1. Reliable and Accurate Data Collection

    Retailers need a competitive intelligence solution that goes beyond merely capturing information en masse from competitor sites. An ideal solution ensures that data is consistent, extensive, and highly accurate, with an added level of granularity. This is achieved through statistical process control methods for data quality assurance, enabling highly accurate data capture and processing.

    Such a platform should be capable of scraping data from various sources, including desktop sites, mobile sites, and mobile applications, as well as a variety of online platforms: aggregators, omnichannel retailers, delivery intermediaries, quick commerce platforms, D2C sites, and more. This versatility ensures that data is captured across any global region and in dozens of languages, making the system geography and language agnostic.

    DataWeave’s solution includes a fast and automated data source configuration system, enabling a swift setup of new web sources for data capture. This capability ensures that retailers can stay ahead of the curve as the market landscape and competitor strategies evolve.

    An effective competitive pricing intelligence solution allows retailers to move away from working with incomplete or inaccurate data and instead leverage a comprehensive information stream to create strategic pricing decisions and optimize their overall business strategy. At the end of the day, the insights you base your decisions on are only as good as the data you aggregate. Even with the world’s best analytics engine, it’s always a case of “garbage in, garbage out.”

    2. Hyperlocal Insights From Store-Level Data

    Monitoring pricing and availability across specific stores is crucial for retailers to gain critical insights into a vast network of locations, enabling them to make strategic decisions that enhance pricing strategies and supply chain effectiveness, thereby minimizing stockouts or pricing inefficiencies in key markets. A platform like DataWeave provides retailers with a comprehensive view of store-level data across ZIP codes, maintaining a hyperlocal competitive strategy. It offers detailed visibility into product availability, highlighting out-of-stock scenarios across different competitors. This capability is invaluable, allowing quick identification of price improvement opportunities and providing retailers with a bird’s eye view of where products can be priced higher than usual to gain margins.

    The system operates at configurable intervals—daily, weekly, or monthly—enabling retailers to keep a vigilant eye on pricing, product availability, and delivery timelines based on the selected fulfillment option. Unlike many other providers who offer limited insights from a sample of stores, this solution delivers exhaustive analytics from every storefront. This comprehensive approach grants retailers (and brands) a strategic edge, facilitating efficient inventory tracking, precise pricing adjustments, and rapid responses to fluctuating market dynamics.

    3. Sophisticated, AI-Powered Product Matching

    A solution that matches products accurately at scale is essential for a robust and reliable competitive pricing strategy. Advanced platforms use unified systems for both text and image recognition to accurately match similar SKUs across thousands of eCommerce stores and millions of products. Deep learning architecture is employed to develop unique AI that matches text and images, grouping similar products based on their features, ensuring accurate matches even for private label products.

    This AI identifies critical elements of products in images, such as focusing on the top half of a model wearing a shirt, the sleeve length, the color of the product, etc.. Deep learning models, trained on extensive datasets of images, enhance these images by removing irrelevant background details and improving the quality of the core product image. Innovative AI then extracts unique signatures from the photos, allowing for quick and efficient identification and grouping of products across billions of indexed items.

    No matter how powerful the AI, combining it with human expertise is key to achieving true data veracity—ensuring accuracy, freshness, and comprehensive coverage required for reliable product matching. A human-in-the-loop approach elevates the AI-powered product matching process by addressing key challenges. AI algorithms may initially identify product matches with 80-90% accuracy, but human validation corrects errors, pushing accuracy closer to 100%. Humans apply contextual judgment for subjective criteria like aesthetics and design, making nuanced decisions that quantitative rules might miss. Continuous learning through an iterative feedback loop allows AI models to quickly adapt to changing trends and preferences as human experts provide context and re-label incorrect predictions. By integrating AI’s automation and scale with human validation, judgment, and knowledge curation, pricing intelligence solutions can achieve the accuracy and coverage necessary for actionable competitive pricing insights.

    This approach results in retailers being able to match products and compare prices between identical products, similar products, and private label brands.

    4. Unit of Measure Normalization

    Effective product matching and grouping are crucial for maintaining competitive pricing, but this requires a tech stack that can normalize units of measure across various sites. For example, a 10.75oz can of chicken noodle soup priced at $3 may seem cheaper than a 12.90oz can priced at $3.20, but this isn’t always the case. Initially, the larger package might appear more expensive, but when prices are compared based on the same unit amount, it often offers better value. Therefore, it is essential for retailers to standardize units to accurately compare prices. Advanced technology goes beyond simply matching products; it ensures accurate comparisons by normalizing unit measurements, including weight, quantity, and volume—crucial factors for establishing a clear pricing picture across competitors.

    Imagine comparing soup prices regardless of whether they are advertised in ounces, milliliters, or liters. By normalizing unit measurements, retailers can develop tailored pricing strategies on a level playing field, eliminating the risk of being misled by seemingly lower prices that conceal smaller quantities. Unit normalization allows retailers to uncover hidden value propositions by accurately determining the cost per unit, enabling them to set competitive prices, highlight the true value of their products, and make data-driven decisions.

    5. Ease of Actionability

    The most valuable insights are ineffective if they cannot be easily accessed and acted upon. Imagine a solution that not only provides industry insights but also customizes alerts and dashboards to show exactly how your prices compare to competitors in your specific categories and product groupings. An ideal solution would offer all this in one centralized platform, giving retailers easy access to data through intuitive dashboards, seamless data export options, and flexible API integrations. This enables a smooth, effortless process for adopting and utilizing the platform.

    Ease of use and actionable insights should be at the core of such a solution. A SaaS-based web portal can provide businesses with access to insights through user-friendly dashboards, detailed reports, and impactful visualizations. Customized insights tailored for each persona within the organization facilitate swift actions on relevant competitive intelligence. Whether it’s day-to-day tactical recommendations or inputs for long-term strategies, the platform should ensure that all insights are easily consumable and actionable.

    Moreover, the data should be accessible using plug-and-play APIs, enabling businesses to integrate external data with their internal pricing or ERP systems and BI tools. This integration generates predictive intelligence, enhances decision-making, and drives more robust business outcomes.

    Choosing the Right Pricing Intelligence Solution Will Determine Your Success

    Retailers need to leave behind generic pricing intelligence tools. For true success, retailers need a solution built to tackle their specific challenges. With capabilities like comprehensive data collection capturing granular details across regions and languages, local insights into store-level data for informed decision-making, accurate price comparisons with unit normalization, and access to actionable insights, retailers gain a complete and holistic picture of the pricing landscape, setting them up for success. Additionally, AI-powered and human-aided product matching ensures accurate competitor analysis

    These are just some of the essential capabilities DataWeave offers to retailers. By prioritizing these, retailers can transform their pricing strategy into a profit-generating machine, keeping them ahead of the curve and exceeding customer expectations in a competitive market to help them stay at the forefront of their categories.

    To learn more, talk to us today!

  • Cinco de Mayo 2024 Pricing Insights: An Analysis of Discounts Amid Inflation

    Cinco de Mayo 2024 Pricing Insights: An Analysis of Discounts Amid Inflation

    Cinco de Mayo is a vibrant celebration of Mexican-American and Hispanic heritage, marked by lively parades, festive tacos, and refreshing tequila across North America. For the service industry, brands, and retailers, this day offers a golden opportunity to roll out enticing promotions on beloved Mexican foods and beverages, drawing in large crowds and boosting sales.

    Americans love to indulge in Mexican cuisine during Cinco de Mayo. Take avocados, for example: despite inflation, avocado sales soared to 52.3 million units this year, marking a 25% increase from last year, according to the Hass Avocado Board’s 2023 Holiday Report. Such festive events see a significant sales spike, largely driven by appealing discounts and special offers.

    So, what discounts did retailers roll out this Cinco de Mayo?

    At DataWeave, our cutting-edge data aggregation and analysis platform tracked and analyzed the prices and deals on Mexican food and alcohol products offered by leading retailers. Our in-depth analysis sheds light on their pricing competitiveness during Cinco de Mayo, revealing how pricing strategies differed across various subcategories and brands.

    We conducted a similar analysis in 2022, allowing us to compare the prices of identical products this year versus last year. This comparison helps us understand the impact of inflation over the past two years on the prices offered today.

    Our Methodology

    For our analysis, we monitored the average discounts offered by major US retailers on over 2,000 food and beverage products during Cinco de Mayo, as well as in the days leading up to the event. Many retailers kick off their Cinco de Mayo promotions a week before, so we included the entire week leading up to May 5th in our analysis.

    Key Details:

    • Number of SKUs: 2000+
    • Retailers Analyzed: Target, Amazon Fresh, Safeway, Walmart, Total Wines & More, Sam’s Club, Meijer, Kroger
    • Categories: Food, Alcohol
    • Analysis Period: April 28 – May 5

    To truly demonstrate the value of Cinco de Mayo for shoppers, we concentrated on price reductions and additional discounts during the event. By comparing these with regular day discounts, we were able to highlight the genuine savings and benefits that Cinco de Mayo promotions offer to budget-conscious consumers.

    Our Findings

    Safeway led the pack with the highest average additional discount of 4.91%, covering 38.6% of their food inventory for Cinco de Mayo. Total Wine & More followed closely, offering an average discount of 3.46% across 70.8% of its tequila, whiskey, mezcal, and other spirit products during the Cinco de Mayo week.

    In contrast, Target provided minimal additional discounts, averaging just 0.8% over a small fraction (11.6%) of its SKUs. Similarly, Kroger’s additional discounts were also 0.8%, but they were spread across over 60% of its tracked products. Walmart (1.4%) and Amazon Fresh (1.2%) offered relatively conservative discounts during the sale period.

    During Cinco de Mayo, various brands rolled out attractive discounts to entice shoppers. Among beverage brands, The American Plains vodka led the way with the highest average discount of 20.80%. Coffee brands also joined the festivities with significant discounts: Death Wish Coffee at 14.30%, Dunkin’ at 11.10%, and Starbucks at 5.70%. Notably, Dunkin’ and Death Wish Coffee introduced complimentary beverages such as whiskey barrel-aged coffee and spiked coffee products to celebrate the event.

    In the wine category, Erath stood out with a 10% additional discount. However, brands like Jose Cuervo and Franzia offered more modest discounts of 0.70% and 1.80%, respectively.

    Food brands associated with traditional Mexican ingredients or products, such as tortillas, salsas, and spices, provided higher discounts compared to mainstream snack brands. For instance, McCormick (25%), El Monterey (13.3%), and La Tortilla Factory (16.7%)—known for ready-to-eat frozen foods, seasonings, and condiments—delivered the highest discounts. Other notable discounts included Jose Ole (12.5%), a frozen food brand, and Yucatan (8.3%), known for its guacamole.

    Safeway’s private label brand, Signature Select, offered a 5.20% discount. Additionally, Safeway provided deep discounts on brands like Pace, Herdez, and Taco Bell, indicating an aggressive discounting strategy. In contrast, brands closely associated with Mexican or Tex-Mex cuisine, such as Old El Paso, Mission, Rosarita, and La Banderita, offered relatively modest discounts ranging from 0.5% to 3.3%.

    The discount patterns varied between alcohol and food categories, with food brands generally offering higher discounts. This trend may be attributed to pricing being regulated in the alcohol industry. These differing discount levels highlight how brands navigated the balance between driving sales and maintaining profit margins during Cinco de Mayo, particularly in the context of inflation affecting costs.

    Impact of Inflation on Cinco de Mayo Prices (2024 vs 2022)

    To gauge the impact of inflation on popular Cinco de Mayo products, we analyzed the average prices at Walmart and Target between 2022 and 2024. These two retailers were chosen due to their prominence in the retail sector and the robustness of our sample data.

    At Walmart, the Tex Mex category saw the highest average price increase, rising by 22.51%. Other notable subcategories with significant price hikes include Condiments (23.21%), Vegetables/Packaged Vegetables (21.22%), and Lasagne (14.10%). Categories like Dips & Spreads (13.77%), Pantry Staples (14.92%), and Salsa & Dips (8.23%) experienced relatively lower increases.

    At Target, the Snacks subcategory had the steepest average price rise at 27.94%, followed by Meal Essentials (16.07%) and Deli Pre-Pack (8.82%). Categories such as Dairy (0.51%), Frozen Meals/Sides (7.11%), and Adult Beverages (7.41%) saw smaller price increases.

    Brands associated with traditional Mexican or Tex-Mex cuisine faced higher price hikes. Examples include Old El Paso (24.59% at Walmart, 8.70% at Target), Tostitos (35.44% at Walmart, 11.41% at Target), Ortega (30.59% at Walmart, 19.69% at Target), and Rosarita (14.39% at Walmart).

    In contrast, private label or store brands generally experienced lower price increases compared to national brands. For instance, Good & Gather (Target’s private label) saw a 9.55% increase, while Market Pantry (Walmart’s private label) had a 17.27% rise. This trend is understandable as retailers have more control over their costs with private label brands.

    The data clearly indicates that both Walmart and Target have significantly raised prices across various categories and brands, reflecting the broader inflationary environment where the cost of goods and services has been steadily climbing.

    Interestingly, we observed higher price increases at Walmart compared to Target. Although Walmart is renowned for its consumer-friendly pricing strategies, it too had to elevate grocery prices post-2022 to combat inflationary pressures. As consumers become more cost-conscious and reduce spending on discretionary items, Walmart and other retailers are now cutting prices across categories to align with shifting consumer behaviors.

    Mastering Pricing Strategies During Sale Events

    Our pricing analysis for Cinco de Mayo reveals compelling insights into the dynamics of retailer landscapes in the US. It highlights the enduring relevance of private label brands, even amidst fluctuating demand, showing the emergence of local, national, and small players vying for market share.

    As retailers navigate inflationary pressures and evolving consumer behaviors, understanding these pricing dynamics becomes crucial for optimizing strategies and bolstering market competitiveness. This analysis offers actionable intelligence for retailers seeking to navigate the intricate terrain of sale event promotions while addressing shifting consumer preferences and economic challenges.

    Access to reliable and timely pricing data equips retailers and brands with the tools needed to make informed decisions and drive profitable growth in an increasingly competitive environment. To learn more and gain guidance, reach out to us to speak to a DataWeave expert today!

  • How Monitoring and Analyzing  End-User Prices can Help Retailers and Brands Gain a Competitive Edge

    How Monitoring and Analyzing  End-User Prices can Help Retailers and Brands Gain a Competitive Edge

    Retailers and brands are constantly engaged in a fierce battle over prices and discounts. Whether it’s major events like Amazon Prime Day, brand-led sales, or everyday price wars, they depend on pricing intelligence and digital shelf analytics to fine-tune their strategies. With a variety of offers such as sales, promotions, and bundles, determining the actual cost to the customer becomes a complex task. The price set by the brand, the retailer’s offer, and the final amount paid by the customer often vary significantly.

    In their analysis, retailers and brands frequently focus on the listed price or the final sale price, overlooking a critical factor: the “end-user price.” This includes all discounts, taxes, and shipping costs, providing a more accurate picture of what customers are truly willing to pay at checkout.

    Grasping this end-user price is vital for both retailers and brands. For retailers, it helps them stay competitive and refine their promotional strategies. For brands, it offers insights into competitive positioning, net revenue management, and shaping customer price perception.

    However, emphasizing the end-user price is challenging, as it involves comprehending all the intricate elements of pricing.

    How end-user pricing is calculated

    The list price, also known as the manufacturer’s recommended retail price (MSRP), is the initial price set by the brand. This may not always be displayed on marketplaces, especially in categories like grocery. The selling price, on the other hand, is the amount at which a retailer offers the product, often reduced from the list price. The end-user price is the actual amount the customer pays at checkout, which includes taxes, promotions, and other factors that affect the final cost.

    The process involves 3 key stages:

    Step 1: Identifying and categorizing promotional offers

    The first critical step in calculating end-user pricing is to identify and categorize the various promotional offers available for a given product that can reduce the final amount paid by the consumer. These promotions span a wide range of types:

    • Bank Offers: Involving discounts or cash back incentives when paying with specific bank credit or debit cards. For instance, a customer may receive 10% cashback on their purchase by using a specific bank’s card.
    • Bundled Deals: Combining multiple products or services at a discounted bundle price. A common example is a smartphone bundle including the phone itself, a protective case, and earphones at a reduced total cost.
    • Promo Codes/Coupons: Customers can enter promo codes or coupons during checkout to unlock special discounted prices or percentage-off offers, like 20% off a hotel booking, or even a special brand discount personalized for their needs (think loyalty offers and in-app promotions).
    • Shipping Offers: These include free shipping or reduced shipping fees for certain products or orders, such as free delivery on orders above a set amount.
    • TPRs (Temporary Price Reductions): TPRs play a significant role in the strategies of most retailers. Brands and retailers use them to encourage shoppers to purchase more of a product or to try a new product they wouldn’t usually buy. A TPR involves reducing the price of a product by more than 5% from its regular shelf price.

    By accurately identifying and classifying each type of promotion available, brands can then calculate the potential end-user pricing points.

    Step 2: Accounting for location and fulfilment nuances (delivery, in-store pickup) that impact final pricing

    Product pricing and promotional offers can vary based on the consumer’s location or ZIP code. Additionally, customers may opt for different fulfilment modes like delivery, shipping, or in-store pickup, which can further impact the final cost. Accurately calculating the end-user price necessitates considering these location-based pricing nuances as well as the chosen fulfilment method.

    In the example below, the selling price is $4.32 for one retailer (on the left in the image) after a discount for online purchase. In another case with Meijer, the item total shows $17.91, but the consumer ends up paying $15.74 after taxes and fees are applied (on the right in the image).

    Step 3: Applying each eligible promotion or offer to the selling price to determine potential end-user price points

    With the various promotional offers and discounts categorized in the previous steps, retailers and brands can now apply each eligible promotion to the product’s selling price. This involves deducting percentages for bank cashback, implementing bundled pricing, applying coupon code discounts, and incorporating shipping promotions.

    For retailers, this step allows them to calculate their true effective selling price to customers after all discounts and promotions. They can then compare this end-user price against competitors to ensure they remain competitively priced.

    For brands, by systematically layering every applicable offer onto the baseline selling price, they can accurately calculate the multiple potential end-user price points a customer may pay at checkout for their products across different retailers and regions.

    Why the end-user price matters

    Optimizing pricing strategies using the end-user price can benefit retailers and brands in several ways:

    • Price Competitiveness: By monitoring end-user pricing, retailers can adjust for discounts and promotional offers to attract customers, while brands can refine their pricing models to stay ahead in the market.
    • Customer Acquisition and Loyalty: Offers, promotions, and discounts directly impact the final price paid by customers, playing a crucial role in attracting new customers and retaining existing ones. For example, Walmart’s competitive pricing in groceries boosts customer loyalty and repeat purchases.
    • Consumer Perception: End-user pricing significantly shapes how consumers perceive both retailers and brands. Competitive pricing and promotional transparency enhance reputation and conversion rates. Amazon, for instance, is known for its competitive pricing and fast deliveries, which strengthen its consumer perception and satisfaction.
    • Sales Volumes: The final checkout price influences affordability and perceived value, directly affecting sales volumes. Both retailers and brands benefit from understanding this, as it guides consumer purchasing decisions and drives revenue streams.
    • Brand Perception: Consistent and transparent pricing enhances the perception of both the retailer and the brand. This not only strengthens the value proposition but also builds consumer trust and fosters long-term loyalty.

    While the listed and selling prices are readily available, calculating the true end-user price is quite complex. It involves meticulous tracking and application of various types of promotions, offers, location-based pricing nuances, and fulfillment costs – an uphill task without robust technological solutions.

    Track and Analyze end-user prices with DataWeave

    DataWeave’s end-user price tracking capability empowers retailers and brands with the insights and tools necessary to comprehend the complexities of pricing dynamics. For retailers, it offers the ability to monitor end-user pricing across various products and categories compared to competitors, ensuring competitiveness after all discounts and enabling optimization of promotional strategies. Brands benefit from informed pricing decisions, optimized strategies across retail channels, and a strengthened position within their industries.

    Our intuitive dashboard presents classified promotions and corresponding end-user prices across retailers, providing both retailers and brands with a transparent, comprehensive view of the end-user pricing landscape.

    Within the detailed product view of DataWeave’s dashboard, the Price and Promotions panel showcases diverse promotions available across different retailers for each product, along with the potential end-user price post-promotions.

    Harness the power of DataWeave’s sophisticated Pricing Intelligence and Digital Shelf Analytics to gain an accurate, real-time understanding of your end-user pricing dynamics. Make data-driven pricing decisions that resonate with customers and propel your brand toward sustained success.

    Find out how DataWeave can empower your eCommerce pricing strategy – get in touch with us today or write to us at contact@dataweave.com!

  • Augmenting AI-powered Product Matching with Human Expertise to Achieve Unparalleled Accuracy

    Augmenting AI-powered Product Matching with Human Expertise to Achieve Unparalleled Accuracy

    In today’s expansive omnichannel commerce landscape, pricing intelligence has become indispensable for retailers seeking to stay competitive and refine their pricing strategies. The sheer magnitude of eCommerce, spanning thousands of websites, billions of SKUs, and various form factors, adds layers of complexity. Consequently, ensuring the accuracy and reliability of competitive insights presents a formidable challenge for retailers aiming to leverage pricing data effectively.

    At the core of any robust pricing intelligence system lies product matching. This process enables retailers to recognize identical or similar products across competitors. Once these matches are identified, tracking prices is a relatively more straightforward task, facilitating ongoing analysis and informed decision-making.

    Accurate matching is crucial for meaningful price comparisons and tailoring product assortments. The challenge is matching products is often complicated, especially for non-local brands, niche categories, or items lacking consistent global identifiers. It becomes even trickier when trying to match very similar but not identical products. A comprehensive approach that compares and analyzes multiple attributes like product titles, descriptions, images and more is essential.

    Artificial intelligence algorithms are commonly used to automate product matching, leveraging machine learning techniques to analyze patterns in images and text data. While AI can adapt and improve over time, the question remains: Can it fully address the complexities of product matching on its own?

    The reality is that many retailers still struggle with incomplete, inaccurate, or outdated product data, despite these AI-powered product matching solutions. This can lead to suboptimal pricing decisions, missed opportunities, and reduced competitiveness.

    Challenges in an ‘AI-only’ Approach to Product Matching

    While AI plays a vital role in automated product matching solutions, there are complexities that AI alone cannot fully address:

    Subjectivity in Matching Criteria

    Some product categories have subjective or hard-to-quantify criteria for determining similarity. AI learns from historical data, so it may struggle with nuanced aspects like:

    Aesthetics, style, and design: In the Fashion and Jewellery vertical, for example, products are matched according to attributes like style, aesthetics, design – all of which have some subjectivity involved.

    Quantity/packaging variations: In the grocery sector, variations in product packaging and quantities can introduce complexities that require subjective decision-making. For example, apples may be sold in different packaging like a 0.5 kg bag or a pack of 4 individual apples. Determining if these different packaging options should be considered equivalent often involves making a qualitative judgment call, rather than a clear-cut objective decision.

    Matching product sets: For categories like home furnishings, the focus is often on matching coordinated sets rather than individual items. For example, in the bedroom category, matching may involve grouping together an entire set of complementary furniture like a bed frame, dresser, and wardrobe based on their cohesive design and style. This goes beyond simply making one-to-one product associations, requiring more nuanced judgments about aesthetic coordination.

    Contextual Factor

    Products can have regional preferences, cultural differences, or evolving trends that impact how they are matched. AI may miss important context like Local/regional product names or distinct brand names across countries.

    For instance, in the image we see Sprite (in the US) is branded Xubei in China. Continuous human curation is needed to help AI adapt to this context.

    High Accuracy & Coverage Expectations

    Retailers rely on AI powered and automated pricing adjustments based on product matching for insight. To ensure that pricing recommendations and updates are accurate, accurate product matching is crucial. For this, simply identifying similar top results is not enough – the process must comprehensively capture all relevant matches. While AI excels at finding the top groupings with around 80% accuracy, even small matching errors can have significant consequences.

    As AI matching improves, customer expectations may rise even higher. If AI achieves 90% accuracy, for instance, SLAs may demand over 95%. Reaching such a high level of accuracy is very challenging for AI alone, especially when faced with incomplete data, contextual nuances, evolving trends, and subjective matching criteria across products and categories.

    The solution is to combine the power of AI with human expertise. This is the key to achieving true data veracity – the accuracy, freshness, and comprehensive coverage required for precise and reliable product matching.

    Human-in-the-Loop Approach for Elevated Product Matching

    Human intelligence and quality testing can elevate the AI powered product matching process by addressing key challenges:

    • Matching Validation: AI algorithms may identify product matches with 80-90% accuracy initially. Having humans validate these AI-suggested matches allows for correcting errors and pushing the accuracy close to 100%. As humans flag issues, provide context, and re-label incorrect predictions, it allows the AI model to learn and enhance its reliability for complex, high-stakes decisions.
    • Applying Contextual Judgment: For subjective matching criteria like aesthetics, design, and categorizing product sets, human discernment is needed. Humans can make nuanced judgments beyond just quantitative rules, ensuring meaningful apples-to-apples product comparisons. Their contextual understanding augments AI’s capabilities.
    • Continuous Learning Via Feedback Loop: Product experts possess rich category knowledge across markets. Integrating this human insight through an iterative feedback loop helps AI models quickly learn and adapt to changing trends, preferences, and context. As humans explain their match assessments, the AI continuously enhances its precision over time.

    By combining AI’s automation and scale with human validation, judgment, and knowledge curation, pricing intelligence solutions can achieve the accuracy and coverage demanded for actionable competitive pricing insights.

    DataWeave’s Data Veracity Framework: A Scalable Workflow Combining AI and Human Expertise

    Given the vast number of products, retailers, and brands that exist today, any product matching solution must be highly scalable. At DataWeave, we bring you such a scalable workflow to address these complexities by integrating human expertise with AI-driven automation. The image below outlines our approach for combining AI with human intelligence in a seamless, scalable workflow for accurate product matching:

    Retailers and brands can benefit in several ways with this workflow, as listed below.

    Several Rounds of Data Verification Due to Hierarchical Validation Teams

    The workflow employs a hierarchical validation team of Leads and Executives to efficiently integrate human expertise without creating bottlenecks. Verification Leads play a pivotal role in managing the distribution of product matches identified by DataWeave’s AI model to the Verification Executives.

    The Executives then meticulously validate these AI-suggested matches, adding any missing product associations and removing inaccurate matches. After validation, the matched product groups are sent back to the Leads, who perform random sampling checks to ensure quality.

    Throughout this entire workflow, feedback and suggestions are continuously gathered from both the Executives and Leads. This curated input is then incorporated back into DataWeave’s AI model, allowing it to learn and improve its matching accuracy on an ongoing basis.

    This hierarchical structure ensures that human validation seamlessly scales alongside the AI’s matching capabilities. Leveraging the respective strengths of AI automation and human expertise in an iterative feedback loop prevents operational bottlenecks while steadily elevating overall accuracy.

    Confidence-based Distribution of Matched Articles for Validation

    The AI model assigns confidence scores, differentiating high-confidence (>95%) and low-confidence matches. For high-confidence groups, executives simply remove incorrect matches – a quicker process. Low-confidence matches require more human effort in adding/removing matches.

    As the AI model improves over time with feedback, the share of high-confidence matches increases, making validation more efficient and swift.

    Automated, Standardized Process with Iterative Feedback Loop

    The entire workflow is standardized and automated, with verification metrics seamlessly tracked. At each step, feedback captured from both leads and executives flows back into the AI, enhancing its matching accuracy and coverage iteratively.

    DataWeave’s closed-loop system of AI automation with hierarchical human validation allows product matching to achieve comprehensive accuracy at a vast scale.

    Unleash the Power Accurate and Comprehensive Product Matching

    In summary, combining AI and human expertise in product matching is crucial for retailers navigating the complexities of omnichannel retail. While AI algorithms excel in automation, they often struggle with subjective criteria and contextual nuances. DataWeave’s approach integrates AI-driven automation with human validation, delivering the industry’s most accurate product matching capabilities, enabling actionable competitive pricing insights.

    To learn more, reach out to us today!

  • How Gas Stations and Convenience Stores in the U.S. Can Adapt To Evolving Fuel Pricing Trends in 2024

    How Gas Stations and Convenience Stores in the U.S. Can Adapt To Evolving Fuel Pricing Trends in 2024

    As we move into the second quarter of 2024, the US energy landscape is poised for notable shifts that will impact gasoline and diesel prices. The shift towards renewable energy sources, evolving consumer preferences, and volatile global market forces are all converging to reshape the fuel retail industry.

    For fuel retailers, understanding these projections is crucial – changes in consumer demand and cost pressures can significantly affect their bottom line. In this article, we provide insights on the factors shaping the fuel pricing environment for the remainder of the year, covering a variety of fuel types.

    Gasoline Prices: A Downward Trend Ahead

    According to the January Short-Term Energy Outlook by the EIA, US retail gasoline prices are projected to decline in 2024. Similarly, the forecast also predicts reduced gasoline consumption in 2025. This is attributed to a significant increase in inventories, thanks to expanded refinery capacity. US operable refinery capacity has grown from 18.06 million barrels per day in January 2023 to 18.31 million barrels per day by December 2023.

    Meanwhile, the World Bank reports that global trade growth in 2024-25 is expected to be only half the average in the decade before the pandemic, leading to reduced consumption and demand.

    The increase in supply, coupled with this dip in demand and consumption expected in 2025, sets the stage for further price reductions. Such expansion not only enhances supply but also alleviates price pressures for consumers.

    Diesel Dynamics: Supply Up, Prices Down

    Similar supply-side dynamics are at play in the diesel market, with retail prices expected to fall in both 2024 and 2025. Despite a forecasted uptick in US diesel consumption in these two years, an increase in production capacity and easing inventory strains are likely to keep prices in check. This is particularly noteworthy, as diesel fuel plays a critical role in transportation and logistics, underpinning the movement of goods and services nationwide.

    Crude Oil and Crack Spreads: The Refining Equation

    Crude oil prices, a pivotal factor in the fuel price equation, are expected to mirror 2023 levels through 2024.

    The anticipated decrease in gasoline and diesel prices is largely attributed to narrowing crack spreads—the differential between wholesale fuel prices and crude oil. A lower crack spread signifies reduced refining costs, a welcome development for both refiners and consumers. This expectation is grounded in the increasing availability of refinery capacity and, consequently, fuel supply, even as demand shows signs of tapering off.

    Global Influences and Economic Implications

    The outlook is further buoyed by new refinery capacities coming online internationally, particularly in the Middle East. This global increase in refined product supplies is poised to ease price pressures for consumers not just domestically but across international markets. Interestingly, this forecast comes at a time when gasoline consumption is expected to remain flat or slightly decrease, a rare occurrence in the context of positive economic growth. This decoupling of fuel consumption from economic expansion highlights evolving consumer behaviors and efficiency gains across the automotive sector.

    Looking Ahead: Uncertainties and Transformations

    While the projections offer a glimpse into a future of potentially lower fuel prices, they are not without uncertainties. Factors such as crude oil price fluctuations, refinery shutdowns, and logistical challenges could sway outcomes.

    The projected decrease in US gasoline and diesel prices presents both opportunities and challenges.

    • For American consumers, lower fuel costs offer relief for household budgets and transportation expenses, potentially freeing up disposable income and stimulating broader economic activity.
    • However, these pricing trends pose a need for strategic planning and adaptation within the US energy sector. Companies must navigate shifting supply dynamics and the ongoing transition towards renewable energy sources – a pivotal chapter in the quest for sustainable and affordable solutions.
    • Energy firms will need to carefully analyze the implications, aligning their business models through refining capacity expansions, logistical optimizations, and a focus on renewable fuels.

    Staying Ahead of Competition with Fuel Price Tracking

    In this evolving landscape, closely tracking fuel prices and having access to up-to-date data is crucial for informed decision-making and staying competitive in the market for fuel retailers. While prices may go down in the long- to medium-term, ensuring short-term price competitiveness at a hyperlocal level is essential for gas stations and convenience stores navigating the changing tides.

    DataWeave’s real-time fuel pricing data, covering a wide range of fuel types from gasoline to diesel and updated as frequently as every 30 minutes, empowers retailers to quickly adapt to market changes and remain strategically aligned with evolving consumer preferences.

    By closely monitoring hyperlocal fuel price fluctuations across their coverage areas, retailers can quickly adapt their pricing strategies to remain competitive and align with shifting consumer behaviors.

    Further, DataWeave’s real-time fuel pricing intelligence can help retailers understand the relationship between crude oil prices, crack spreads (the differential between wholesale fuel prices and crude oil), and their own pricing strategies. Our solution offers real-time insights and analytics to help retailers navigate the evolving fuel pricing landscape.

    Visit our recently launched U.S. Fuel Price Interactive Dashboard which displays weekly fuel prices across 400+ unique ZIP codes, delivering insights into price changes by region, store, fuel type, and other dimensions.

    To learn more about DataWeave’s solutions or to discuss how we can support your fuel retail business, reach out to our team today!

  • Why Localized, Store-Specific Pricing and Availability Insights is Critical for Consumer Brands

    Why Localized, Store-Specific Pricing and Availability Insights is Critical for Consumer Brands

    Brands are becoming increasingly proficient in monitoring and refining their presence on online marketplaces, utilizing Digital Shelf Analytics to gather and analyze data on their online performance. These tools offer invaluable insights into enhancing visibility, adjusting pricing strategies, and improving content quality on eCommerce sites.

    Yet, as the retail landscape shifts towards a more integrated omnichannel approach, it’s crucial for brands, particularly those in CPG, to apply similar strategies to their offline channels. For brands that count physical stores among their primary sales channels, gaining localized insights is key to boosting in-store sales performance.

    Collecting shelf data from offline channels presents more challenges than online. Traditional methods, such as physical store visits, often fall short in reliability, timeliness, scale, and level of coverage.

    However, the world of eCommerce provides a solution. As part of the effort to facilitate options like buy-online-pickup-in-store (BOPIS) for shoppers, major retailers make store-specific product details available online. Consumers often go online and select their nearest store to make purchases digitally before choosing a fulfillment option like picking up at the store or direct delivery. Aggregating this store-level information offers brands critical insights into pricing and inventory across a vast network of stores, enabling them to make informed decisions that improve pricing strategies and supply chain efficiency, thus minimizing stockouts in crucial markets.

    Further, as consumers increasingly seek flexibility in how they receive their purchases—be it through in-store pickup, delivery, or shipping—brands need to adeptly monitor pricing and availability for these different fulfilment options. Such granular insight empowers brands to adapt swiftly and maintain a competitive edge in today’s dynamic retail environment.

    Why does monitoring pricing and availability data across stores matter to brands?

    • Hyperlocal Competitive Strategy: This allows brands to adjust their pricing strategies based on regional competition. By understanding the local market, brands can decide whether to position themselves as cost leaders or premium offerings. In particular, this is indispensable for Net Revenue Management (NRM) teams.
    • Targeted Marketing Initiatives: Understanding regional price and availability enables brands to customize their marketing efforts for specific markets. By aligning their strategies with local demand trends and inventory levels, brands can more effectively engage their target audiences.
    • Efficient Inventory Management: By keeping a close eye on store-level data, brands can better manage their stock, ensuring high-demand products are readily available while minimizing the risk of overstocking or running out of stock.
    • Minimum Advertised Price (MAP) Monitoring: While brands cannot directly control retail pricing, staying updated on pricing trends helps them adjust their MAP to reflect the competitive landscape, consumer expectations, cost considerations, and regional differences. A strategic approach to MAP management supports brand competitiveness and profitability in a fluctuating market.

    DataWeave’s Digital Shelf Analytics solutions equip brands with the necessary data and insights to do all of the above.

    DataWeave’s Digital Shelf Analytics is location-aware

    DataWeave’s Digital Shelf Analytics platform stands out with its sophisticated location-aware capabilities, enabling the aggregation and analysis of localized pricing, promotions, and availability data. Our platform defines locations using a range of identifiers, including latitudes and longitudes, ZIP codes, or specific stores, and can aggregate this data for particular states or regions.

    The strength of the platform lies in its robust data collection and processing framework, which operates seamlessly across thousands of stores and regions. This system is designed to operate at configurable intervals—daily, weekly, or monthly—allowing brands to keep a vigilant eye on product availability, pricing strategies, and delivery timelines based on the selected fulfillment option.

    Unlike many other providers, who may provide limited insights from a sample of stores, our solution delivers exhaustive analytics from every storefront. This comprehensive approach grants brands a strategic edge, facilitating efficient inventory tracking, precise pricing adjustments, and rapid responses to fluctuating market dynamics. It cultivates brand consistency and loyalty by enabling brands to adapt proactively to the changing landscape.

    Aggregated store-level digital shelf insights via DataWeave

    In the summarized view shown above, a brand can track how its various products are positioned across stores and retailers like Walmart, Amazon, Meijer, and others in the US.

    Using DataWeave, brands can easily see important metrics like availability levels, prices, and other metrics across these stores gaining immediate visibility without having to physically audit them. the brand can track the same metrics for products across competitor brands and inform its own pricing, stock, and assortment decisions.

    Store-level availability insights

    We provide a comprehensive view of product availability, highlighting the distribution of out-of-stock (OOS) scenarios across various retailers and pinpointing the availability status throughout a brand’s network of stores. This capability enables swift identification of widespread availability issues, offering a bird’s-eye view of where shortages are most pronounced. By simply hovering over a specific location, detailed information about stock status and pricing for individual stores becomes accessible.

    Such insights are crucial for brands to adapt their strategies, mitigate risks, and ensure they meet consumer needs despite the ever-changing retail ecosystem.

    Store-level pricing insights

    Retailers often adopt different pricing strategies to deal with margin pressure, local competition, and surplus stock. Grasping these pricing dynamics at a hyperlocal level enables brands to tailor their strategies effectively to maintain a competitive edge.

    Our platform offers an in-depth look at how prices vary among retailers, across different stores, and throughout various regions. This analysis reveals the nuanced pricing tactics employed by retailers on a regional scale.

    For example, brands might see that some retailers, like Kroger and Walmart in the chart below, maintain consistent pricing across their outlets, demonstrating a uniform pricing strategy. In contrast, others, such as Meijer and Shoprite, might adjust their prices to match local market conditions, indicating a more localized approach to pricing.

    With DataWeave, brands can dive deeper into the pricing landscape of a specific retailer, examining a price map that provides detailed information on pricing at the store level upon hovering over a given location.

    By presenting a historical analysis of average selling prices across different retailers, we equip brands with the insights needed to understand past pricing strategies and anticipate future trends, helping them to strategize more effectively in an ever-evolving market.

    Digital Shelf Analytics that work for both eCommerce and brick-and-mortar store data

    While established brands have made strides in gathering online pricing and availability data through Digital Shelf Analytics solutions, integrating comprehensive insights from both brick-and-mortar and eCommerce channels often remains a challenge.

    DataWeave stands out for its capacity to collect data across diverse digital platforms, including desktop sites, mobile sites, and mobile applications. This capability ensures that omnichannel brands can have a holistic view of their pricing, promotional, and inventory strategies across all locations and digital landscapes.

    Leveraging localized Digital Shelf Analytics to understand the intricacies of pricing and availability at the store level allows brands to fine-tune their approaches, swiftly adapt to local market shifts, and uphold a unified brand presence across the digital and offline spheres. This strategic agility places them in a favorable competitive position, enhancing customer satisfaction and trust, which are crucial for sustained success.

    Know more about DataWeave’s Digital Shelf Analytics here.

    Schedule a call with a specialist to see how it can work for your brand.

  • Easter Candy Pricing Trends 2024: Winning Strategies for Retailers and Brands Amid Cocoa Price Surge

    Easter Candy Pricing Trends 2024: Winning Strategies for Retailers and Brands Amid Cocoa Price Surge

    Easter egg hunts just got more challenging for families this year as the price of chocolate and other candies has soared. The root of this price surge lies in a cocoa deficit, attributed to diseases affecting crops and the adverse effects of climate change on West African farms, which supplies over 70% of the world’s cocoa. This has resulted in a tripling of cocoa prices over the last year, causing a “cocoa crunch,” and severely impacted confectioners and chocolate makers.

    Reuters recently reported that Iconic brands such as Hershey’s and Cadbury find themselves grappling with the need to adjust to escalating costs for raw materials. Given that Easter is one of the top three candy-purchasing occasions, these manufacturers are contemplating raising their prices to sustain their profit margins.

    Despite the challenges posed by the cocoa shortfall and persistent inflation, the National Confectioners Association anticipates that Easter candy sales in the U.S. will match or even exceed last year’s figures, which amounted to approximately $5.4 billion. This expectation is predicated more on price increases than on a rise in sales volume.

    At DataWeave, our ongoing analysis of pricing trends across various consumer categories among retailers has provided insight into the evolving landscape of chocolate and candy prices in 2023 and 2024.

    Our Analysis of Inflation in Candy and Chocolate Prices

    Our study encompassed a broad array of 3,300 products from leading U.S. retailers, Amazon, Target, Kroger, and Giant Eagle. As illustrated in the following chart, the trajectory of prices over the past 15 months was compared against the average prices in January 2023. Our tracking focused on two key price points: the selling price, which represents the final cost to consumers after applying any discounts or promotions, and the Manufacturer’s Suggested Retail Price (MSRP), as determined by the brands themselves.

    The findings from our analysis indicate that the average selling price, primarily influenced by retailer decisions, has experienced a steady increase throughout 2023, reaching a peak at 16.2% above January 2023’s figures by December. As of March 2024, coinciding with the Easter season, the selling prices are approximately 10% higher than they were at the beginning of the previous year.

    Simultaneously, the MSRP has seen a consistent uptick, driven by the climbing costs of cocoa. Brands have adjusted their suggested prices accordingly, with the current MSRP standing about 7% above its January 2023 level, after having peaked at a 7.6% increase by December 2023. This reflects the direct impact of rising cocoa costs on product pricing strategies.

    Chocolate Candies Are Hit The Hardest

    Across all candies, chocolate-based products have witnessed significantly sharper price increases than their non-chocolate counterparts. In the past 14 months, the selling prices of chocolate items have surged by 14.9%, a stark contrast to the modest 4% rise observed in non-chocolate candies.

    This price escalation was particularly pronounced during the Christmas shopping period, a response to heightened demand, before experiencing a temporary decline in February.

    The diminishing availability of cocoa, coupled with rising costs for packaging and transportation, has compelled brands and retailers alike to transfer these added expenses onto the consumer. This dynamic underpins the distinct pricing trends observed across the candy spectrum, with chocolate items bearing the brunt of these cost pressures.

    Discounts Offered By Retailers and Brands to Entice Easter Shoppers

    In our analysis, we delved deeper to identify the retailers and brands offering the most compelling prices for Easter-centric confections, including Chocolate Eggs, Chocolate Bunnies, and Easter-themed gift packs.

    Kroger emerged as the frontrunner among the retailers we monitored, offering an impressive 19% discount on Easter candies. Giant Eagle followed with a solid 14% average markdown. Meanwhile, Amazon and Target provided more modest promotional discounts at 12% and 10%, respectively.

    Kroger is making significant efforts to ensure consumers have access to attractively priced Easter treats. The retailer planned to keep its doors open throughout the Easter weekend, featuring baskets brimming with discounted items such as Russell Stover chocolate bunnies, Brach’s jelly beans, Reese’s eggs, and assorted bags of popular candies from Snickers, Twix, and Starburst, among others. Additionally, Kroger is enhancing its value proposition through gift card offers and exclusive Easter deals for its loyalty program members.

    On the brand front, Starburst by Mars Wrigley leads with the steepest discount of 25%. Cadbury, under Mondelez, is not far behind, offering 21% off its mini eggs and other Easter treats, marking an increase from last year’s 17% discount. Ferrero Rocher is making a strong pricing move with an average 20% markdown on its Easter selections, including the chocolate bunny and squirrel figures.

    The beloved Peeps marshmallow candies by Just Born are being offered at an 18% discount this year, slightly less than the 23% discount seen in 2023, likely reflecting the impact of rising sugar costs, given their sugar and corn composition.

    Other notable brands, including M&M’s and the premium Swiss chocolatier Lindt, have elevated their average Easter discounts to 17% this year, up from the previous year’s discounts of 12%, and 10% respectively, showcasing a competitive pricing strategy to delight consumers this Easter season.

    Coping With Inflation This Easter Season

    Retailers and brands aiming to remain profitable and competitive in the current challenging environment can adopt a few strategic approaches:

    • Creative Product Bundling: Design innovative combo packs that mix chocolate and non-chocolate items. Such bundles can cater to diverse consumer preferences and budget ranges while preserving profit margins.
    • Encouragement of Bulk Purchases: Offer enticing discounts on larger quantities to promote bulk buying. This strategy can help amplify sales volumes, compensating for increased costs per item and fostering economies of scale.
    • Strategic Competitive Pricing: Keeping a vigilant eye on competitors’ pricing strategies is vital. Aim to capture market share through well-thought-out discount strategies that balance competitiveness with margin preservation. Leveraging advanced pricing intelligence, such as that offered by DataWeave, can provide invaluable insights for making informed pricing decisions.
    • Product Size Adjustments: Consider revising the size or weight of products as a cost management measure, a strategy known as “shrinkflation.” It’s crucial to approach this transparently, ensuring clear communication on packaging to uphold consumer trust.

    Adopting these strategies—focusing on bundle offerings, incentivizing bulk purchases, optimizing pricing strategies based on competitive intelligence, and thoughtfully adjusting product sizes—will be pivotal for confectioners to navigate the challenges posed by the cocoa price surge.

    For more information, reach out to us to speak to a DataWeave expert today!


  • How AI-Powered Visual Highlighting Helps Brands Achieve Product Consistency Across eCommerce

    How AI-Powered Visual Highlighting Helps Brands Achieve Product Consistency Across eCommerce

    As eCommerce increasingly becomes a prolific channel of sales for consumer brands, they find that maintaining a consistent and trustworthy brand image is a constant struggle. In an ecosystem filled with dozens of marketplaces and hundreds of third-party merchants, ensuring that customers see what aligns with a brand’s intended image is quite tricky. With many fakes and counterfeit products doing the rounds, brands may further struggle to get the right representation.

    One way brands can track and identify inconsistencies in their brand representation across marketplaces is to use Digital Shelf Analytics solutions like DataWeave’s – specifically the Content Audit module.

    This solution uses advanced AI models to identify image similarities and dissimilarities compared with the original brand image. Brands could then use their PIM platform or work with the retailer to replace inaccurate images.

    But here’s the catch – AI can’t always accurately predict all the differences. Relying solely on scores given by these models poses a challenge in tracking the subtle differences between images. Often, image pairs with seemingly high match scores fail to catch important distinctions. Fake or counterfeit products and variations that slip past the AI’s scrutiny can lead to significant inaccuracies. Ultimately, it puts the reliability of the insights that brands depend on for crucial decisions at risk, impacting both top and bottom lines.

    Dealing with this challenge means finding a balance between the number-based assessments of AI models and the human touch needed for accurate decision-making. However, giving auditors the ability to pinpoint variations precisely goes beyond simply sharing numerical values of the match scores with them. Visualizing model-generated scores is important as it provides human auditors with a tangible and intuitive understanding of the differences between two images. While numerical scores are comparable in the relative sense, they lack specificity. Visual interpretation empowers auditors to identify precisely where variations occur, aiding in efficient decision-making.

    How AI-Powered Image Scoring Works

    At DataWeave, our approach involves employing sophisticated computer vision models to conduct extensive image comparisons. Convolutional Neural Network (CNN) models such as Resnet-50 or YOLO, in conjunction with feature extraction models, analyze images quantitatively. This AI-powered image scoring process yields scores that indicate the level of similarity between images.

    However, interpreting these scores and understanding the specific areas of difference can be challenging for human auditors. While computer vision models excel at processing vast amounts of data quickly, translating their output into actionable insights can be a stumbling block. A numerical score may not immediately convey the nature or extent of the differences between images

    In the assessment of these images, all fall within the 70 to 80 range of scores (out of a maximum of 100). However, discerning the nature of differences—whether they are apparent or subtle—poses a challenge for the AI models and human auditors. For example, there are differences in the placement or type of images in the packaging, as well as packing text that are often in an extremely small font size. It is, of course, possible for human auditors to identify the differences in these images, but it’s a slow, error-prone, and tiring process, especially when auditors often have to check hundreds of image pairs each day.

    So how do we ensure that we identify differences in images accurately? The answer lies in the process of visual highlighting.

    How Visual Highlighting Works

    Visual highlighting is a method that enhances our ability to comprehend differences in images by combining sophisticated algorithms with human understanding. Instead of relying solely on numerical scores, this approach introduces a visual layer, resembling a heatmap, guiding human auditors to specific areas where discrepancies are present.

    Consider the scenario depicted in the images above: a computer vision model assigns a score of 70-85 for these images. While this score suggests relatively high similarity, it fails to uncover major differences between the images. Visual highlighting comes into play to overcome this limitation, precisely indicating regions where even subtle differences are seen.

    Visual highlighting entails overlaying compared images and emphasizing areas of difference, achieved through techniques like color coding, outlining, or shading specific regions. The significance of the difference in a particular area determines the intensity of the visual highlight.

    For instance, if there’s a change in the product’s color or a discrepancy in the packaging, these variations will be visually emphasized. This not only streamlines the auditing process but also enables human evaluators to make well-informed decisions quickly.

    Benefits of Visual Highlighting

    • Intuitive Understanding: Visual highlighting offers an intuitive method for interpreting and acting upon the outcomes of computer vision models. Instead of delving into numerical scores, auditors can concentrate on the highlighted areas, enhancing the efficiency and accuracy of the decision-making process.
    • Accelerated Auditing: By bringing attention to specific regions of concern, visual highlighting speeds up the auditing process. Human evaluators can swiftly identify and address discrepancies without the need for exhaustive image analysis.
    • Seamless Communication: Visual highlighting promotes clearer communication between automated systems and human auditors. Serving as a visual guide, it enhances collaboration, ensuring that the subtleties captured by computer vision models are effectively conveyed.

    The Way Forward

    As technology continues to evolve, the integration of visual highlighting methodologies is likely to become more sophisticated. Artificial intelligence and machine learning algorithms may play an even more prominent role in not only detecting differences but also in refining the visual highlighting process.

    The collaboration between human auditors and AI ensures a comprehensive approach to maintaining brand integrity in the ever-expanding digital marketplace. By visually highlighting differences in images, brands can safeguard their visual identity, foster consumer trust, and deliver a consistent and reliable online shopping experience. In the intricate dance between technology and human intuition, visual highlighting emerges as a powerful tool, paving the way for brands to uphold their image with precision and efficiency.

    To learn more, reach out to us today!


    (This article was co-authored by Apurva Naik)

  • Capturing and Analyzing Retail Mobile App Data for Digital Shelf Analytics: Are Brands Missing Out?

    Capturing and Analyzing Retail Mobile App Data for Digital Shelf Analytics: Are Brands Missing Out?

    Consumer brands around the world increasingly recognize the vital role of tracking and optimizing their digital shelf KPIs, such as Content Quality, Share of Search, Availability, etc. These metrics play a crucial role in boosting eCommerce sales and securing a larger online market share. With the escalating requirements of brands, the sophistication of top Digital Shelf Analytics providers is also on the rise. Consequently, the adoption of digital shelf solutions has become an essential prerequisite for today’s leading brands.

    As brands and vendors continue to delve further and deeper into the world of Digital Shelf Analytics, a significant and often overlooked aspect is the analysis of digital shelf data on mobile apps. The ability of solution providers to effectively track and analyze this mobile-specific data is crucial.

    Why is this emphasis on mobile apps important?

    Today, the battle for consumer attention unfolds not only on desktop web platforms but also within the palm of our hands – on mobile devices. As highlighted in a recent Insider Intelligence report, customers will buy more on mobile, exceeding 4 in 10 retail eCommerce dollars for the first time.

    Moreover, thanks to the growth of delivery intermediaries like Instacart, DoorDash, Uber Eats, etc., shopping on mobile apps has received a tremendous organic boost. According to an eMarketer report, US grocery delivery intermediary sales are expected to reach $68.2 billion in 2025, from only $8.8 billion in 2019.

    In essence, mobile is increasingly gaining share as the form factor of choice for consumers, especially in CPG. In fact, one of our customers, a leading multinational CPG company, revealed to us that it sees up to 70% of its online sales come through mobile apps. That’s a staggering number!

    The surge in app usage reflects a fundamental change in consumer behavior, emphasizing the need for brands to adapt their digital shelf strategies accordingly.

    Why Brands Need To Look at Apps and Desktop Data Differently

    Conventionally, brands that leverage digital shelf analytics rely on data harnessed from desktop sites of online marketplaces. This is because capturing data reliably and accurately from mobile apps is inherently complex. Data aggregation systems designed to scrape data from web applications cannot easily be repurposed to capture data on mobile apps. It requires dedicated effort and exceptional tech prowess to pull off in a meaningful and consistent way.

    In reality, it is extremely important for brands to track and optimize their mobile digital shelf. Several digital shelf metrics vary significantly between desktop sites and mobile apps. These differences are natural outcomes of differences in user behavior between the two form factors.

    One of these metrics that has a huge impact on a brand’s performance on retail mobile apps is their search discoverability. Ecommerce teams are well aware of the adverse impact of the loss of even a few ranks on search results.

    Anyone can easily test this. Searching something as simple as “running shoes” on the Amazon website and doing the same on its mobile app shows at least a few differences in product listings among the top 20-25 ranks. There are other variances too, such as the number of sponsored listings at the top, as well as the products being sponsored. These variations often result in significant differences in a brand’s Share of Search between desktop and mobile.

    Share of Search is the share of a brand’s products among the top 20 ranked products in a category or subcategory, providing insight into a brand’s visibility on online marketplaces.

    Picture a scenario in which a brand heavily depends on desktop digital shelf data, confidently assuming it holds a robust Share of Search based on reports from its Digital Shelf Analytics partner. However, unbeknownst to the team, the Share of Search on mobile is notably lower, causing a detrimental effect on sales.

    To fully understand the scale of these differences, we decided to run a small experiment using our proprietary data analysis and aggregation platform. We restricted our analysis to just Amazon.com and Amazon’s mobile app. However, we did cover over 13,000 SKUs across several shopping categories to ensure the sample size is strong.

    Below, we provide details of our key findings.

    Share of Search on The Digital Shelf – App Versus Desktop

    Our analysis focused on three popular consumer categories – Electronics, CPG, and Health & Beauty.

    In the electronics category, brands like Apple, Motorola, and Samsung, known for their mobile phones, earbuds, headphones, and more, have a higher Share of Search on the Amazon mobile app compared to the desktop.

    Meanwhile, Laptop brands like Dell, Acer, and Lenovo, as well as other leading brands like Google have a higher Share of Search on the desktop site compared to the app. This is the scenario that brands need to be careful about. When their Share of Search on mobile apps is lower, they might miss the chance to take corrective measures since they lack the necessary data from their provider.

    In the CPG category, Ramen brand Samyang, with a lot of popularity on Tiktok and Instagram, shows a higher Share of Search on Amazon’s mobile app. Speciality brands like 365 By Whole Foods, pasta and Italian food brands La Moderna, Divinia, and Bauducco too have a significantly higher Share of Search on the app.

    Cheese and dessert brands like Happy Belly, Atlanta Cheesecake Company, among others, have a lower Share of Search on the mobile app. Ramen brand Sapporo is also more easily discovered on Amazon’s desktop site. Here, we see a difference of more than 5% in the Share of Search of some brands, which is likely to have a huge impact on the brand’s mobile eCommerce sales levels and overall performance.

    Lastly, in the Health & Beauty category, Shampoos and hair care brands like Olaplex, Dove, and Tresemme exhibited a higher Share of Search on the mobile app compared to the desktop.

    On the other hand, body care brands like Neutrogena and Hawaiian Tropic, as well as Beardcare brand Viking Revolution displayed a higher Share of Search on Amazon’s desktop site.

    Based on our data, it is clear that there are several examples of brands that do better in either one of Amazon’s desktop sites or mobile apps. In many cases, the difference is stark.

    So What Must Brands Do?

    Our findings emphasize the imperative for brands to move beyond a one-size-fits-all approach to digital shelf analytics. The striking variations in Share of Search between mobile apps and desktops conclusively demonstrate that relying solely on desktop data for digital shelf optimization is inadequate.

    If brands see that they’re falling behind on the mobile digital shelf, there are a few things they can do to help boost their performance:

    • If a brand’s Share of Search is lower on the mobile app, they can divert their retail spend to mobile in order to inorganically compensate for this difference. This way, any short-term impact due to lower discoverability is mitigated. This is also likely to result in optimized budget allocation and ROAS.
    • Brands also need to ensure their content is optimized for the mobile form factor, with images that are easy to view on smaller screens, and tailored product titles that are shorter than on desktops, highlighting the most important product attributes from the consumer’s perspective. Not only will this help brands gain more clicks from mobile shoppers, but this will also gradually lead to a boost in their organic Share of Search on mobile.
    • CPG brands, specifically, need to optimize their digital shelf for delivery intermediary apps (along with marketplaces). The grocery delivery ecosystem is booming with companies like DoorDash, Delivery Hero, Uber Eats, Swiggy, etc. leading the way. Using Digital Shelf Analytics to optimize performance on delivery apps is quite an involved process with a lot of bells and whistles to consider. Read our recently published whitepaper that specifically details how brands can successfully boost their visibility and conversions on delivery apps.

    But first, brands need to identify and work with a Digital Shelf Analytics partner that is able to capture and analyze mobile app data, enabling tailored optimization approaches for all eCommerce platforms.

    DataWeave leads the way here, providing the world’s most comprehensive and sophisticated digital shelf analytics solution, rising above all other providers to provide digital shelf insights for both web applications and mobile apps. Our data aggregation platform successfully navigates the intricacies of capturing public data accurately and reliably from mobile apps, thereby delivering a comprehensive cross-device view of digital shelf KPIs to our brand customers.

    So reach out to us today to find out more about our digital shelf solutions for mobile apps!

  • The Indian E-Commerce Showdown: Unveiling the Price War Between Flipkart’s Big Billion Days and Amazon’s Great Indian Festival

    The Indian E-Commerce Showdown: Unveiling the Price War Between Flipkart’s Big Billion Days and Amazon’s Great Indian Festival

    India’s homegrown eCommerce giant Flipkart, now backed by Walmart, reported a record 1.4 Billion customer visits during the early access phase and throughout the seven days of its premier shopping event, the Big Billion Days, launched on 8th October 2023. Competing with Flipkart, Amazon’s Great Indian Festival sale event started on October 8th as well and saw a whopping 95 Million customer visits to the website within the first 48 hours of the event.

    For consumers, the most pressing question was, “Who offered more attractive deals and lower prices during these sale events?”

    To answer this question, we leveraged our proprietary data aggregation and analysis platform and analyzed the prices and discounts on Amazon and Flipkart across key product categories..

    The details of our sample are mentioned below:

    • Number of SKUs Analyzed: 30,000+
    • Websites: Amazon.com and Flipkart.com
    • Categories: Apparel, Home & Furniture, Electronics, Health & Beauty
    • Dates: 7th Oct 2023 to 22nd Oct 2023

    Key Findings

    Based on our analysis, the Big Billion Days by Flipkart showcased relatively higher price reductions across categories compared to the Great Indian Festival sale by Amazon. The Apparel category on Flipkart saw the highest average discount at 50.6%. The Health & Beauty category had the lowest discount across Flipkart at 39.4% and Amazon at 33%.

    Overall, Flipkart offered higher discounts in each product category. It is clear that the retailer invested heavily in leveraging its supplier partnerships with key brands or sellers to enable them to offer higher discounts, thereby attracting more customers.

    Next, let’s take a closer look at each product category.

    Apparel

    While a majority of retailers expected demand for apparel and clothing to dip this festive season in India, eCommerce giants like Amazon and Flipkart are likely to recognize the strong consumer inclination towards apparel during this period.

    In the detailed assessment of Apparel sub-categories, Women’s Dresses, Women’s Tops, Men’s Shirts, Men’s Shoes, and Women’s Innerwear emerged as the segments showcasing the most substantial discounts during the sale events. While Flipkart offered higher average discounts across all sub-categories, Amazon offered competitive discounts as well.

    We observed significant differences in the average discounts across brands between Flipkart’s Big Billion Days and Amazon’s Great Indian Festival. Reinforcing the significant discounts on the Shoes subcategory, brands like Red Tape, Arrow, Adidas, Reebok, Nike, and more offered extensive discounts on both Flipkart and Amazon. Notably, Adidas and Reebok offered better deals on Amazon’s Great Indian Festival as compared to Flipkart.

    One8 by Virat Kohli had a significantly lower discount on Amazon compared to Flipkart, indicating an exclusive partnership.

    For brands, however, reducing prices is just one approach to entice shoppers. They must also guarantee their prominent presence and easy discoverability within Amazon and Flipkart search results. To gain insight into this, we monitored brands’ Share of Search across various frequently used search terms in addition to the discounts they provided. The Share of Search denotes the portion of a brand’s products within the top 20 search results for a specific search query.

    Our data indicates that Jockey and Speedo gained in Share of Search on Flipkart, but reduced discoverability on Amazon. Van Heusen fell behind in search results on Flipkart but showed a higher Share of Search on Amazon.

    Home & Furniture

    With demand for home and furniture products picking up in October, right before the festive season, Amazon and Flipkart offered significant discounts in this category.

    Discounts on both Amazon and Flipkart hovered around 50%. Across a few subcategories, Flipkart offered slightly lower discounts compared to Amazon. Only Luggage, Rugs, Sofas, and Entertainment Units saw lower markdowns on Flipkart during the Big Billion Days. 

    Dishwashers and Washer/ Dryers saw higher discounts on Amazon compared to Flipkart. The significant discounts on these products on Amazon possibly point to changing consumer preferences, as demand for these products is traditionally low in India, but seems to be growing.

    When it comes to Home & Furniture brands, Nasher Miles, Safari, Aristocrat, VIP, and American Tourister, luggage brands mostly, offered higher discounts on Flipkart, followed closely by Amazon.

    In terms of Share of Search, Skybags had high discoverability on both Flipkart and Amazon. The brand leveraged a strategy of offering big discounts this festive season as well as ensuring prominent placement in search results. Wildcraft lost out on its discoverability on Flipkart in contrast to its prominence on Amazon. Duroflex saw lower searchability on Amazon compared to Flipkart’s Big Billion Days.

    Consumer Electronics

    The Consumer Electronics and Appliances Manufacturers Association (CEAMA) expected an uptick in sales of consumer electronics products this festive season in India. With more consumers buying premium products using credit cards and EMIs, demand for expensive, high-end electronics was expected to increase.

    Again, average discounts in this category hovered around 50% on Flipkart and Amazon.

    Across electronics subcategories, Smartwatches, Earbuds, and Drones had the highest markdowns with Flipkart leading the pack during the Big Billion Days. Amazon offered relatively higher discounts at 44.9% on the TV subcategory, compared to Flipkart’s 40.6%.

    Speakers, Laptops, Smartphones, and Tablets also saw lower markdowns on Amazon compared to Flipkart. Amazon was the official partner for the launch of many high-level smartphones and products in September-October, contributing to the higher markdowns in the subcategory.

    Across brands, Lenovo’s discounts were the most differentiated between the two sites, with the brand offering higher discounts on Amazon (45.4%) compared to Flipkart (24.7%). Noise offered the highest discounts at 72.5% on Amazon and 52.8% on Flipkart. Brands like Boat and Zebronics, also saw lower discounts on Flipkart.

    Mi and JBL offered deeper discounts on Flipkart’s Big Billion Days. Apple meanwhile stands out with only 11.83% discounts on Amazon, but the brand offered impressive 31.4% discounts on Flipkart.

    Samsung dominated the Share of Search on Amazon at 15.7%, compared to only 2.6% on Flipkart. Apple and Lenovo also saw higher discoverability on Amazon. On Flipkart, JBL and Skullcandy stand out as brands with high search visibility.

    Health & Beauty

    The Health & Beauty category saw the lowest markdowns with only 39.4% discounts on Flipkart and 33% on Amazon.

    In the subcategories analyzed, Electric Toothbrushes had relatively high markdowns across both sites. Staple and lower priced subcategories like Toothpaste had the lowest markdowns across both sale events, with Amazon offering only 17.4% average discounts.

    Across brands, Beardo, a leading beard care brand, offered significantly higher discounts on Amazon compared to Flipkart. Most other well-known brands, including Nivea and Vaseline, saw higher discounts on Amazon compared to Flipkart. Only Tresmme and Dove were exceptions with higher discounts on Flipkart.

    In terms of Share of Search, once again, Beardo was the most discoverable brand in this category. Brands like Dove, Pond’s, Swiss Beauty, and Tresemme saw a lower Share of Search on Flipkart compared to Amazon.

    Navigating the Competitive Landscape: How To Thrive During Sale Events

    Amazon and Flipkart’s strategic pricing during the Big Billion Days and the Great Indian Festival Sale reflects a balance of profitability, inventory, and competition. Competitive pricing insights empower retailers to make informed decisions, optimize strategies, and thrive during high-stakes sale events with timely and relevant insights at a massive scale.

    To learn more about how you can leverage competitive pricing insights to stay ahead of the game during sale events, reach out to us today!

  • Black Friday Cyber Monday 2023: Unveiling Health & Beauty Pricing and Discount Trends

    Black Friday Cyber Monday 2023: Unveiling Health & Beauty Pricing and Discount Trends

    On Black Friday this year, Health & Beauty brands saw a significant increase with a 13% jump in foot traffic, according to a report by RetailNext. Despite caution from various sources, higher prices for everyday goods, and high interest rates, consumers chose to spend big this cyber week.

    So what kind of deals did top retailers and brands offer in the Health & Beauty category this BFCM? At DataWeave, we harnessed the power of our proprietary data aggregation and analysis platform to track and analyze the prices and deals of Health & Beauty products across prominent retailers to uncover unique insights into their price competitiveness this BFCM, as well as understand how pricing strategies varied across diverse subcategories and brands.

    Also check out our insights on discounts and pricing for Consumer Electronics, Apparel, and Home & Furniture categories this Black Friday and Cyber Monday.

    Our Methodology

    For this analysis, we tracked the average discounts among leading US retailers in the Health & Beauty category during the Thanksgiving weekend sale, including Black Friday and Cyber Monday. We noticed prices and discounts didn’t change significantly over the course of the weekend, and hence the average prices of products between the 24th and 27th of November are being reported. Our sample was chosen to encompass the top 500 ranked products in each product subcategory across leading retailers during the sale.

    • Sample size: 15,253 SKUs
    • Retailers tracked: Amazon, Walmart, Target, Sephora, Ulta Beauty
    • Subcategories reported on: Shampoo, Toothpaste, Conditioner, Sunscreen, Makeup, Electric Toothbrush, Beard Care, Moisturizer
    • Timeline of analysis: 24 to 27 November 2023

    Our Key Findings

    Average Discounts Across Retailers

    Amazon leads the pack with a huge margin, offering an average discount of 31.9%, covering 62% of its products analyzed. Target follows an 18.8% average discount across only 5% of its analyzed assortment. The other retailers aren’t even close.

    Ulta Beauty was the next in line, providing a 9.2% average discount followed by Walmart with a 6.8% average discount. Sephora, known for its premium beauty offerings, adopted a more conservative approach with a 3.5% average discount, targeting only 9% of its top products

    Across retailers, it is clear that Amazon led the charge by far this cyber week, with the other retailers choosing to markdown prices conservatively in the Health & Beauty category.

    Average Discounts: Subcategories

    Amazon offered high discounts on lower priced subcategories like Toothpaste (49.4%), Sunscreen (46.3%), Moisturizers (38.5%), and Conditioners (37.5%), highlighting its focus on products with high demand that consumers would look to stock up on. Ulta Beauty also focused its discounts on Toothpaste (15.6%), Moisturizers (14.9%), and Conditioners (12.6%), targeting skincare and grooming.

    Sephora, meanwhile, offered the most attractive deals on the Makeup subcategory at 5.3% across 12.67% of its analyzed assortment, banking on the demand generated due to the brand’s popularity in this subcategory.

    Target prioritized discounts on Toothpaste (22.5%), Shampoo (21.6%), and Moisturizers (18.9%). Walmart too offered significant discounts on Shampoo (21.6%) and Toothpaste (22.5%).

    Retailers prioritized staple subcategories like Toothpaste and Moisturizer with substantial discounts during this Black Friday Cyber Monday, ensuring a broad consumer appeal. In contrast, discretionary items like Makeup may be less motivated by discounts alone, and hence saw lower discounts during the sale.

    Average Discounts: Brands

    Brands offered the most attractive deals on Amazon, with OGX leading the pack at 58.4% average discount. Neutrogena and Colgate followed with an average discount of 50.4% and 44%. This mirror’s Amazon’s subcategory focus on shampoos, conditioners, and toothpastes.

    Other instances of brands offering attractive deals across retailers include Belif (27.9%) and Anastasia Beverly Hills (17.6%) on Sephora, Johnson’s (20%) and Philips Sonicare (18.8%) on Target, and Olay (12.2%) and Colgate (10.6%) on Walmart.

    Ulta Beauty hosted several attractive deals by specific brands, including Moon (30.7%), Joico (24%), and Clinique (22.3%).

    Share of Search For Health & Beauty Brands Across Subcategories

    Our Share of Search analysis illuminates the strategic moves made by brands to enhance their visibility, playing a crucial role in influencing consumer choices during Black Friday and Cyber Monday.

    Among some of the leading brands, Head & Shoulders and Oral-B increased their Share of Search by 2.3% and 1% respectively, reflecting a successful strategy to boost brand visibility during the Black Friday and Cyber Monday shopping events. On the other hand, L’Oreal Paris, Colgate, and Neutrogena faced marginal decreases in Share of Search.

    Overall, since the difference in Share of Search values did not change dramatically, the visibility levels of leading brands across key subcategories remained consistent during the Thanksgiving weekend.

    —

    For deeper insights on pricing and discounting trends across a diverse range of shopping categories during Black Friday and Cyber Monday, check out our blog!

    To learn more about our AI-powered Pricing Intelligence and Digital Shelf Analytics platform, contact us today!

  • Black Friday Cyber Monday 2023: Insights on Pricing and Discounts in Home & Furniture

    Black Friday Cyber Monday 2023: Insights on Pricing and Discounts in Home & Furniture

    Insider Intelligence‘s forecast of a 4.5% growth in US Holiday Sales this year has been validated by the sustained robust spending observed during Black Friday and Cyber Monday. Despite multiple challenges impacting consumer spending, such as escalating prices of everyday products and elevated interest rates, shoppers continued to spend significantly, aligning with these earlier predictions.

    However, in response to these projections, retailers strategically adjusted their approach. Our analysis indicates substantial discounts prevalent in the Consumer Electronics and Home & Furniture segments during Cyber Week. Prominent retailers specializing in Home & Furniture, such as Wayfair, Overstock, and Home Depot, notably led the charge in offering attractive discounts.

    At DataWeave, we harnessed the power of our proprietary data aggregation and analysis platform to track and analyze the prices and deals of home & furniture products across prominent retailers to uncover unique insights into their price competitiveness this BFCM, as well as understand how pricing strategies varied across diverse subcategories and brands.

    We’ve also recently published our analysis of the Consumer Electronics and Apparel categories this Black Friday and Cyber Monday.

    Our Methodology

    For this analysis, we tracked the discounts offered by leading US retailers in the Home & Furniture category during the Thanksgiving weekend sale, including Black Friday and Cyber Monday. We noticed prices and discounts didn’t change significantly over the course of the weekend, and hence the average prices of products between the 24th and 27th of November are being reported. Our sample was chosen to encompass the top 500 ranked products in each product subcategory across leading retailers during the sale.

    • Sample size: 44,716 SKUs
    • Retailers tracked: Amazon, Walmart, Target, Best Buy, Overstock, Wayfair, Home Depot
    • Subcategories reported on: Dishwasher, Washer/Dryer, Mattresses, Beds, Dining Tables, Entertainment Units, Rugs, Luggage, Bookcases, Cabinets, Sofas, Coffee Tables
    • Timeline of analysis: 24 to 27 November 2023

    Our Key Findings

    Discounts Across Retailers

    Wayfair led the pack with the highest average discount of 27.5%, covering an impressive 88% of its Home & Furniture inventory. This bold strategy positions Wayfair as a go-to destination for consumers seeking substantial savings on high-quality Home & Furniture items during Black Friday and Cyber Monday.

    Home Depot offered an average discount of 17.5%, covering a substantial 69% of the products analyzed, choosing to cash in on the Cyber Week madness. Overstock followed next with an average discount of 16.6%.

    Interestingly, Home & Furniture happens to be one of the few categories in which Amazon did not offer the highest discount among the analyzed retailers, choosing a moderate average discount of 13.8%.

    Best Buy also maintained a competitive stance in the category, providing an average discount of 12.8% across 58% of their assortment. Target adopted a conservative markdown strategy, offering a relatively low average discount of 6.5%.

    In summary, the Home & Furniture category exhibited a diverse range of discounting strategies among retailers, reflecting a balance between competitiveness and profit margins. Consumers could have chosen from a spectrum of discounts based on their preferences and budget considerations during Black Friday and Cyber Monday.

    Average Discounts: Subcategories

    Among subcategories, Amazon offered a moderate 8.3% average discount on 32.9% of its products in this Dishwasher category, while Best Buy took a more aggressive stance with a 14.7% average discount covering 55.9% of its products.

    Home Depot emerged as a standout player in the Washer/Dryer category, providing a substantial 21.3% discount on 78.4% of its analyzed inventory. Best Buy closely followed with a 15.1% average discount targeting 67.6% of its products.

    Wayfair grabbed attention with a generous 36.9% average discount on Mattresses, covering almost all (99%) of its analyzed products. In addition, Wafair led the discount war in Beds, Dining Tables, Cabinets, Sofas, Coffee Tables, and Entertainment Units. Overstock took an aggressive pricing stance on Rugs, offering a substantial 52.3% average discount, covering 100% of its Rugs inventory.

    Average Discounts: Brands

    Among brands, Signature Design by Ashley maintained a consistent presence with substantial discounts on both Best Buy (25.24%) and Overstock (16.19%). This could be indicative of the brand’s commitment to appealing to a diverse customer base through varied retail channels. Costway emerges as a standout brand offering exceptionally high discounts at both Target (61.6%) and Walmart (51.7%).

    Home Decorators Collection, Home Depot’s in-house brand, offered a significant 30.9% discount at Home Depot. High-margin private label brands like these afford retailers the opportunity to offer markdowns while retaining significant margins.

    Strategic positioning on specific platforms, as seen with Alwyn Home on Wayfair and Noble House at Home Depot, suggests brands tailor their approach to the strengths and customer demographics of each retailer. The data suggests a nuanced interplay between brand positioning, discount strategies, and the perceived value offered.

    Share of Search For Home & Furniture Brands

    The Share of Search data for the Home & Furniture category unveils intriguing insights into brand visibility and performance during the Black Friday and Cyber Monday events. In this competitive landscape, where consumer decisions are influenced not only by discounts but also by brand visibility, the dynamics of Share of Search become pivotal.

    Samsung strategically increased its Share of Search during the sale, showcasing a 1.2% improvement. This suggests a deliberate effort to reinforce brand visibility and capture the attention of potential buyers actively searching for Home & Furniture products, in this case, Washer/Dryers and Dishwashers.

    Bosch too experienced a notable surge in Share of Search by 1.1%. LG, meanwhile, maintained a consistent Share of Search, with a marginal decrease of 0.1%. American Tourister experienced a modest increase in Share of Search by 0.4%.

    Like in the other categories analyzed, the dynamics of Share of Search in the Home & Furniture category reflect brand strategies aimed at not only offering discounts but also ensuring heightened visibility during the critical Black Friday and Cyber Monday shopping events. Positive shifts indicate effective marketing efforts, while stable performers demonstrate a resilient brand presence in a competitive online marketplace.

    To explore how our insights can help retailers and brands boost their pricing strategies during sale events, reach out to us today!

    For more in-depth analyses and trends across various shopping categories, stay tuned to our blog.

  • Black Friday Cyber Monday 2023 Insights: A Report on Pricing and Discounts in Apparel

    Black Friday Cyber Monday 2023 Insights: A Report on Pricing and Discounts in Apparel

    As the highly anticipated shopping season approached, industry analysts, including Deloitte, had forewarned consumer spending caution owing to persistent inflationary pressures tightening budgets. Despite these concerns, the holiday spirit was buoyed by sensational deals that delighted bargain-hunting shoppers.

    According to the National Retail Federation (NRF), over 200 million consumers participated in both in-store and online shopping activities over the Thanksgiving weekend. This marked an almost 2% uptick from the previous year, surpassing the NRF’s initial estimates of 182 million and showcasing a robust start to the holiday shopping season.

    So what was all the hype about this Black Friday and Cyber Monday? How did top retailers react to reports of possibly decreased consumer spending? At DataWeave, we harnessed the power of our proprietary data aggregation and analysis platform to track and analyze the prices and deals of products across prominent retailers and categories to uncover unique insights into their price competitiveness this BFCM, as well as understand how pricing strategies varied across diverse subcategories and brands.

    In this article, we focus on the pricing and discounting strategies of Amazon, Walmart, and Target in the Apparel category.

    (Read Also: Black Friday Cyber Monday 2023: Insights on Pricing and Discounts in Consumer Electronics)

    Stay tuned to our blog for insights on other shopping categories like Home & Furniture, and Health & Beauty!

    Our Methodology

    For this analysis, we tracked the average discounts of apparel products among leading US retailers during the Thanksgiving weekend sale, including Black Friday and Cyber Monday. We noticed prices and discounts didn’t change significantly over the course of the weekend, and hence the average prices of products between the 24th and 27th of November are being reported. Our sample was chosen to encompass the top 500 ranked products in each product subcategory across during the sale.

    • Sample size: 17,981 SKUs
    • Retailers tracked: Amazon, Walmart, Target
    • Subcategories reported on: Women’s Tops, Men’s Swimwear, Men’s Innerwear, Women’s Innerwear, Women’s Athleisure, Women’s Dresses, Men’s Athleisure, Men’s Shirts, Women’s Shoes, Men’s Shoes, Women’s Swimwear
    • Timeline of analysis: 24 to 27 November 2023

    Our Key Findings

    Average Discounts Across Retailers

    Amazon offered the most attractive deals, showcasing an average discount of 19.5%, applying to a substantial 61% of their apparel inventory.

    Trailing closely behind was Target, offering an average discount of 14.8% across 52% of the products analyzed. Walmart, however, took a more conservative approach, providing an average discount of 8.5%, applicable to 29% of its products.

    The contrast in discounting strategies highlights the diverse tactics employed by retailers to entice Black Friday and Cyber Monday shoppers within the Apparel category. Amazon remains the forerunner, balancing competitive discounts with a significant coverage of discounted items.

    Target follows suit with a competitive stance, while Walmart opts for a more reserved markdown approach, given that the retailer tends to carry a large number of products in the affordable price ranges.

    Average Discounts: Subcategories

    Examining the Black Friday and Cyber Monday discount landscape within the Apparel category reveals intriguing patterns among major retailers. Amazon led the charge, boasting an impressive 24.9% average discount on Women’s Tops, covering a substantial 76.5% of its products. In the same subcategory, Target competed fiercely with a 25.1% average discount, covering 87.5% of its products. Walmart, taking a measured approach, presented a 14.6% average discount across 45.1% of its Women’s Tops inventory.

    Notably, Men’s Swimwear at Target has no discounts. Meanwhile, Amazon remained aggressive across various subcategories, particularly in Women’s Shoes and Women’s Tops, aiming to capture a significant market share through both competitive pricing and a broad coverage of discounted items.

    Average Discounts: Brands

    Across brands, Tommy Hilfiger and Jockey took the lead on Amazon with an enticing average discount of 28.3% and 24.6% respectively, appealing to savvy shoppers. Calvin Klein followed closely with a 17.3% discount, offering a balance of style and affordability.

    In Walmart, Crocs stood out with a 39.9% average discount, followed by Reebok (15.7%) and Hanes (14.9%) Xhilaration, Target’s in-house brand, stole the spotlight on the retailer platform with an impressive 50% average discount. Reebok (32.3%) and Levi’s (22.9%) maintained competitive discounts, appealing to diverse tastes.

    Our analysis sheds light on the dynamic landscape of apparel discounts, showcasing how brands adopt varying pricing strategies to position themselves competitively for Black Friday and Cyber Monday shoppers.

    Share of Search For Apparel Brands Across Subcategories

    The dynamics of Black Friday and Cyber Monday extend beyond price reductions, with brands strategically vying for increased visibility through Share of Search metrics. This metric signifies a brand’s prominence among the top 20 ranked products in a given subcategory, offering valuable insights into their online marketplace visibility.

    Among the standout performers in the Apparel category, Jockey experienced a significant surge in Share of Search, leaping from 1.70% before the event to an impressive 13.30% during the Black Friday and Cyber Monday sales. Speedo, in the Women’s Swimwear subcategory, demonstrated a substantial increase from 4.40% to 13.30%, solidifying its presence and gaining an 8.90% boost in Share of Search.

    Tommy Hilfiger and Adidas also exhibited notable gains in Share of Search, increasing by 5.30% and 5.60%, respectively. However, some brands experienced a slight dip, with Speedo in the Men’s Swimwear subcategory seeing a 2.50% dip in their search visibility, and Reebok in Men’s Shoes witnessing a 3.3% decrease.

    These fluctuations highlight the dynamic nature of brand strategies during Black Friday and Cyber Monday in the Apparel category, where gaining visibility also proves to be crucial alongside offering competitive discounts.

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    For a deeper dive into the world of competitive pricing intelligence and to explore how our solutions can benefit apparel retailers and brands, reach out to us today!

    Stay tuned to our blog for forthcoming analyses on pricing and discounting trends across a spectrum of shopping categories, as we continue to unravel the intricacies of consumer behavior and market dynamics.

  • Black Friday Cyber Monday 2023: Insights on Pricing and Discounts in Consumer Electronics

    Black Friday Cyber Monday 2023: Insights on Pricing and Discounts in Consumer Electronics

    As Black Friday and Cyber Monday unfolded across the globe, there was a noticeable subdued atmosphere compared to previous years. TD Cowen brokerage adjusted its forecast for US holiday spending, revising it down from an initial 4-5% growth to a more conservative estimate of 2-3%.

    Compounded by persistent inflation and elevated interest rates, many consumers find themselves financially strained, leading to the projection of the slowest growth in US holiday spending in five years.

    In this context, it would be relevant to investigate whether this restrained reaction from consumers had an influence on the extent of attractive deals and discounts provided by top retailers and brands during the sale event.

    At DataWeave, we harnessed the power of our proprietary data aggregation and analysis platform to track and analyze the prices and deals of consumer electronics products across prominent retailers to uncover unique insights into their price competitiveness this BFCM, as well as understand how pricing strategies varied across diverse subcategories and brands.

    Keep an eye on our blog for insights on other shopping categories like Apparel, Home & Furniture, and Health & Beauty!

    Our Methodology

    For this analysis, we tracked the average discounts among leading US electronics retailers during the Thanksgiving weekend sale, including Black Friday and Cyber Monday. We noticed prices and discounts didn’t change significantly over the course of the weekend, and hence the average prices of products between the 24th and 27th of November are being reported. Our sample was chosen to encompass the top 500 ranked products in each product subcategory across leading retailers during the sale.

    • Sample size: 23,505 SKUs
    • Retailers tracked: Amazon, Walmart, Target, Best Buy
    • Subcategories reported on: Headphones, Laptops, Smartphones, Tablets, Speakers, TVs, Earbuds, Wireless Headphones, Drones, Smartwatches
    • Timeline of analysis: 24 to 27 November 2023

    Our Key Findings

    Average Discounts Across Retailers

    The observed Black Friday and Cyber Monday discount strategies reveal a distinct competitive landscape among major retailers. Amazon emerged as the frontrunner, offering the highest average discounts at 23.30%, spanning a significant 74% of their consumer electronics inventory. Best Buy closely followed, with an average discount of 19.40% across 76% of their products.

    On the other hand, Target and Walmart adopted a more conservative stance, providing lower average discounts at 14.8% and 12%, respectively, with Target discounting 51% of its products and Walmart discounting 41%. This variation in discounting strategies highlights the diverse approaches retailers take to attract and retain Black Friday and Cyber Monday shoppers, balancing competitiveness with profit margins.

    Average Discounts: Subcategories

    In the Headphones subcategory, Amazon stands out with a substantial 31.40% average discount, targeting 84.69% of SKUs, showcasing an aggressive discounting strategy. Best Buy follows closely, demonstrating competitive pricing with a 21.80% average discount on 67.03% of products.

    Meanwhile, in TVs, Best Buy offered a significant 17.9% average discount across 89% of its products, signaling a targeted effort to capture a broad market share in this subcategory.

    In the Laptop subcategory, Target was highly conservative, with only a 4.1% average discount covering 14.3% of its products, while Walmart positioned itself with a moderate 9.5% average discount, targeting 39.8% of its inventory.

    Among Smartphones, Amazon (14.7%) was third to Best Buy and Target, which offered average discounts of 20.5% and 18.1%, respectively. Walmart, with an average discount of only 9.9% in the subcategory opted for a relatively muted approach.

    Average Discounts: Brands

    The discount strategies across top electronics brands during Black Friday unveil distinct approaches. Samsung emerges as a focal point across Amazon, Best Buy, Walmart, and Target. The brand was most attractively priced on Best Buy, with an average discount of 25.3%, followed by Target (18.3%) and Amazon (17.9%).

    Apple’s discounts were quite consistent across Amazon (17.6%), Best Buy (16.1%), and Target (17.8%), with the exception of Walmart (8.1%). JBL, interestingly, opted to discount very heavily on Best Buy, at an average of 38.8%, resulting in several attractive deals for shoppers on the website. Sony, too, offered impressive discounts at over 23% on Amazon and Best Buy, followed by 16% on Walmart. On Amazon, Amazon Renewed (13.9%) was among the most aggressively discounted products, highlighting an effort to further appeal to cost-conscious consumers.

    Overall, our analysis throws light on the nuanced strategies employed by leading brands on Amazon, Best Buy, Walmart, and Target, reflecting a delicate interplay between brand positioning, pricing competitiveness, and customer appeal.

    Share of Search For Consumer Electronics Brands Across Subcategories

    The Share of Search data reflects intriguing shifts in brand strategies during the Black Friday and Cyber Monday events. During sale events, brands looking to entice shoppers don’t rely only on price but also on search visibility to help drive awareness and conversion. Share of Search is defined as the share of a brand’s products among the top 20 ranked products in a subcategory, thereby providing insight into a brand’s visibility on online marketplaces.

    Some of the brands that improved their Share of Search the most include LG, Skullcandy, Asus, JBL, and Samsung. On the other hand, prominent brands like Sony and Apple actually lost ground on this metric by 0.4% and 2% respectively.

    At DataWeave, our commitment to empowering retailers and brands with actionable competitive and digital shelf insights remains unwavering. Our AI-powered platform provides a comprehensive view of market dynamics for our customers, enabling informed decision-making. As a partner in your journey, we offer tailored solutions to enhance your competitive edge, drive sales, and elevate your brand presence. To find out more about our solution, reach out to us today!

    To learn more about pricing and discounting trends during Black Friday and Cyber Monday across various other shopping categories, stay tuned to our blog!

  • Which Amazon Sale Offered Better Deals: Prime Day in July or Big Deal Days in October?

    Which Amazon Sale Offered Better Deals: Prime Day in July or Big Deal Days in October?

    Amazon reported a record-breaking Prime Day this July, marking it as the biggest sales event in the company’s history. So when the eCommerce giant announced the Prime Big Deal Days this fall, we were curious to find out how big a deal it really is.

    The Prime Big Deal Days, similar in magnitude to the Summer Prime Day, promised to present substantial savings across a diverse range of categories, including electronics, toys, home, fashion, beauty, and Amazon products.

    However, for a shopper, an important question is: Does the Prime Big Deal Days in October offer lower prices than Amazon’s mega Prime Day event in July?

    To answer this question, we turned our data aggregation and analysis platform to focus on these two sale events and analyzed which event offered better deals across key categories and brands.

    TL;DR: Surprisingly, the Prime Big Deal Days in October offered, on average, 2.02% higher discounts than its counterpart event in July.

    Read on for details on how we went about our analysis and how discounts vary across categories, sub-categories, and brands.

    Our Methodology

    We tracked the prices and discounts of a large sample of products during both Prime Day events. The following are some relevant details about our sample:

    • Number of products analyzed: 1500+
    • Categories: Apparel, Consumer Electronics, Home & Furniture, Health & Beauty
    • Prime Day Sale Analysis: 11-12 July 2023
    • Prime Big Deal Days Analysis: 10-11 Oct 2023
    • Website: Amazon.com

    Our analysis focused on the differences in the prices and discount levels of products between the two sale events.

    Our Key Findings

    The average discount during the Prime Big Deal Days in October was 29.44%, which was 2.02% higher than the average discount during the Prime Day sale in July (27.42%). Interestingly, the October event offered better deals across each product category analyzed, albeit at slightly varying levels.

    By offering deeper discounts in October, Amazon may have aimed to encourage early holiday shopping, thereby capturing a larger share of the consumer wallet before competitors intensify their promotional activities closer to the festive season.

    As other retailers and online marketplaces gear up for their own holiday promotional events, Amazon’s decision to provide heightened discounts in October could serve as a preemptive move to secure customer loyalty and drive sales momentum before the onset of the peak shopping period.

    Additionally, Amazon’s strategic push to amplify the visibility of its diverse product offerings, including exclusive launches and partnerships during the October event might have contributed to the higher discounts.

    Next, let’s take a closer look at each product category.

    Apparel

    During October’s Prime Big Deal Days, the Apparel category experienced a notable uptick, boasting a 2.29% increase in discounts compared to the earlier Prime Day event in July.

    In the detailed assessment of Apparel sub-categories, Men’s and Women’s Swimwear, alongside Men’s Shoes, Innerwear, and Athleisure, emerged as the segments showcasing the most substantial average discounts during October. Fall also brought about more affordable prices for Women’s Innerwear and Men’s Shirts. However, Women’s Athleisure, Dresses, and Tops displayed diminished average discounts during this Prime Big Deal Days event.

    Delving into brand-specific analyses revealed intriguing trends. Athleisure brands such as Ibkul, Esprlia, and Ryka notably escalated their discounts in October after minimal markdowns during the Summer Prime Day sale.

    Steve Madden, witnessing heightened discounts in October, hinted at a growing demand for boots and footwear in the Autumn and Winter seasons. For instance, the Steve Madden Men’s Fenta Fashion Sneaker was priced at $46 during the Summer Prime Day, and only at $35 during the Prime Big Deal Days in October.

    Conversely, brands like PGA Tour, Land’s End, Roxy, and Anrabess offered more substantial discounts during the Summer compared to the October event.

    Consumer Electronics

    The Consumer Electronics segment during October’s Prime Big Deal Days showcased an average price decrease of 1.98% compared to the Prime Day event in July.

    Nearly all scrutinized subcategories experienced heightened discounts during the Fall Prime Big Deal Days in October. Tablets, Speakers, Drones, and Smartwatches notably presented higher discounts of 4.06%, 3.51%, 2.99%, and 2.69%, respectively, in October. However, more enticing deals were found on Earbuds and TVs during July’s event.

    Examining consumer electronics brands, Google stood out by offering the most compelling deals in October, boasting an average discount of 23.35%, marking an 8.94% increase from the Summer Prime Days’ 14.41%. Psier, Sony, and OnePlus also featured significantly reduced prices during the Fall. For example, the OnePlus 10 Pro | 8GB+128GB was $500 during the sale in July and only $440 during the Prime Big Deal Days in October.

    Conversely, prominent brands such as Bose, Sennheiser, Samsung, LG, and Asus opted to offer heavier discounts in July. Notably, the Samsung All-in-One Soundbar w/Dolby 5.1 was priced at $218 in October but only $168 in July.

    Home & Furniture

    During October’s Prime Big Deal Days, the Home & Furniture category experienced a notable 1.59% increase in average discounts compared to the Prime Day event held in July.

    Notably, Entertainment Units, Rugs, and Coffee Tables emerged as standout sub-categories that were more attractively priced in October, exhibiting price differences of 7.73%, 5.33%, and 4.80%, respectively.

    Interestingly, among the scrutinized sub-categories, only Luggage showed a lower price during the Prime Day sale in July compared to the October event. This shift likely reflects evolving consumer demand as the holiday season approaches, with items like rugs and entertainment units becoming increasingly sought-after categories for purchase.

    If you’re keen to explore how these trends vary across brands within this category, reach out to us for more insights.

    Health & Beauty

    During October’s Prime Big Deal Days, the Health & Beauty category showcased products at an average of 1.99% lower prices compared to the Prime Day event held in July.

    Our analysis of Health & Beauty reveals that a majority of the subcategories presented higher discounts during the October Big Deal Days event. Essential items such as Toothpaste, Sunscreen, and Electric Toothbrushes notably stood out as significantly more affordable during the Fall event, reflecting not only consistent demand but also a seasonal emphasis on these products. For instance, the Oral B iO Series 3 Limited Edition Electric Toothbrush, priced at $140 during the summer Prime Days, was further discounted to $120 in the fall event.

    Interestingly, Beard Care emerged as an exception, displaying higher discounts during the Prime Day sale in Summer compared to Fall’s Prime Big Deal Days.

    Examining brands within the category, Babyganics, Thinkbaby, and Vaseline showcased substantial increases in average additional discounts during October’s Prime Big Deal Days.

    Conversely, prominent brands like Maybelline, Neutrogena, and Cetaphil offered lower discounts during the fall event.

    Competitive Insights to Drive Optimized Sale Event Pricing

    At DataWeave, we understand the pivotal role of competitive pricing insights in empowering retailers and brands to gain a competitive edge, especially during significant events like Prime Day. Our commitment lies in providing retailers with precise and extensive competitor price tracking on a large scale. This empowers them to devise impactful pricing strategies and consistently uphold a competitive stance in the market. To learn more about how this can be done, talk to us today!

  • Why Unit of Measure Normalization is Critical For Accurate and Actionable Competitive Pricing Intelligence

    Why Unit of Measure Normalization is Critical For Accurate and Actionable Competitive Pricing Intelligence

    Competitive pricing intelligence is pivotal for retailers seeking to analyze their product pricing in relation to competitors. This practice is essential for ensuring that their product range maintains a competitive edge, meeting both customer expectations and market demands consistently.

    Product matching serves as a foundational element within any competitive pricing intelligence solution. Products are frequently presented in varying formats across different websites, featuring distinct titles, images, and descriptions. Undertaking this process at a significant scale is highly intricate due to numerous factors. One such complication arises from the fact that products are often displayed with differing units of measurement on various websites.

    The Challenge of Varying Units

    In certain product categories, retailers often offer the same item in varying volumes, quantities, or weights. For instance, a clothing item might be available as a single piece or in packs of 2 or 3, while grocery brands commonly sell eggs in counts of 6, 12, or 24.

    Consider this example: a quick glance might suggest that an 850g pack of Kellogg’s Corn Flakes priced at $5 is a better deal than a 980g pack of Nestle Cornflakes priced at $5.2. However, this assumption can be deceptive. In reality, the latter offers better value for your money, a fact that only becomes evident through price comparisons after standardizing the units.

    This issue is particularly relevant due to the prevalence of “shrinkflation,” where brands adjust packaging sizes or quantities to offset inflation while keeping prices seemingly low. When quantities, pack sizes, weight, etc. reduce instead of prices increasing, it’s important that this change is considered while analyzing competitive pricing.

    Normalizing Units of Measure

    In order to effectively compare prices among different competitors, retailers must standardize the diverse units of measurement they encounter. This standardization (or normalization) is crucial because price comparisons should extend beyond individual product SKUs to accommodate variations in package sizes and quantities. It’s essential to normalize units, ranging from “each” (ea) for individual items to “dozen” (dz) for sets, and from “pounds” (lb), “kilograms” (kg), “liters” (ltr), to “gallons” (gal) for various product types.

    For example, a predetermined base unit of measure, such as 100 grams for a specific product like cornflakes, serves as the reference point. The unit-normalized price for any cornflake product would then be the price per 100 grams. In the example provided, this reveals that Kellogg’s is priced at $0.59 per 100 grams, while Nestle is priced at $0.53 per 100 grams.

    Various Categories of Unit Normalization

    1. Weight Normalization

    Retailers frequently feature products with weight measurements expressed in grams (g), kilograms (kg), pounds (lbs), or ounces (oz).

    2. Quantity or Pack Size Normalization

    Products are also often featured with varying pick sizes or quantities in each SKU.

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    3. Volume or Capacity Normalization

    Products can also vary in volumes or capacities with units like liters (L) or fluid ounces (fl oz).

    DataWeave’s Unit Normalized Pricing Intelligence Solution

    DataWeave’s highly sophisticated product matching engine can match the same or similar products and normalize their units of measurement, leading to highly accurate and actionable competitive pricing insights. It standardizes different units of measurement, like weight, quantity, and volume, ensuring fair comparisons across similar and exact matched products.

    Retailers have the flexibility to view pricing insights either with retailer units or normalized units. This capability empowers retailers and analysts to perform accurate, in-depth analyses of pricing information at a product level.

    In some scenarios, analyzing unit normalized pricing reflects pricing trends and competitiveness more accurately than retail price alone. This is particularly true for categories like CPG, where products are sold in diverse units of measure. For instance, in the example shown here, we can view a comparison of price position trends for the category of Fruits and Vegetables based on both retail price and unit price.

    The difference is striking: the original retail price based analysis shows a stagnation in price position, whereas unit normalized pricing analysis reflects a more dynamic pricing scenario.

    With DataWeave, retailers can specify which units to compare, ensuring that comparisons are made accurately. For example, a retailer can specify that unit price comparisons apply only to 8, 12, or 16-ounce packs, as well as 1 or 3-pound packs, but not to 10 and 25-pound bags. This precision ensures that products are matched correctly, and prices are represented for appropriately normalized units, leading to more accurate pricing insights.

    To learn more about this capability, write to us at contact@dataweave.com or visit our website today!

  • From Data to Dollars: How Digital Shelf Analytics Drives Tangible Business Impact and ROI for Brands

    From Data to Dollars: How Digital Shelf Analytics Drives Tangible Business Impact and ROI for Brands

    For consumer brands, the digital marketplace presents an unparalleled landscape of opportunities for engaging with consumers and expanding their market presence. Within this dynamic environment, Digital Shelf Analytics has emerged as a crucial pillar in a brand’s eCommerce strategy. This technology provides valuable insights into a brand’s organic and paid visibility on marketplaces, content quality, pricing strategies, promotional efforts, and product availability. These insights help brands gain a comprehensive understanding of their competitive positioning and overall market performance.

    Nevertheless, many brands often grapple with the question of whether this understanding translates into tangible actions that drive real business impact and return on investment (ROI). This uncertainty stems from a lack of clarity about the direct correlation between digital shelf insights and key metrics such as enhanced sales conversions.

    Nonetheless, there is compelling evidence that when these insights are effectively harnessed and strategic actions are taken, brands can realize significant, measurable benefits.

    So, the question arises: does Digital Shelf Analytics genuinely deliver on its promises?

    At DataWeave, we’ve partnered with numerous brands to fuel their eCommerce growth through the application of digital shelf analytics. In this article, we will delve into these insights, uncovering the concrete and quantifiable results that brands can achieve through their investments in digital shelf analytics.

    Digital Shelf KPIs and Their Impact

    Digital Shelf Analytics is a robust system that analyzes specific key performance indicators (KPIs) about the digital shelf, furnishing brands with precise recommendations to not only bolster these KPIs but also to monitor the enhancements over time. The following is a brief explanation of digital shelf KPis and their expected impact areas:

    Product Availability: Ensuring Shoppers Never Hear “Out of Stock” Again

    Timely insights on the availability of products ensures brands reduce replenishment times at scale, which can significantly impact sales, creating an unbreakable link between product availability and revenue. With Digital Shelf Analytics, procurement and replenishment teams can set up notifications to promptly identify low or out-of-stock items and take swift action. This can also be done for specific ZIP codes or individual stores. In addition, availability plays a crucial role in a brand’s Share of Search and search rankings, as online marketplaces often ensure only in-stock products are shown among the top ranks.

    Share of Search: Dominating the Digital Aisles

    If a product isn’t visible, does it even exist? In fact, 70% of consumers never go beyond the first page of search results on major online marketplaces. Therefore, as a brand, the visibility of your products for relevant search keywords and their appearance on the first page can heavily determine your awareness metrics. This is where the concept of Share of Search comes into play. Think of it as securing prime shelf space in a physical store. Digital shelf insights and benchmarking with category leaders for Share of Search help ensure your products command relevant attention on the digital shelf.

    Content Quality: Crafting the Perfect Product Story

    Creating engaging product descriptions and visuals is akin to giving your products a megaphone in a crowded marketplace. By enhancing content quality, including product names, titles, descriptions, and images, brands can climb the search result rankings, leading to increased visibility and subsequently, more sales.

    Ratings and Reviews: The Power of Social Proof

    Public opinion holds immense sway. Research indicates that a single positive review can trigger a 10% surge in sales, while a multitude of favorable reviews can propel your product to a 44% higher trajectory. The correlation between ratings and sales is not surprising—each step up the rating ladder can translate to substantial revenue growth.

    While it’s reasonable to anticipate a connection between these KPIs and downstream impact metrics such as impressions, clicks, and conversions, we were driven to explore this correlation through the lens of real-world data. To do so, we meticulously monitored the digital shelf KPIs for one of our clients and analyzed the improvements in these metrics.

    It’s essential to acknowledge that not all observed impact areas can be solely attributed to enhancements in digital shelf KPIs. Still, it’s evident that a robust correlation exists. The following section presents an in-depth case study, shedding light on the results of this analysis.

    A Success Story: Real-World Impact of Digital Shelf Analytics

    Let’s dive into the journey of one of our clients – a prominent CPG brand specializing in the sale of baked goods and desserts. Through their experience, we will illustrate the transformative impact of our DataWeave Digital Shelf Analytics product suite.

    Over a period of one year, from August 2022 to July 2023, the brand leveraged several key modules of Digital Shelf Analytics for Amazon, including Share of Search, Share of Category, Availability, Ratings and Reviews, and Content Audit. Each of these digital shelf KPIs played a vital role in shaping the brand’s performance across various stages of the buyer’s journey.

    The buyer’s journey is typically delineated into three key stages:

    • Awareness: At this stage, shoppers peruse multiple product options presented on search and category listing pages, gaining an initial understanding of the available choices.
    • Consideration: Here, shoppers narrow down their selections and evaluate a handful of products, moving closer to a purchase decision.
    • Conversion: In this final stage, shoppers make their ultimate product choice and proceed to complete the purchase.

    Let’s now examine the data to understand how digital shelf KPIs helped drive tangible ROI on Amazon for the brand across the stages of the buyer journey.

    Stage 1: Raising Awareness

    Enhancing Share of Search and Share of Category can help brands boost product visibility and raise brand awareness. The following chart demonstrates the steady, incremental improvements in our client’s Share of Search and Share of Category (in the top 20 ranks of each listing page) throughout the analyzed period. These enhancements were achieved through various measures, including product sponsorship, content enhancement, price optimization, promotional initiatives, and more.

    This amplified Share of Search and Share of Category directly translates into improved product discoverability, as evident from the surge in impressions depicted in the chart below.

    Stage 2: All Things Considered

    In the consideration stage, shoppers make their product selections by clicking on items that meet their criteria, which may include factors like average rating, number of ratings, price, product title, and images. For brands, this underscores the importance of crafting meticulously detailed product content and accumulating a substantial number of ratings.

    The subsequent chart illustrates the year-long trend in both average ratings and the number of ratings, both of which have displayed steady improvement over time.

    The enhancements in the number of ratings and the average rating have a direct and positive impact on product consideration. This, in turn, has led to a noticeable year-over-year increase in page views, as indicated in the chart below.

    These improvements are likely to have also been influenced by the overall enhancement of content quality, which is detailed separately in the section below.

    Stage 3: Driving Decisions

    As buyers progress to the next stage, they reach the pivotal point of making a purchase decision. This decision is influenced by multiple factors, including product availability, content quality, and the quality of reviews, reflecting customer sentiment.

    Our client effectively harnessed our Availability insights, significantly reducing the likelihood of potential out-of-stock scenarios and enhancing replenishment rates, as highlighted in the chart below. The same chart also indicates improvements in content quality, measured by the degree to which the content on Amazon aligns with the brand’s ideal content standards.

    Below, you’ll find the year-over-year growth in conversion rates for the brand on Amazon. This metric stands as the ultimate measure of business impact, directly translating into increased revenue for brands.

    As the data uncovers, growth in key digital shelf KPIs cumulatively had a strong correlation with impressions, page views, and conversion rates.

    It is also important to note that the effect of each KPI cannot be viewed in isolation, since they are often interdependent. For example, improvement in content and availability could boost Share of Search. Accurate content could also influence more positive customer feedback. Brands need to consider optimizing digital shelf KPIs holistically to create sustained business impact.

    Impact on eCommerce Sales

    After the implementation of digital shelf analytics, the results spoke for themselves. Sales consistently outperformed the previous year’s records month after month. As shown in the chart below, the diligent application of DataWeave’s recommendations paved the way for an impressive 8.5% year-over-year increase in sales, leaving an indelible mark on the brand’s eCommerce success.

    From boosting product visibility to catapulting conversion rates, Digital Shelf Analytics serves as the key to unlocking unparalleled online success.

    While the success story detailed above does not establish a direct causation between Digital Shelf Analytics and sales revenue, there is undoubtedly a strong correlation. It’s evident that digital shelf KPIs play a pivotal role in optimizing a brand’s eCommerce performance across all stages of the buyer journey. Hence, for brands, it is vital that they collaborate with the right partner and harness digital shelf insights to fine-tune their eCommerce strategies and tactics.

    That said, the eCommerce landscape is in a constant state of flux, and there is still much to learn about how each digital shelf KPI influences brand performance in the online realm. With more data and an increasing number of brands embracing Digital Shelf Analytics, it’s only a matter of time before a direct causation is firmly established.

    Reach out to us today to know more about how your brand can leverage Digital Shelf Analytics to drive higher sales and market share in eCommerce.

  • Revolutionizing Fuel Pricing: How Fuel Retailers and Convenience Stores Can Gain a Winning Edge with DataWeave

    Revolutionizing Fuel Pricing: How Fuel Retailers and Convenience Stores Can Gain a Winning Edge with DataWeave

    Consider this scenario: A retailer establishes its fuel prices using pricing data that’s a few days old, only to subsequently discover that a nearby competitor is offering substantially lower prices. The result? Lost customers, decreased foot traffic, and diminished sales. This serves as a stark reality that retailers must confront and address today.

    In the fiercely competitive realm of retail, where every decision holds weight, maintaining a competitive edge is paramount. The fuel category, frequently underestimated, has the potential to significantly impact a retailer’s revenue stream. This challenge is not unique; retailers worldwide, particularly in North America, grapple with a common hurdle: mastering the intricate art of real-time fuel pricing.

    The Quest For Reliable, Real-Time Fuel Pricing Data

    For retailers, traditional methods for procuring and analyzing fuel price data have proven to be both expensive and error-prone, often relying on manual data collection or third-party data providers. These outdated approaches yield frustrating delays, inaccuracies, and missed opportunities. When it comes to obtaining timely fuel pricing intelligence, the majority of fuel retailers grapple with three central challenges:

    • Low Accuracy: Ensuring that fuel pricing information remains up-to-date, dependable, and actionable, even when sourced from complex web-based platforms.
    • Less Coverage: Acquiring comprehensive data that encompasses all of North America, spanning across retailers, convenience stores, fuel stations, and beyond.
    • High Cost: Effectively managing the substantial costs associated with acquiring and processing this vital information.

    DataWeave’s Fuel Pricing Intelligence Solution

    Comprehensive, accurate, and real-time fuel pricing intelligence can play a huge role in the profitability of retailers throughout North America. DataWeave takes the forefront in delivering this transformative Data-as-a-Service (DaaS) solution to some of the most prominent retailers in the region, including the top 20 fuel retail behemoths.

    With a rich and extensive history spanning over a decade in the realm of competitive intelligence, DataWeave boasts an impressive track record of empowering well-informed decision-making in retail. We leverage state-of-the-art technology to bring an unparalleled level of accuracy, timeliness, and coverage to fuel pricing intelligence.

    The following are some compelling advantages offered by our solution:

    Accurate and Real-Time First Party Data

    We deliver retailers an unparalleled advantage through real-time, first-party fuel price data. Our data originates directly from the retailer’s own channels, encompassing websites and mobile apps, rendering it the industry’s foremost and most reliable source.

    Imagine having access to fuel pricing information that updates as frequently as every 30 minutes. This rapid update cadence guarantees that you, as a retailer, constantly possess the latest pricing insights at your fingertips, empowering you to respond swiftly to market fluctuations and competitor manoeuvres. Our comprehensive data spans a wide spectrum of fuel types, including:

    • Gasoline: Be it regular, mid-grade, super, premium, ethanol-free, ethanol blends, methanol blends, or reformulated gasoline, we have got you covered.
    • Diesel: Our data encompasses biodiesel, biodiesel off-road, biodiesel blends, biodiesel ultra-low sulfur (ULS), diesel ultra-low sulfur (ULS), diesel off-road, standard diesel, and premium diesel.

    Armed with our real-time, first-party data, you can make pricing decisions with unwavering confidence, secure in the knowledge that you possess access to the most current, authoritative, and extensive fuel pricing intelligence in North America.

    The data points we capture directly from relevant web sources include: gas station postal code, store name and code, location, city, state, ZIP code, fuel type, competitor name, regular price, member price (if available), time and date of data capture, and more.

    Click here if you wish to access a sample report of our fuel pricing data.

    Unrivaled Geographical Coverage

    Our extensive coverage of fuel data spans over 30,000 ZIP codes and encompasses the top 100 retailers across the western, mid-western, and eastern regions of the United States.

    Retailers benefit from the flexibility to configure and tailor the solution to their precise needs, whether it involves adding more locations or selectively acquiring specific segments of the data. This far-reaching coverage guarantees that retailers, whether situated in bustling urban centers or remote areas, can readily access the essential data required to maintain their competitive edge.

    Moreover, if you currently source your fuel pricing data from alternative providers, our solution seamlessly integrates, amplifies, and complements your existing array of data sources, ensuring a harmonious and unified approach to data acquisition.

    Optimization of Dynamic Pricing Strategies

    In the world of retail, the importance of timing cannot be overstated. Even a mere difference of a few cents can translate into millions of dollars in revenue impact. With DataWeave, retailers gain the capability to make data-driven decisions that provide them with a competitive edge around the clock, every single day.

    Our platform empowers you to unearth margin gaps by pinpointing opportunities to raise prices while maintaining your competitive pricing position. It also identifies instances where you may be substantially overpriced, prompting necessary price adjustments to ensure competitiveness within the market. All these valuable insights are available at a hyperlocal level, facilitating pricing efficiency and optimization across your various regions of coverage. Equipped with this real-time data, you can swiftly adapt to ever-changing market conditions.

    Furthermore, our comprehensive competitive data seamlessly integrates into your existing pricing systems through APIs, facilitating quick and informed pricing actions based on robust data.

    Reliable and Customer-First Tech Platform

    Our platform boasts a remarkable level of sophistication when it comes to data aggregation, normalization, visualization, and integration capabilities. It stands as a massively scalable system with the capacity to aggregate billions of data points daily, spanning thousands of web sources. This includes the intricate handling of sources like mobile apps and websites known for frequently altering their site structures, among others.

    What truly sets us apart is our proficiency in addressing these challenges through a blend of human expertise and large-scale machine learning. Additionally, our commitment to delivering unmatched service extends to round-the-clock, 24/7 support. This comprehensive approach makes our fuel pricing intelligence solution not only effective but also cost-efficient in meeting your fuel data requirements.

    We also provide a variety of options for you to consume our data, which includes receiving our reports via email, SFTP, S3 buckets, data lakes like Snowflake, and APIs.

    Enhance your Fuel Pricing Strategies with DataWeave

    In the ever-competitive world of retail, staying ahead is not just a goal; it’s a necessity. The fuel pricing landscape, often overlooked, holds immense power to impact a retailer’s profitability. DataWeave’s real-time, comprehensive, and accurate fuel pricing intelligence solution is the key to securing this advantage. Retailers and convenience stores now have a powerful platform at their disposal, offering unparalleled precision, comprehensive coverage, and the agility needed to navigate this landscape.

    Join the ranks of industry leaders who have already harnessed the potential of DataWeave. Reach out to us today to redefine your approach to fuel pricing and propel your business to new heights!

  • Backpacks to Binders: Examining Back-to-School Price Hikes in 2023

    Backpacks to Binders: Examining Back-to-School Price Hikes in 2023

    This year’s back-to-school shopping season has presented a considerable challenge for inflation-weary parents in the US. Despite chatter about alleviating inflation rates, the reality of rising prices tells a different story.

    As families hunt for school supplies, apparel, and other essential items for the academic year, the financial strain remains palpable. Experts note that elevated prices coupled with extensive shopping lists have compelled many parents to be more discerning about their purchases, expenditure thresholds, and preferred shopping venues. Essentially, shoppers are looking for more value for their money with every purchase. According to the National Retail Federation’s 2023 projection, this back-to-school season is poised to be the most financially demanding one to date. The forecast anticipates total spending exceeding $135 billion, marking an increase of over $24 billion compared to the previous year.

    At DataWeave, we continually monitor and analyze pricing activity among retailers across popular shopping categories. Our recent study delved into the pricing trends in the back-to-school category, which includes backpacks, fundamental school supplies, binders, planners, writing instruments, and more. The aim was to understand how the costs of back-to-school essentials have shifted in 2023 in comparison to 2022.

    Pricing of Back-to-School Products in 2023

    Our analysis, spanning 1200 products across major retailers such as Amazon, Walmart, Kroger, and Target reveals an average price surge of 9.8% in 2023 compared to the previous year.

    This upward pricing trend can be attributed to retailers’ strategic efforts to guarantee product availability and uphold quality during a period of heightened demand. As the back-to-school season sparks a surge in shopping activity, retailers like Kroger, Amazon, and Walmart are likely adjusting prices strategically to align with the expenses incurred in securing adequate supplies, managing logistics, and meeting operational demands.

    Average Price Increase 2022-23 By Retailer, Back-To-School Category

    Kroger led the way with a 12.1% price hike, the most significant among the scrutinized retailers. It was followed by Amazon with an average increase of 10.5% and Target with 7.8%. Walmart remains the outlier, with the smallest price increases for back-to-school products in 2023.

    Pricing across Categories and Subcategories

    Among the various categories examined, backpacks have experienced the most pronounced escalation, with prices soaring by a substantial 25%. Within the top 10 highest priced backpacks we looked at, the most substantial price hikes were observed for brands like The North Face (44%) and Fjallraven (33%).

    Average Price Increase 2022-23 By Category Across Retailers, Back-To-School

    The Office Organization category also witnessed a significant price surge of 16.8%, attributed to subcategories like File Folders and Desk Accessories, which saw respective price hikes of 31.3% and 25.2%.

    Categories like Memo Boards & Supplies (14.3%), Binders (12.5%), and Themebooks & Portfolios (12.4%) have likewise encountered notable price hikes. On the other end of the spectrum, Planners and Journals saw a modest rise of 4.4%, while Mailing and Shipping Supplies and Office Machine Accessories experienced comparatively lower price increases at 7% each.

    Interestingly, while items like Journals and Writing Instruments maintain popularity year-round, Backpacks and Memo Boards are particularly sought after during the back-to-school season, contributing to more substantial price hikes in these categories.

    On the other hand, consumers are consistently on the lookout for cost savings and deals from retailers, especially as they deal with inflationary pressures. In response, Kroger, Target, and Walmart have introduced back-to-school savings initiatives. For instance, Kroger is offering more than 250 items for less than $3 and some items for just $1, encompassing essentials such as paper, pencils, and glue sticks. Lower price increases across categories like journals and writing essentials could be attributed to these initiatives.

    Brands with the Highest Price Increases across Categories

    Across various back-to-school categories, some brands stand out with significant price increases. For instance, in the Office Organization category, Ubrands leads the pack with a substantial 38.30% surge, followed by Pendaflex at 30.80%. Meanwhile the Backpacks category sees Champion and Adidas recording significant price jumps of 29.6% and 23.6%, respectively.

    Brands with highest price increases across Back to School categories 2022-23

    Ubrands and Pentel from Basic School and Office Supplies Category also record high price increases at 22.70%, followed by Carolinapd from the Themebooks & Portfolios Category at 21.08%. 3M in Mailing in Shipping Supplies shows the lowest price increase at 6.80%.

    Interestingly, the ever popular Writing Instruments category showcases BIC at the forefront, exhibiting the most notable price escalation of 13.2%. Expo trails closely at 11.6%, while Uniball demonstrates an 11.4% increase. Even Sharpie, a beloved writing brand, displays a modest price uptick of 9.3%.

    The average price increments seen across brands mirror the overarching trend of increased costs throughout back-to-school categories.

    Navigating the Competitive Pricing Landscape During the Back-To -School Season

    Given the challenging pricing landscape during the back-to-school season, retailers would be wise to provide lower-cost alternatives alongside popular brand names. This allows parents to easily make substitutions while adhering to a school supplies list.

    With our competitive pricing intelligence solution, retailers can confidently analyze and monitor their prices relative to competition, ensuring they maintain a leadership position in pricing within their desired set of products, while posturing for margins with other products.

    To learn more about how we can help, reach out to us today!

  • DataWeave Launches PricingPulse: Empowering Retail Leaders With Comprehensive and Strategic Pricing Insights

    DataWeave Launches PricingPulse: Empowering Retail Leaders With Comprehensive and Strategic Pricing Insights

    In the evolving retail landscape, success often hinges on a singular focal point: pricing. A recent Statista survey revealed that 70% of US online users prioritize competitive pricing in their digital shopping choices. In this cutthroat arena, where surpassing rivals is paramount, a deep comprehension of pricing nuances is no longer just an edge, but a necessity.

    Retailers are increasingly adopting pricing intelligence solutions that meticulously dissect competitor pricing data in comparison to their own, down to the SKU level. This analysis empowers their pricing teams with the insights they need to price their products competitively on a day-to-day basis.

    However, in a landscape where a staggering 50 million price changes occur daily, reliance on a reactive pricing intelligence solution, though effective in many ways, often falls short. To develop a strategic and predictive pricing engine, retailers also need the ability to track historical pricing relative to market conditions, competitor actions, seasonality, promptness of competitor pricing actions, and more. This would be particularly useful for senior retail pricing and business unit leaders as they look to gain a strategic perspective on their competitive pricing health. However, even today’s leading providers of retail pricing intelligence solutions lack in this area. This results in a relatively myopic view of competitive pricing even in large retail organizations.

    Introducing DataWeave’s PricingPulse

    DataWeave’s PricingPulse helps retail leaders better understand their competitive pricing strategies in comparison to relevant market dynamics over time. The capability bridges the gap between day-to-day competitive pricing operations and long-term strategic pricing analysis and actions, enabling senior retail pricing leaders to untangle the complexities of their pricing strategies. Delivered as a dashboard, the view offers an elevated vantage point for industry-wide pricing dynamics, empowering retailers with the foresight needed to navigate market shifts, predict vulnerabilities, and capitalize on new opportunities.

    PricingPulse is provided to all DataWeave retail customers as an add-on to our Pricing Intelligence solution.

    The insights offered by PricingPulse enable retailers to answer pivotal questions about competitor pricing behaviors, price leadership across categories, timing of price changes, and the effectiveness of capitalizing on price improvement opportunities. Some of the questions that PricingPulse offers answers to include:

    • How frequently are my competitors changing prices and for which products?
    • How does my price leadership vary across key product categories?
    • Which day of the week or month do my competitors change their pricing most and least frequently?
    • How well do I seize on price improvement opportunities over time?

    Strategic Pricing Views Via PricingPulse

    In the following section, we share a few views available to retail leaders via our PricingPulse dashboard. For a complete list of insights available on the dashboard, request a demo today.

    Competitive Price Leadership Across Retailers and Categories

    This view provides retailers with an overview of the price leaders across various product categories and how it changes with time. More often than not, retailers would aim to gain price leadership in certain categories, while maintaining healthy margins in others.

    Retailers can also gauge their consistency and effectiveness in maintaining a competitive edge for key categories over time. They can fortify areas of strength and identify opportunity areas to optimize their pricing.

    In addition, the dashboard tracks a retailer’s price index across categories, a measure that determines its price competitiveness.

    The price index is determined by dividing the retailer’s price by the lowest price offered by any of its competitors. A ratio lesser than 1 indicates that the retailer is the lowest priced in the market. This measure is also presented for competitors, providing insights into competitors that are most attractively priced in the market. A timeline trend of this metric helps track how price leadership among retailers changes over time.

    Price Change Trends

    This view provides a summary of the level of price changes by a retailer and its competitors over a period of time, which includes the average magnitude of price changes as well as the proportion of the retailer’s assortment that underwent these price changes.

    In addition, the number of price changes each month are provided for each retailer. This is further broken down into the total number of price changes during each day of the week.

    These insights help retailers determine which competitors are most and least active in their pricing activities, how aggressive the pricing actions are, and if there are any specific price change patterns followed in terms of the days of the week or month.

    Price Improvement Opportunities and Actions

    The dashboard actively reports on price improvement opportunities, which could include either a price increase opportunity or a price decrease opportunity, for a retailer and its competitors across categories over time. A price increase opportunity occurs when a product is significantly under priced (by more than 2%) and a price decrease opportunity occurs when a product is significantly overpriced (by more than 2%).

    Further, the retailer gains insight into how many price improvement opportunities were actually acted on within 15 days of the opportunity presenting itself. This “action rate” helps retailers quantify how well they seize on price improvement opportunities, which eventually result in higher sales and margins. The dashboard also reports on the average number of days it took for a retailer to act on a price improvement opportunity, thereby quantifying the responsiveness and agility of pricing teams.

    This is especially useful for pricing leaders to “audit” or evaluate the performance of their pricing teams. When similar insights are viewed for a set of competitors as well, retailers can better understand the level of sophistication of their competitors’ pricing operations.

    Ready to Elevate Your Pricing Game?

    The launch of DataWeave’s PricingPulse marks a significant advancement in the realm of pricing solutions for retail leaders. As the retail landscape undergoes continuous transformation, the significance of precise pricing strategies cannot be overstated. PricingPulse is the first and only pricing view in the industry to bridge the gap between tactical pricing decisions and comprehensive strategic analysis.

    In a world where agility and foresight are crucial, PricingPulse equips retail leaders with the ability to predict competitor actions, optimize pricing strategies, and stay ahead of the competition.

    If you are a senior pricing leader or retail business unit head, reach out to us today to either sign up or learn more!

  • Amazon India’s Pricing and Discounts on Prime Day 2023: A Deep Dive Analysis Across Leading Categories and Brands

    Amazon India’s Pricing and Discounts on Prime Day 2023: A Deep Dive Analysis Across Leading Categories and Brands

    Amazon’s India Prime Day 2023 shattered previous records with a peak of 22,190 orders received in a minute. An important aspect of Amazon’s India Prime Day was the benefits it offers to Prime Members. Thousands of sellers, brands, and bank partners collaborated to help Prime members save a staggering sum of over Rs. 300 Crores. The 2 day (July 15-16) event even witnessed strong growth in Prime membership, with 14% more members shopping than last year’s Prime Day event. 45,000+ new products were launched by over 400+ top Indian and global brands.

    However, our analysis reveals that Amazon was able to make a huge splash despite adopting a relatively modest discounting strategy for the event.

    Pricing and Discounts on Prime Day 2023

    While Prime Day is Amazon’s showstopper, bringing huge benefits to partner brands and sellers, it’s interesting to also see how Flipkart responded to such a massive sale by its biggest competitor. Therefore, we leveraged our proprietary data aggregation and analysis platform to analyze the prices and discounts of Amazon and Flipkart across key product categories – Apparel, Home & Furniture, Consumer Electronics, and Health & Beauty – during Prime Day.

    Since products on Amazon and other eCommerce websites are often sold at discounts even on normal days not linked to a sale event, we delved into the real value that Prime Day offers to shoppers by focusing on price reductions or additional discounts during the sale compared to the week before. As a result, our approach highlights the genuine benefits of the event for shoppers who count on lower prices during the sale.

    Research Methodology

    For our analysis, we tracked the prices of a large number of products across Amazon and Flipkart during Prime Day as well as the week prior to the event. The details of our sample are mentioned below:

    • Number of SKUs: 85,000+
    • Retailers: Amazon, Flipkart
    • Categories: Apparel, Home & Furniture, Consumer Electronics, Health & Beauty
    • Pre-event Analysis:10-14 July 2023
    • Prime Day Analysis: 15-16 July 2023

    Our Findings

    Based on our analysis, Prime Day showcased relatively higher price reductions in the Health and Beauty category, offering an average additional discount of 5.3%. In comparison, the Apparel category had lower discounts at 4.90%, followed by the Home & Furniture category at 2.50% during the sale event.

    Average price reduction on Amazon on Prime Day across categories.

    The Consumer Electronics category, known for attractive prices during sale events, featured only 0.9% price reductions. This is due to the fact that the category was already being sold at a very high average discount of around 44.8% the week prior to Prime Day.

    Below, we delve deeper into our analysis of each category to better understand how price reductions were distributed across key subcategories on Amazon. We also report on the degree to which Flipkart responded to Amazon’s pricing actions during the event.

    Apparel

    As Amazon grappled with heightened costs and reduced profit margins in apparel (like most other retailers), its average discount before Prime Day was already at 36.5%. Then, on Prime Day, Amazon’s apparel deals were tempered at around 4.9% average price reduction across 43.7% of its assortment.

    Flipkart, on the other hand, offered only a modest additional discount of 1.8% across 17.7% of its Apparel assortment. It’s clear that while Flipkart took steps to compete against Amazon in this category, it was done to a lower extent on fewer products than Amazon.

    Apparel average price reduction across retailers on Prime Day.

    Across all the apparel subcategories we analyzed, Men’s Shoes (11.6%), Women’s Shoes (9.5%), and Men’s Shirts (8.7%) were among the ones with the highest price reductions. On the other hand, Men’s and Women’s Swimwear (2.3%), Women’s Innerwear (2.9%), and Women’s Athleisure (3.3%) had conservative markdowns.

    Apparel average price reduction across subcategories on Amazon.

    Pricing choices within different subcategories likely stemmed from a range of factors, such as inventory quantities, trends in demand, and the aim to harmonize competitive deals with the maintenance of viable profit margins. These decisions reflect Amazon’s attempt to cater to a consumer base that is particularly conscious of pricing.

    Across all apparel subcategories, leading brands that offered the highest markdowns were Sweet Dreams (65.5%), Ketch (55.1%), Clarks (44.9%), and Kibo (38.4%). Meanwhile, Reebok and Adidas offered significant additional discounts at 26.3% and 24.9%, respectively, as well.

    Apparel average price reduction across leading brands on Amazon.

    For brands, however, reducing prices is just one approach to entice shoppers. They must also guarantee their prominent presence and easy discoverability within Amazon’s search results. This significantly amplifies their potential to generate higher clicks and conversions. In our analysis, we monitored brands’ Share of Search across various frequently used search terms in addition to the discounts they provided. The Share of Search denotes the portion of a brand’s products within the top 20 search results for a specific search query.

    Our data indicates that certain brands gained ground in their discoverability during Prime Day, while others fell behind. Van Heusen in Women’s Athleisure (30%), Campus in Men’s Shoes (50%), and Rovar’s (30%) in Women’s Swimwear among others, improved their Share of Search by significant levels during Prime Day.

    Apparel share of search on Amazon on Prime Day.

    On the other hand, brands like Sparkx in Men’s Shoes, Xyxx in Men’s Innerwear, WomanLikeU in Women’s Swimwear, and Adidas in Women’s Shoes lost around 40%-80% in their Share of Search during the event. This is likely to have impacted their sales volumes adversely.

    Home & Furniture

    The Home & Furniture industry faced challenges of reduced demand and overstocked inventory over the past year. Therefore, even before Prime Day, discounts offered in this category on Amazon averaged a staggering 45.3%. Consequently, on Amazon Prime Day, additional discounts averaged only 2.5% on Amazon, offered across 33.3% of its assortment. Flipkart opted, in effect, not to compete with Amazon in this category, offering a negligible additional discount of 0.8% across 14.70% of its assortment.

    Home & furniture average price reduction across retailers on Prime Day.

    Of all the Home & Furniture subcategories we analyzed, Luggage (5.1%), Beds (3.9%), and Coffee Tables (3.1%) had high price reductions, while Rugs (0.6%), Bookcases (1.5%), and Washer/Dryers (1.2%) had lower markdowns. This highlights the difference in consumer preferences across geographies, with rugs being more discretionary in India but staple in the US.

    Home & furniture average price reduction across subcategories on Amazon.

    The Home & Furniture category is not known for its brand loyalty among shoppers. Therefore, brands often rely on attractive pricing to gain shopper interest. This Prime Day, brands that offered the highest markdowns in this category include It Luggage (40%), Couch Culture (25.8%), Story@Home (23.3%), and Verage (21.2%).

    Home & furniture average price reduction across leading brands on Amazon.

    In terms of Share of Search, Wudparadise in Entertainment Units gained the highest (50%). Solimo (an Amazon Brand) in Beds (40%), Sofas (30%), and Coffee Tables (10%) gained significant ground in its respective categories too. In contrast, About Space in Bookcases (-60%), Anika in Entertainment Units (-40%), and Sleepyhead in Mattresses (-40%) lost out on their discoverability in their respective categories during the event.

    Home & furniture share of search on Amazon on Prime Day.

    To gain a competitive edge during sale events like Prime Day, brands need to monitor their Share of Search closely, especially in categories like Home & Furniture with low brand loyalty.

    Consumer Electronics

    This Prime Day, five smartphones got sold every second with 70% of the demand coming from Tier 2 & 3 cities in India, largely comprising of foldable smartphones and newly launched smartphones (OnePlus Nord 3 5G, Samsung Galaxy M34 5G, Motorola Razr 40 Series, Realme Narzo 60 Series and iQOO Neo 7 Pro 5G). Multiple new products were launched this Prime Day, by brands such as OnePlus, iQOO, Realme Narzo, Samsung, Motorola, boAt, Sony, and more in India.

    Consumer electronics average price reduction across retailers on Prime Day.

    Despite the high demand and new product launches, Amazon’s price reductions in the Consumer Electronics category averaged only 0.9% across 27% of its assortment. Similar to what we observed in the Home & Furniture category, this can be attributed to the prevailing high average discount of 44.8% the week prior to Prime Day. Essentially, in Consumer Electronics, shoppers needn’t always wait till sale events like Prime Day to view the most attractive deals. Several are offered even during the days leading up to the sale.

    Across subcategories, Earbuds (2.4%), Wireless Headphones (1.6%), and TVs (1.3%) received the highest price reductions due to their popularity and high sales volumes during sales events. On the other hand, Smartwatches (0.6%), Drones (0.4%), and Smartphones (0.3%) had lower markdowns.

    Consumer electronics average price reduction across subcategories on Amazon.

    In terms of price reductions across brands, Da Capo (52.6%), Muzen (33.3%), JLab (23.6%), and Earboss (21.5%) offered the most attractive deals in the Consumer Electronics category. Notably, Amazon Basics also offered modestly attractive deals (12.2%), highlighting Amazon’s strategy of promoting in-house brands.

    Consumer electronics average price reduction across leading brands on Amazon.

    The Consumer Electronics category has a loyal shopper base, but generic search keywords like earbuds, headphones, and tablets remain essential for attracting high-intent shoppers and increasing brand awareness. So when it comes to Share of Search, Noise in Smartwatches, Samsung in Smartphones and Tablets, and HP in Laptops, all made strong strides in building their discoverability on Amazon during Prime Day.

    Consumer electronics share of search on Amazon on Prime Day.

    Xiaomi in Laptops, Ekko in Earbuds, OnePlus in Smartphones and Apple in Tablets, lost out to other brands during the sale.

    Health & Beauty

    Health & Beauty emerged as the top-performing category in terms of additional discounts during Prime Day in India. Our data shows that Amazon offered an average additional discount of 5.3% on almost half of its products (46.8%) in this category. Competing head to head with Amazon in this category, Flipkart offered 5.5% additional discounts across 35.8% of its assortment.

    Health & beauty average price reduction across retailers on Prime Day.

    Within all the subcategories we analyzed, Sunscreen (7.5%), Make-Up (7.2%), Shampoo (6.6%), and Moisturiser (6.4%) saw the highest price reductions on Amazon. Conversely, staple items like Toothpaste (3.%) and Beardcare (3.6%) had lower markdowns.

    Health & beauty average price reduction across subcategories on Amazon.

    During the sale event, brands like Sadhev (43.4%), Clear (41.1%), Teenilicious (40.4%), and Coal Clean Beauty (38.4%), offered the most attractive deals.

    Health & beauty average price reduction across leading brands on Amazon.

    In terms of significant gains in Share of Search for brands, L’Oreal Paris in Shampoo and Conditioner led the pack along with Oracura in Electric toothbrushes and The Formularx in Moisturiser. Perfora in Toothpastes and Ustraa in Beardcare also gained more than 10% in their Share of Search during the sale event.

    Health & beauty share of search on Amazon on Prime Day.

    Other popular brands like Tresemme in Conditioners, and Swiss Beauty in Make-Up surprisingly had reduced visibility among the top search results for relevant subcategories.

    Navigating the Competitive Landscape: How To Thrive During Sale Events

    Amazon’s strategic pricing during Prime Day reflects a balance of profitability, inventory, and competition. Competitive pricing insights empower retailers to make informed decisions, optimize strategies, and thrive during high-stakes events. Prime Day serves as a crucial opportunity to drive sales, attract new customers, and boost loyalty. Therefore, monitoring competitor prices accurately, at scale, is essential for impactful pricing strategies.

    For more insights on staying ahead during sale events, reach out to us today!

    If you’d like to learn about Amazon’s pricing and discounts during Prime Day 2023 in the US, check out our analysis here.

  • Amazon US Prime Day 2023: Insights on Pricing and Discounts Across Popular Categories and Brands

    Amazon US Prime Day 2023: Insights on Pricing and Discounts Across Popular Categories and Brands

    Amazon’s Prime Day this year proved to be a record-breaking success, becoming the largest Prime Day event in the company’s history. Over the two-day extravaganza, shoppers in the US spent a staggering $12.7 billion, a 6.1% increase from the previous year. Amid inflationary pressures and supply chain disruptions, Amazon adopted a bold discounting strategy, offering steeper discounts compared to Prime Day 2022.

    An interesting aspect of Amazon’s approach is their loyalty based offerings. In the weeks leading to Prime Day on July 11-12, members of the loyalty program were given access to “invite-only deals” where shoppers could request invites to specific products that they were looking to purchase on deals. Overall, Amazon’s pricing and discount strategies during Prime Day were carefully designed to create a buzz among shoppers, generate increased sales, and maintain a competitive advantage in the market.

    While Prime Day is Amazon’s showstopper, it’s interesting to also see how other leading retailers respond to such a massive sale by their biggest competitor. Do they also lower their prices during the event, or are they happy to take a backseat? To answer these questions, we leveraged our proprietary data aggregation and analysis platform to analyze the prices and discounts of Amazon and its leading competitors across key product categories – Apparel, Home & Furniture, Consumer Electronics, and Health & Beauty – during Prime Day.

    Since products on Amazon and other eCommerce websites are often sold at discounts even on normal days not linked to a sale event, we delved into the real value that Prime Day offers to shoppers by focusing on price reductions or additional discounts during the sale compared to the week before. As a result, our approach highlights the genuine benefits of the event for shoppers who count on lower prices during the sale.

    Research & Methodology

    For our analysis, we tracked the prices of a large number of products across several leading retailers during Prime Day as well as the week prior to the event. The details of our sample are mentioned below:

    • Number of SKUs: 110,000+
    • Websites: Amazon, Walmart, Target, Overstock, The Home Depot, Wayfair, Ulta Beauty, Sephora
    • Categories: Apparel, Home & Furniture, Electronics, Health & Beauty
    • Pre-event Analysis: 4-10 July 2023
    • Prime Day Analysis: 11-12 July 2023

    Our Key Findings

    Our data reveals that Amazon’s price reductions were most aggressive in the Consumer Electronics category, with an average price reduction of 10.4% on Prime Day, due to the category’s popularity and high demand.

    The Health & Beauty (6.7%), Apparel (5.9%), and Home & Furniture (4.8%) categories offered relatively modest deals during the sale event.

    The Health & Beauty (6.7%), Apparel (5.9%), and Home & Furniture (4.8%) categories offered relatively modest deals during the sale event.

    Below, we delve deeper into our analysis of each category to better understand how price reductions were distributed across key subcategories on Amazon as well as the discounting strategies of Amazon’s leading competitors.

    Apparel

    As Amazon grappled with surplus inventory, heightened storage costs, and reduced profit margins in apparel (like most other retailers), its average discount before Prime Day was already as high as 13.3%. Then, on Prime Day, Amazon’s apparel deals were tempered at around 5.9% across an impressive 33.1% of its assortment, while Target and Walmart chose not to compete in a meaningful way.

    Unlike Prime Day 2022, when Target competed with Amazon with high discounts, the retailer offered only 0.8% additional discount across 4.4% of its assortment in this category. Walmart, too, reduced its prices by only 1.4% on 8.5% of its assortment during Prime Day.

    Check out our latest analysis on fashion pricing trends across 2022-23 to better understand the pricing dynamics in this category in greater detail.

    Across all the apparel subcategories we analyzed, Women’s Athleisure (8.7%), Men’s Swimwear (8%), and Women’s Tops (7.6%) were among the ones with the highest price reductions. On the other hand, Men’s Athleisure (2.5%), Women’s Shoes (3.5%), and Men’s Innerwear (4.1%) had conservative markdowns.

    Pricing decisions across the various subcategories are likely to have been influenced by several factors like inventory levels, demand patterns, and the need to balance competitive offers with maintaining reasonable profit margins, as Amazon tried to cater to a more price-sensitive consumer.

    Across all apparel subcategories, leading brands that offered the highest markdowns were Tommy Hilfiger (11.5%), Amazon Essentials (9.4%), Adidas (8.6%), and Calvin Klein (8.6%).

    For brands, however, lowering prices is only one lever to attract and convert shoppers. They also need to ensure they’re highly visible and discoverable on Amazon’s search listings. This exponentially improves their chances of driving more clicks and conversions. In our analysis, we tracked the Share of Search of brands across several popular search keywords. Share of Search for a brand is defined as the proportion of the brand’s products in the top 20 search results for a search query.

    Our data indicates that several brands gained impressive ground in their discoverability during Prime Day, while others fell behind. Gildan in Men’s Innerwear, Adidas in Men’s and Women’s Shoes, Anrabess in Women’s Athleisure, and Lululemon in Men’s Athleisure, among others, improved their Share of Search by significant levels during Prime Day.

    On the other hand, brands like Hanes in Men’s and Women’s Innerwear, Kanu Surf in Men’s Swimwear, Cupshe in Women’s Swimwear, and others lost around 10% in their Share of Search during the event. This is likely to have impacted their sales volumes adversely.

    Home & Furniture

    The Home & Furniture industry has been challenged with reduced demand due to inflationary pressures over the past year or so. Leading retailers in the category overestimated the demand, leading to overstocking of inventory. As a result, Home & Furniture is one of the few categories that saw Amazon’s competitors participate at a significant level on Prime Day in order to ensure they don’t fall behind on liquidating their stock.

    Amazon’s additional discounts averaged 4.8% across 30.2% of its assortment. Wayfair and Overstock too reduced their prices by 4.8% and 4.3% on around 44% of their respective assortments. Wayfair’s move is likely a part of their strategy to attract new customers and expand their market share, in response to a decline in their consumer base. Last year, Wayfair experienced a loss of 5 million out of its 1.3 billion consumers due to weakening demand.

    Target and Walmart did offer additional discounts, but they were not at a competitive level. The Home Depot effectively opted not to compete at all during the sale event. Overall, the pricing actions of these retailers are in stark contrast to the highly conservative pricing strategies observed on Prime Day last year.

    Our recent pricing analysis of the Home & Furniture category revealed more interesting insights and pricing dynamics over the past year.

    Across all the subcategories we analyzed, Bookcases (8.2%), Rugs (7.8%), Mattresses (6.5%), and Luggage (6.2%) were among the ones with high price reductions.

    Meanwhile, Sofas (2.4%), Washer / Dryers (2.4%), and Entertainment Units (2.7%) had lower markdowns. These are large and substantial purchases, making retailers more cautious about deeply discounting them while still ensuring profitability.

    The brands that stepped up and offered the highest markdowns in this category include Zinus (20.2%), Comfee (10.8%), Sauder (9.9%), and Best Choice Products (8.7%).

    In terms of Share of Search, Rockland in Luggage gained the highest (21%), followed by Farberware in Dishwasher, Olee Sleep in Mattresses, and Homeguave in Mattresses gained significant ground in their respective categories as shown in the image below.

    Brands like Best Choice Products in Coffee Tables, Molblly in Mattresses, and Black+Decker in Washer/Dryers and Dishwashers lost a good portion of their Share of Search during the event. Due to high competition for visibility during sale events, brands that fail to keep an eye on their Share of Search stand to take a hit in their sales, especially in categories like Home & Furniture that tend to have low brand loyalty.

    Consumer Electronics

    2023 was the year of consumer electronics on Amazon Prime Day. Amazon’s price reduction during the sale averaged 10.4% across 54.5% of its assortment in the category. Target and Walmart, on the other hand, offered significantly lower additional discounts of 1.9% and 2.7% on 10.4% and 19.1% of their assortment, respectively.

    The consumer electronics category often witnesses aggressive price reductions during Prime Day and other sale events due to its popularity and high demand. In addition, since retailer margins are usually low in this category, shoppers often have to wait for sale events like Prime Day (when brands markdown their wholesale rates) to have several attractive deals to choose from.

    Across all the subcategories we analyzed, Smartwatches (15.4%), Wireless Headphones (15.4%), Earbuds (14.9%), Headphones (12.5%), and Tablets (12.0%), were among the ones with the highest price reductions. All of these subcategories are quite popular that tend to sell in large volumes during sale events.

    Meanwhile, Laptops (2.1%), TVs (3.1%), and Smartphones (7.6%) had lower markdowns. A lower markdown on smartphones may reflect steady demand throughout the year, reducing the urgency to offer significant discounts during the short Prime Day window.

    Amazon (22%), Tozo (12.5%), Lenovo (10.8%), JBL (8.3%), and Apple (5%) offered the highest price reductions in Consumer Electronics as a whole. Clearly, Amazon didn’t hold back on offering attractive deals on its own private label products in this category.

    Consumer Electronics as a category tends to have a brand loyal shopper base. However, Share of Search generic search keywords are still very important for keywords like earbuds, headphones, and tablets that result in relatively lower priced products. HP in Laptops, Samsung in Tablets and TVs, and Oneplus in Smartphones all made strong strides in building their discoverability on Amazon during Prime Day. Beyond just driving more sales, this also has the intended effect of boosting brand awareness among high-intent shoppers.

    Sony in Headphones, Asus in Laptops, and Insignia in TVs lost out to other brands in terms of their discoverability during the sale. Sony and Asus, especially would be hurting as they are prominent brands in their respective categories.

    Health & Beauty

    The Health & Beauty category is a favorite among consumers during Prime Day, as it encompasses a wide range of products like skincare, cosmetics, and grooming items. As shoppers often tend to stock up during the sale, brands and retailers are willing to offer competitive discounts and gain an edge over their competitors.

    Our data reveals that the average additional discount on Amazon was 6.7%, offered on a little over a third of its assortment. Walmart reduced its prices sizably as well, by an average of 3.1% on 13.4% of its assortment.

    Interestingly, Sephora and Ulta Beauty, leading retailers in the Health & Beauty category did not compete on price at all this Prime Day. It is likely they are confident their loyal customer base will not be influenced by Amazon’s Prime Day deals and be driven away merely by lower prices. In addition, keeping their prices steady during Prime Day might have been a strategic choice to protect their brand reputation and premium positioning.

    Relatively premium subcategories like Electric Toothbrushes (10%), Moisturizer (8.3%), Beardcare (7.3%), and Make Up (6.7%) saw the highest price reductions on Amazon.

    In contrast, staple items like Toothpaste (3.7%), Shampoos (5.4%), and Conditioners (5.7%) had lower markdowns.

    Among the leading brands in this category, Oral-B (10.3%), Philips Sonicare (8.7%), Neutrogena (8.4%), and Colgate (5.6%) offered the most attractive deals during the sale event.

    In terms of significant gains in Share of Search for brands, Oral-B in Electric Toothbrushes led the pack again. Neutrogena in Sunscreens and Somall in Toothpastes also gained more than 10% in their Share of Search during the sale event, followed by Tresemme in Shampoos and Airspun in Make-Up products.

    Other popular brands like Crest in Toothpastes, e.l.f in Make-Up, Philips Sonicare in Electric Toothbrushes, and Sheamoisture in Beradcare surprisingly had reduced visibility among the top search results for relevant subcategories.

    Staying Ahead of the Curve During Sale Events

    This Prime Day, Amazon leveraged its scale to offer aggressive discounts across key product categories, while several competing retailers chose to sit back and let the sale play out. Others chose a selective discounting strategy that focused their modest price reductions on a small set of items.

    At DataWeave, we understand the pivotal role competitive pricing insights play in empowering retailers and brands to gain a competitive edge, especially during crucial events like Prime Day. For retailers, the ability to track competitor prices accurately, at scale, in a timely manner is essential to plotting and acting on impactful pricing strategies and staying ahead of the curve.

    To learn more about how this can be done, reach out to us today!

  • Navigating the Turbulent Home and Furniture eCommerce Market in 2023 with the Power of Competitive Intelligence

    Navigating the Turbulent Home and Furniture eCommerce Market in 2023 with the Power of Competitive Intelligence

    The home and furniture retail industry is going through a turbulent time. As inflation reared its head mid-2022, leading retailers in the category have been grappling with the higher costs associated with producing and distributing their products, as well as reduced shopper demand. The rising costs of raw materials, transportation, and labor have had a direct impact on the pricing dynamics within the industry. For example, reports indicate container rates soared to nearly 10 times pre-pandemic levels towards the end of 2021.

    Furthermore, shoppers’ spending power has been constrained, while higher interest rates have suppressed demand. Retailers have had to adapt their assortment and pricing strategies to cater to a wider range of shopper preferences driven by changing lifestyles and a growing emphasis on sustainability. Post-pandemic, demand has been primarily driven by affluent shoppers.

    Towards the end of 2021, due to supply delays and disruptions, retailers heavily stocked up on available products. However, when demand subsequently decreased in 2022, they were left with a significant amount of unsold stock that was purchased at high rates. This put them in a difficult situation, as they had an excess of products but were unable to sell them even at reduced prices without impacting their profit margins. Additionally, staying competitive in a rapidly changing market environment was equally important.

    Given this context, it is crucial for home and furniture retailers to adopt a data-driven approach that utilizes competitive and market insights to consistently maintain or increase their online sell-through rates. DataWeave’s Commerce Intelligence solution offers exactly that, empowering retailers across various industry segments to stay updated on evolving consumer trends and competitor actions.

    To gain a better understanding of the pricing strategies employed by leading home and furniture retailers throughout the past year, we leveraged our proprietary data aggregation and analysis platform to track and analyze the pricing of a wide range of products across multiple retailers and subcategories within the industry.

    Our Research Methodology

    • Number of SKUs: 400,000+
    • Key retailers tracked: Amazon, Wayfair, Home Depot, Overstock, Target, Walmart
    • Key categories reported: Home and Office, Bed and Bath, Bathroom, Bedroom, Decorative, Dining Room, Kitchen, Garden & Patio, Hardware
    • Timeline of analysis: April 2022 to April 2023

    Our Findings

    Interestingly, our analysis indicates that average prices in the home and furniture category rose by around 5% between March 2022 and April 2023. However, there have been seasonal fluctuations in the prices over the course of the year.

    Among the various subcategories, the most substantial price surge was observed in home office equipment, with an uptick of 9.3% in January 2023 when compared to March 2022. The surge in demand for home office furniture, fueled by the widespread adoption of work from home arrangements, played a pivotal role in depleting inventories and consequently driving up prices. Additionally, the shift towards collaborative workspaces and the gradual expansion of office environments have contributed to the sustained demand for office furniture.

    Avg. price changes MoM across home and furniture subcategories from April 2022-23.

    While prices for several subcategories rose significantly, others experienced subdued growth, such as bed and bath. The subcategory experienced the lowest price increment, registering a modest 2.8% increase annually. This can be attributed to the impact of a subdued housing market and a decrease in first-time buyers, which may partly be due to the global recession and inflationary pressures.

    Moreover, retailers overestimated the demand for home furniture during the holiday season, leading to an overstocking of inventory. Consequently, prices experienced a dip from October to December 2022. In fact, this was a common trend across all home and furniture subcategories. As retailers emerged from the holiday season, prices rose to their highest level in January 2023, and have stayed relatively stable since.

    Some of these trends vary among retailers as each faces different challenges and responds in distinct ways.

    Wayfair, for example, shows a significant dip in pricing after October 2022, with prices stabilizing in 2023. This could be in response to the retailer’s shrinking consumer count, losing 5 million of its 1.3 billion consumers in 2022 due to declining demand.

    Avg. price change MoM within the home and furniture sector across retailers from April 2022-23.

    In fact, online furniture retailers like Wayfair and Overstock reported declines in annual revenue in 2022, as the furniture sector continued to normalize from the high spending seen during COVID-era lockdowns. Wayfair reported that its 2022 net revenue was $12.2 billion, down almost 11% from the year prior. The company also laid off 10% of its workforce in August 2022. Overstock’s reported annual net revenue in 2022 was $1.9 billion, a 30% decrease year-over-year.

    Interestingly, both companies took contrasting approaches in response to this situation. Wayfair opted for aggressive cost-cutting measures, including layoffs and a reduced marketing budget. On the other hand, Overstock focused on attracting new customers through influencer marketing and improving their app, aiming to expand their customer base. With a strategy geared towards younger buyers, Overstock allocated a larger marketing budget than ever before. Our data supports the fact that Overstock did not rely on price reductions to entice shoppers.

    Target has consistently maintained lower price increases compared to Walmart, defying the common perception of Walmart being more conservative in its pricing. Notably, Amazon also stood out minimal price increases throughout the year, being surpassed only by Wayfair since November 2022.

    As price sensitive shoppers increasingly compare prices before making a purchase decision, retailers need to ensure they are priced competitively in the market on a consistent basis to liquidate stock and gain market share without compromising significantly on margins.

    A Sophisticated and Versatile Product Matching Solution is Essential to Achieving Price Leadership

    Product matching plays a vital role in monitoring competitive prices and analyzing price leadership. Within the home and furniture category, there is often a multitude of representations for the same product across various online platforms. Furthermore, eCommerce websites offer a wide array of options, including variations in size, color, material, and similar products. Without an accurate and comprehensive method of matching these products, it becomes impossible to track and compare prices effectively, especially on a large scale. Thus, a versatile product matching engine tailored to the unique requirements of the home and furniture sector becomes essential.

    DataWeave offers an industry-leading product matching platform that harnesses advanced AI models specifically trained to identify and leverage multiple product attributes extracted from titles, descriptions, and images to accurately match products across websites. Additionally, our platform intelligently matches similar products based on a diverse range of extracted attributes. This empowers our retail partners to gain competitive pricing intelligence not only on exact product matches but also on similar and substitute products, as well as their respective variants.

    With our competitive pricing intelligence solution, retailers in the home and furniture industry can confidently analyze and track prices, ensuring they stay at the forefront of price leadership in their market.

    To learn more, reach out to us today!

  • Fashion eCommerce 2023: Leveraging Pricing Intelligence to Stay Competitive Despite Reduced Demand

    Fashion eCommerce 2023: Leveraging Pricing Intelligence to Stay Competitive Despite Reduced Demand

    The fashion industry is currently undergoing a period of stabilization after facing significant disruptions in recent years. Fashion retailers find themselves navigating not only changing consumer preferences but also the challenges brought about by inflation and supply chain issues that are remnants of the COVID-19 era.

    The effects of inflation have raised concerns regarding overabundance, rise of sustainable and pre-used fashion and declining sales, creating a mismatch between supply and demand within the market. As consumers scale back on spending due to rising prices, fashion retailers are left grappling with surplus inventory, heightened storage costs, and reduced profit margins.

    Consequently, these market dynamics have significantly impacted the pricing strategies employed by fashion retailers, resulting in dynamic shifts in pricing and competitiveness across different time periods, subcategories, and individual retailers.

    Counteracting this impact requires fashion retailers to adopt a data-driven approach that leverages competitive and market insights. They must adopt agile and versatile pricing strategies that enable advanced pricing and assortment management. By understanding their market position and the competitive landscape, retailers can effectively react to reduced demand and inflationary pressures without compromising heavily on their top line and profitability.

    At DataWeave, we harnessed the power of our proprietary data aggregation and analysis platform to track and analyze the prices of prominent fashion retailers to uncover unique insights into their price competitiveness over the past year, as well as understand how pricing strategies varied across diverse subcategories.

    Our Methodology

    For this analysis, we tracked the average price changes among leading US fashion retailers over 12 months to understand how their pricing across several fashion subcategories altered in response to supply chain inefficiencies, inflationary pressures, seasonal effects, and changing consumer preferences.

    • Sample: 88,000+ SKUs matched across 5 leading retailers
    • Retailers tracked: Amazon, Walmart, Target, Macy’s, Zappos
    • Key subcategories reported on: Boots, Bottoms, Coats, Denims, Flats, Heels, Jackets, Kids
    • Timeline of analysis: April 2022 to April 2023

    Our Analysis

    While prices have generally been rising in several industry segments, such as groceries, due to inflation, the fashion sector has experienced relatively stable prices, with even a few periods of price drops. In fact, average prices in April 2023 are 1.2% lower than those in April 2022. The main reason for this trend is that consumers have become cautious about discretionary spending on fashion in order to prioritize other necessities, resulting in lower demand and overstocking by retailers.

    In the first quarter of 2022, clothing accounted for only 3.9% of total expenditure by US consumers, down from 4.3% in 2019 before the pandemic. Additionally, in March 2023, 60% of fashion retailers in the US still had surplus goods, accounting for almost 20% of their entire stock. As demand decreased, fashion retailers started offering freebies with purchases, bundling products, giving away unwanted items, and notably, slashing prices.

    Subcategory level analysis of Average Price Change Month-on-Month between April 2022 – April 2023

    Our analysis at a subcategory level reveals that in winter 2022, seasonal demand led to the largest price increases of 6-11% in coats, boots, and jackets. However, these prices quickly declined afterward. In 2023, stabilization of raw material costs and a continuing decline in demand for non-essential apparel and fashion accessories are factors contributing to a significant drop in prices.

    Some of these trends vary among retailers as each faces different challenges and responds in distinct ways. Our data indicates that some retailers have chosen to increase their prices from Q3 2022 due to mounting pressure on profit margins, while others have further lowered prices due to increasing inventory levels.

    Average Price Change Month-on-Month Across Amazon, Macy’s, Walmart, Target, and Zappos between April 2022 – April 2023

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    Capability Spotlight

    Matching products across competitor websites is an essential part of tracking competitive prices and analyzing price leadership. In fashion, matching exact products is no mean feat. Websites often host a slew of variants in terms of size, color, material, etc. without any form of standardization in the way the products are represented. So fashion retailers often struggle with simply unusable pricing insights resulting from inaccurate and incomplete product matching. 

    DataWeave’s industry-leading product matching algorithm recognizes and leverages dozens of product attributes extracted from product titles, descriptions, and images to match products at very high levels of accuracy and coverage. What’s more, our platform can also match similar products based on a large variety of parameters, so our customers can benefit from a comprehensive competitive perspective.

    _____________

    For example, in August, Target reported a 90% plunge in profits during the second quarter of 2022, as shoppers concerned about inflation reduced spending on nonessential items. The company stated that its price cuts did not have the desired impact, resulting in a 1.5% increase in inventory compared to three months prior. As a result, we can see that Target’s average fashion prices spiked in August 2022 and have remained steady since then. Walmart also faced similar challenges and increased its prices in October 2022.

    However, during the same period in August 2022, Macy’s announced increased discounts to clear out excess inventory in preparation for the holiday shopping season. In the same announcement, Macy’s highlighted how the rising cost of groceries, which had experienced a double-digit increase, was impacting consumers’ budgets, changing their behaviors, and increasing the need for discounts. Our data reflects this, showing a significant drop in prices from October 2022 to January 2023.

    However, in January 2023, Macy’s successfully managed its inventory levels, reducing them from $6.4 billion in October 2022 to $4.3 billion in January 2023. As a result, average prices at Macy’s have started to rise.

    _____________

    For today’s fashion retailers, achieving a balance between expansion goals and profitability is crucial. It requires a meticulous examination of competitive and market insights on a regular basis to mitigate competitive pressures and navigate through these challenging times successfully.

    DataWeave’s platform offers retailers the insights they need to gain a competitive advantage. With access to accurate, timely, and actionable pricing and assortment insights, retailers can make informed decisions and stay ahead of the competition. To learn more, reach out to us today!

  • Impact of Inflation on Grocery: Pricing Insights on Leading US Retailers

    Impact of Inflation on Grocery: Pricing Insights on Leading US Retailers

    Inflation, like an invisible force, silently shapes the dynamics of economies, gradually eroding the purchasing power of consumers and leaving its imprint on various industries. High costs, hiring lags, and stagnating earnings pose severe challenges to businesses. One industry segment that intimately feels the impact of inflation is grocery, where price increases can be extremely concerning for the average consumer.

    Over the last 12-plus months, the US has experienced a notable rise in inflation, stirring up concerns and influencing the way we shop for everyday essentials. Rising costs of raw materials, transportation, and labor have all played a role in driving up prices. Additionally, disruptions in global supply chains and fluctuations in currency exchange rates have further exacerbated the situation, creating a complex web of interdependencies.

    To understand the magnitude of this phenomenon across leading e-retailers, we delved into an in-depth analysis of four major retail giants: Walmart, Amazon, Target, and Kroger.

    Each of these retailers possesses a unique business model and competitive strategy, as well as faces unique challenges. This leads to distinct approaches to managing inflationary pressures. Walmart for instance, expects operating income growth to outpace sales growth in 2023. Given the persistence of high prices and the potential for further macro pressures, the retailer is taking a cautious outlook. In 2022, Amazon’s eCommerce business swung to a net loss of $2.7 billion, compared to a profit of $33.4 billion the previous year.

    Amid these challenging circumstances, understanding the grocery pricing trends and strategies becomes imperative for retailers, both online and in stores to adapt and thrive in the current economic landscape. By examining their pricing trends, we can gain valuable insights into how these companies navigate the turbulent waters of the grocery industry against the backdrop of inflation.

    Our Research Methodology

    The data collected for our analysis encompassed a diverse range of products, from pantry staples like flour and rice to perishable goods like dairy and produce – a basket of around 600 SKUs matched across Amazon, Kroger, Target and Walmart, between January 2022 to February 2023.

    Further, we separately focused on the prices of a smaller subset of 30+ high-volume daily staples that are likely to yield higher sales and margins for these retailers.

    Average Selling Price of a Broad Set of Grocery Items

    Our analysis reveals that Walmart consistently offers the lowest prices, with an average of 8% below its closest competitor, Target, despite an annual price increase of about 5%. Walmart seems to prioritize a “stability and predictability” strategy over margin optimization. The retailer’s 8% growth last quarter indicates that this strategy is bearing fruit. However, it’s important to note that this approach may have its drawbacks as Walmart’s margins come under pressure.

    Average selling price trend across a basket of 500+ SKUs across Target, Walmart, Kroger, Amazon in the grocery category from Jan ’22 to Feb ’23.

    In order to weather inflationary pressures, Walmart may adopt a cautious approach to growth while also focusing on securing margins. Reports suggest that the retailer has been pushing back against consumer packaged goods (CPG) manufacturers following a series of price hikes to counter inflationary cost pressures in early 2023. One of the reasons behind Walmart’s growth and increased sales can be attributed to ‘non-traditional’ higher-income households now seeking deals and discounts at Walmart as their spending power declines.

    Interestingly, Amazon emerges as the highest-priced retailer, followed by Kroger, which increased its prices by 10% throughout the year. Consumer perception commonly associates Amazon with the lowest prices, but the data tells a different story. In fact, Amazon has been charging 12% to 18% higher prices than Walmart for groceries and is still maintaining its success.

    While the company’s online sales declined by 4%, it saw a significant 9% increase in revenue from third-party seller services, such as warehousing, packaging, and delivery, in 2022. Amazon’s strong logistics and same-day delivery services give it a competitive advantage over other retailers, contributing to its revenue growth and margins. Interestingly, this presents an opportunity for Walmart and other retailers to increase prices while maintaining their strong competitive price positions.

    Kroger, on the other hand, seems to be aiming for a premium price perception, consistently raising prices almost every month. Kroger’s pricing strategy appears to be closer to Amazon’s.

    Average Selling Price for High-Volume Daily Staples

    Pricing strategies often change for different categories of products. To better understand this, we focused our analysis further on a small subset of 30+ high-volume staples across retailers. These include baked goods, popular beverages, canned food, frozen meals, dairy, cereals, detergents, and other similar items.

    Average selling price trend of 30+ high-volume daily staples across Target, Walmart, Kroger, Amazon in the grocery category from Jan ’22 to Feb ’23.

    Walmart, possibly overestimating the impact of inflation, has continued to keep its prices the lowest, potentially aiming to increase margins through volume.

    The level of price disparity across retailers is expectedly lower here, with Amazon and Kroger closely tracking Walmart’s average prices.

    Target’s pricing strategy stands out as it consistently emerges as the highest-priced retailer for daily staples, despite being one of the lower-priced retailers for a broader basket of grocery items. This suggests that Target’s underlying technology may not be as optimized to address market dynamics compared to other leading retailers. In our opinion, Target may want to strengthen its efforts to track pricing more intensely for this sub-category.

    A Data-fuelled Approach is the Need of the Hour

    In the challenging economic landscape, retailers and grocery stores are under pressure to maintain their revenues and margins. Adopting a comprehensive and dynamic pricing strategy is crucial. Understanding which product categories are experiencing price increases among competitors can help retailers make informed decisions on pricing at both the category and product level.

    Retailers should consider their balancing margin performance with consumers’ willingness to pay, rather than implementing broad price increases that may harm customer trust. Price increases can be challenging for both customers and merchants. Retailers who employ a data-driven and insight-based approach are more likely to succeed.

    Keep an eye on the DataWeave blog for analysis on pricing, discounting, stock availability, discoverability, and more, across retailers and brands from other industry segments as well.

    For immediate insights, subscribe to our interactive grocery price tracking dashboard. Better still, reach out to us to speak to a DataWeave expert today!

  • Decoding the 2022 Black Friday Record Sales: The Who, The What, and The How?

    Decoding the 2022 Black Friday Record Sales: The Who, The What, and The How?

    Contrary to popular speculation of lukewarm online sales owing to the weak economy, high inflation, and stretched wallets, Black Friday this year recorded a whopping $9 billion in e-commerce sales. Despite the lull in online shopping across many retailers in the months preceding Thanksgiving and weakened consumer sentiment, US online merchants saw a sizable boost in sales during and after Thanksgiving, albeit at a slower growth of 2.3%, as reported by Adobe Analytics.

    This article looks closely at the Black Friday data to understand which brands, retailers, and product categories were key players. Through DataWeave’s innovative Digital Shelf Analytics product, we deep dive into the availability, discount, and share-of-search data to deduce why some product categories and retailers fared better than others.

    Who: Retailers and Brands that had the Highest Presence

    Black Friday sales this year were driven by consumers grabbing the biggest and best deals to make the most of their already stretched wallets. Many shoppers opted for flexible payment schemes, and Buy Now Pay Later (BPNL) payments rose by 78% compared to the week before Thanksgiving. Surprisingly, Amazon, which was the most searched retailer during Black Friday last year, came only fourth this year, as reported by the Search Intelligence company, Captify.

    According to Captify, Walmart was the most searched retailer for Black Friday deals, followed by Target, Kohls, and Amazon in that order. Amazon, however, has reported its biggest Thanksgiving sale this year, with independent retailers selling through Amazon seeing a total sales of $1 billion. With the economic slowdown and thin wallets looming large, discount rates greatly influenced consumer spending. Mobile shopping accounted for 55% of digital sales, 8.5% more than the previous year. 

    As told by Adobe, Electronics were the significant sales driver, reporting 221% higher sales than in October this year, with smart home items and audio equipment playing an important role with 271% and 230% higher sales. Toys ( popular purchases were Fortnite, Roblox, Bluey, Funko Pop!, and Disney Encanto) and exercise equipment also registered a substantial growth of 285% and 218%, respectively. 

    Other top-selling items included gaming consoles (Xbox Series X and PlayStation 5 devices, games including FIFA 23, NBA 2k23, and Pokemon Scarlet & Violet), drones, Apple MacBooks, and Dyson products (airwrap and vacuum). Amazon’s most popular items were reported to be Apple Airpods, Nintendo Switches, Echo Dot smart speakers, and Fire TV sticks. 

    What: Top Selling Product Categories

    Electronics, closely followed by home appliances (robotic vacuum cleaners), toys, and exercise equipment, were popular product categories in demand during Black Friday this year. Several retailers, including Amazon, Walmart, Target, Kohls, BestBuy, and Home Depot, offered lucrative pre-Black Friday discounts to trigger early sales kick-off. 

    Amazon carried an early discount of 50% on its Echo smart speaker, Target offered 30% off on Dyson vacuum cleaners, Walmart offered 25-35% off on Apple ipads and watches, and Kohls offered 51% off on the iRobot Roomba. 

    Amazon’s top ten best-selling products ranged from Amazon devices like Echo Dot speakers, Fire TV sticks, and Echo Show to Apple AirPods, Nintendo Switches, New Balance sneakers, Champion Apparel, and Burt’s Bees Lotions. The popular product categories were home, fashion, toys, beauty & health, and Amazon devices. Consumers heavily supported small businesses, contributing to $1 billion in sales. Top sellers from small businesses included card and board games.

    Briefly correlating the discounts offered with the best-selling product categories, one can notice that the deals have largely influenced Black Friday sales this year. Popular categories are those that have had deep discounts, reflecting the consumer’s tendency to wait and grab the best deals.  

    How: Role of Digital Shelf Analytics – Key Performance Indicators 

    Digital Shelf Analytics
    DataWeave’s Analysis Methodology

    We have seen a summary of the Black Friday 2022 statistics – sales recorded, top-selling products, product categories, and retailers. Using DataWeave’s e-commerce analytics product, we track and study the variations in digital shelf KPIs across retailers before Thanksgiving and during Thanksgiving to understand how these influence sales. 

    Availability scores, discount rates, and share of search data are analyzed for top retailers in the US for key product categories. Data is tracked and analyzed across two time periods – before Thanksgiving (Nov 10 – Nov 21) and during Thanksgiving (Nov 21 – Nov 25).

    Methodology

    • Retailers tracked: Amazon, Best Buy, Sephora, Target, Ulta, Walmart
    • Product Categories tracked: Electronics, Home Improvement, Beauty, Furniture
    • Digital Shelf KPIs tracked: Availability, Discount rates, Share of Search
    • Location: USA
    Amazon Digital Shelf Analytics

    Amazon maintained good availability across all product categories – Beauty ranks the highest.

    Salient Insights

    • Amazon maintained good overall availability – an improvement of 3% over Prime day. 
    • Beauty had the highest availability of 95%, with none and Lotion & Brushes reporting 97% and 95% availability, respectively. Shampoo reported the lowest availability at 92%
    • Home Improvement had the least availability at 87%, with dishwashers (68%) and washers and dryers (78%) having the lowest availability. 
    • Unlike Furniture and Home Improvement, most categories maintained similar availability scores before and during Black Friday.
    • Furniture improved its availability during Black Friday by 4%, while Home Improvement reported a decrease in availability during Black Friday by 4%. 
    • Electronics, which was a major sales driver, had an availability of > 90% across all sub-categories except for Television, which had a low availability of 70%
    • Tables and chairs registered 99% availability under Furniture

    The above data indicates that Amazon ensured the high availability of utility products that consumers would buy even during a slow economy. Other retailers showed similar availability trends, with scores being similar prior to and during the event.  

    Black Friday Discounts with ecommerce analytics

    Discounts Drove Sales – Best Buy offered the Highest Discounts

    Highlights

    • Best Buy offered the highest early Black Friday discount of 30%, followed by an additional 9% discount around Black Friday. Walmart followed next with 21% early discounts and an extra 4.5% discount during the event. Amazon came next with 17% early discounts and a 5% discount during Black Friday. Discount rates seem to strongly correlate with online searches, with Walmart beating Amazon this year as the most searched retailer for Black Friday deals. 
    • Electronics was the most discounted category across Amazon, Best Buy, and Target, with an average discount of 21%. Walmart gave lower deals on electronics (12%). Electronics also had heavy early discounts of 12%, with most retailers giving an additional discount of 7-8% closer to Thanksgiving.
    • Best Buy offered early discounts of 10% and further upped their discounts by another 12% closer to Thanksgiving. Being the most discounted category, electronics was also a significant sales driver this Black Friday.
    • Amazon offered the highest discounts for Beauty products (18%), followed by Ulta at 10% and Walmart at 8%. Sephora and Target gave minimal discounts on beauty products (3%)
    • Best Buy gave the maximum discounts on Home Improvement products (16%), followed by Amazon at 14%. Walmart gave much lower discounts of 7% on Home Improvement products. 
    • Furniture is another category with 12-13% discounts at both Amazon and Walmart.
    • Best Buy’s strategy this year has been to offer heavily discounted early deals to boost their sales.
    Black friday 2022 Beauty Analytics
    Icons: Flaticons.com
    Black friday 2022 Electronics analytics
    Icons: Flaticons.com
    Home improvements black friday 2022
    Icons: Flaticons.com
    home furniture black friday 2022
    Icons: Flaticons.com

    Highlights

    • Airpods and headphones were the most discounted item under Electronics, with Amazon and Target offering a whopping 27-29% discount. This clearly resulted in heavy sales of AirPods this Thanksgiving.
    • Best Buy and Target had good discounts on all electronic items, while Amazon gave heavier discounts on AirPods, headphones, and smartwatches.
    • Walmart did not offer hefty discounts on laptops and headphones, instead focused on Smartwatches, smartphones, and television.
    • In Home improvement, Best Buy offered the biggest discounts for refrigerators, washers and dryers, and dishwashers, while Amazon focussed more on Tools.
    • Walmart did not offer many discounts in this category.
    • Amazon topped the discount charts for maximum combined discounts for makeup and hair brushes on the day of the event. 
    • All retailers offered better discounts for utility products like tables, chairs, and cots (~15-17%), while dressers and couches carried lower discounts (~6-10%).
    Discount brackets - Black Friday 2022

    Highlights

    • Different companies had different discount strategies based on price buckets.
    • Amazon gave heavier discounts in the lower price buckets (< 200$) and lower discounts for products priced higher than 200$. 
    • Best Buy offered the heaviest early discounts of >25% on products priced under 20$ but provided a few additional discounts during the event. For products priced higher than 20$, Best Buy uniformly offered substantial early discounts as well as further discounts during the event.
    • On the other hand, Target focussed on mid and high-priced items, offering heavy early discounts of 16-18% on products priced higher than 100$ and early discounts of ~7% for middle and lower-priced items. For middle-priced products (40-100$), it offered heavier discounts of 10-12% during the event. 
    • Walmart focussed on mid-priced products, offering the highest discounts (both early (~12%) and additional discounts (5%)). It offered the least discounts (~8-9%) on products priced higher than 200$.
    Share of Search - Digital Shelf Analytics - Dataweave

    Share of Search – Amazon is the only retailer with sponsored searches; Apple AirPods rule the roost.

    Salient Insights

    • Amazon is the only retailer with sponsored searches, with HP, Lenovo laptops, and Apple AirPods occupying the highest share. This correlates with AirPods being one of the most sold products.
    • HP laptops had the highest share on Amazon pre-Event but gave the spot to Lenovo during Thanksgiving.
    • Tracphone and Motorola smartphones, Insignia Televisions, and JBL headphones had a good SoS on Amazon.
    • On Best Buy, HP and Dell laptops featured most in searches, with HP ruling the roost during the event. Lenovo had a small presence.
    • Samsung smartwatches, televisions, and Apple AirPods have a big chunk of the search at Best Buy.
    • On Target, pop sockets, smartphones, Apple smartwatches, headphones, and AirPods have the most prominent presence. Apple was the most featured brand in this segment.
    share of search beauty - black friday 2022
    Note: The share of search percentage reported here is the average score across all subcategories (makeup, lotion, shampoo, hair dryers and hair brushes) of Beauty.

    Salient Insights

    • Amazon, Target, Sephora, and Ulta sold beauty products, with Amazon being the only retailer with sponsored products.
    • Ogx, bs-mall, conair, hywestger were popular brands on Amazon, with interest-based ads occupying a substantial part of the search results, especially in Lotions (~40-50%)
    • Tresemme, Scotch Brite, Revlon and Cerave were popular brands in Target
    • Dyson products (brushes and hair dryers) are featured at Ulta’s top of the search, followed by Pureology shampoos.
    • Sephora’s own collection of brushes featured prominently on their website both before and during the event, followed by Dyson and T3 brushes and hair dryers.
    share of search -Digital Shelf Analytics- home improvements
    Note: The share of search percentage reported here is the average score across all subcategories (refrigerator, washers/dryers, dishwashers, tools and coolers) of Home Improvements.

    Salient Insights

    • In Amazon, Frigidaire and RCA had the highest SoS amongst Refrigerators, and LG occupied the highest share among washers and dryers, Coleman in Coolers, Dewalt in Tools, and  Comfee in Dishwashers, both before and during Black Friday.
    • In contrast, on Best Buy, Samsung had the highest share of SoS amongst Refrigerators, package deals were most prominent in washers and dryers, LG among dishwashers, ifixit in Tools, and Corsair in Coolers.
    share of search furniture on amazon
    Note: The share of search percentage reported here is the average score across all subcategories (bed, chair, couch, dresser, and table) of Furniture.

    Salient Insights

    • Interest-based ads occupied the highest SoS on Amazon for Beds.
    • Urban shop and Amazon basics were popular in Chairs, Lifestyle in Couches, WLive in Dressers both before and during the event.
    • Vasagle was more popular during the event than Furrion in Tables, though the reverse was true prior to the event.

    Summary & Key Takeaways

    Black Friday this year was a pleasant surprise to Brands and Retailers, reporting much larger sales than predicted. After experiencing a slump in sales in the months leading up to Thanksgiving, e-commerce vendors have a reason to be optimistic about their holiday season sales forecasts.

    • A record-breaking $9.2 Billion in online sales was reported by Adobe Analytics, a growth of 2.3 % compared to the previous year.
    • Mobile shopping accounted for 55% of digital sales, a rise of 8.5% compared to last year.
    • Retailers wooed customers through deep discounts (~30%) prior to Thanksgiving and around Black Friday. Heavily discounted items like Apple AirPods were the most popular.
    • Thanks to inflation and stretched wallets, consumers were willing to spend but waited to grab the best and biggest deals. Utility products had better sales.
    • With tough competition between retailers on who offers the best discounts, Amazon slid down to the fourth position, and Walmart was the most searched retailer.

    DataWeave, through its Digital Shelf Analytics and Commerce Intelligence solutions, gleans useful insights from e-commerce data and breaks down trends during global shopping events like Prime Day, Black Friday, and Cyber Monday. If you are a brand or a retailer who would like to know more about our products and solutions, contact us at contact@dataweave.com.

  • It’s not easy being a Bakery Brand: Insights from Digital Shelf

    It’s not easy being a Bakery Brand: Insights from Digital Shelf

    By 2028, Fortune Business Insights projects that the global bakery products market will reach USD 590 billion. The CAGR (Compounded annual growth rate) for 2021-28 is estimated at 5.12%. Products in this segment include bread, buns, cookies, tortillas, salted snacks, English muffins, bagels, confectionery food, hot dogs, cakes, popcorn, and so on.

    Due to disruptions in the global supply chain caused by lockdowns and border closures, the pandemic has had a negative impact on the demand for bakery products and snacks worldwide. However, the market is not only changing, but consumer demand is increasing. Post-pandemic, health, food, and safety have gained renewed attention.

    People across the world are making healthier choices with a focus on wellness. 

    A growing number of people are interested in plant-based foods and beverages, reducing sugar consumption, and understanding the link between lifestyle and health, including obesity and diabetes. As a result of these trends, food producers are reshaping their product strategies to meet new consumer demands.

    In this article, we take a look at the ways companies can leverage data to inform their e-commerce strategy.

    What’s driving up the demand for bakery products?

    More people are choosing easy-to-use bakery products and snacks over other foods due to urbanization, convenience, western diets, and women’s participation in the workforce. Additionally, innovations in baking systems, food technologies, ingredients, formulations, and product ideas are providing customers with a greater level of choice, flexibility, and freedom.

    How is e-commerce changing the game for bakery product companies?

    To optimize their supply chains, bakery food and snack companies must better understand e-commerce metrics given the wide variety of products available and eventually convert sales. There are several measures that companies need to pay attention to. 

    Stock availability metrics, discounts across locations, and share of search results – are all critical metrics companies need to track. In addition to providing manufacturers and retailers with an insight into the trends, DataWeave’s tools also allow them to make better business decisions and ultimately improve their bottom line. 

    Grocery Retailers and Bakery Brands tracked

    Methodology

    • Data Scrape period: February 2022 to September 2022
    • Country: Canada
    • Grocery Retailers tracked: Atlantic Superstore, Fortinos, InstaCart, Loblaws, Voila, Walmart Grocery, Zehrs.
    • Bakery brands: Betty Crocker, Dempsters, Hostess, No Name, Presidents Choice, Quaker, Vachon, Doritos.
    • Category tracked: Bread and Bakery, Chips, Crackers, Deserts, Snacks.

    Share of Search Analysis

    Which brands feature the most on e-commerce portals?

    When listing items on e-commerce platforms, share of search is crucial. The highest share of the top ten or top twenty items available on these platforms is correlated with how many times the item may be viewed. As a result, it would have a greater chance of being selected by the customer.

    By Retailer for Category “Desserts”

    Share of Search for Brands in each retailer
    • In Walmart Grocery, Vachon has the highest share of search at 41%, whereas Betty Crocker, Presidents Choice and No Name had the lowest share of search at 0%, in the Desserts Category.
    • In Loblaws, Presidents Choice had the highest share of search of 34%, whereas Dempsters had the lowest share of search of 2%  in the Desserts Category. 
    • The brand Presidents Choice consistently ranks high in the share of search results for Desserts across multiple retailers, including Atlantic Superstore, Fortinos, Instacart, Loblaws, and Zehrs – except at two retailers, Voila and Watlmart Grocery, where its share is zero.

    Trend of Share of Search for “Desserts”

    Share of Search analysis by Brands over Time in category “Desserts”
    • Share of search had dropped by around 4% for No Name, whereas for Vachon, it increased by 3% from Jan’-22 to Sep’ 22
    • By brands, Presidents Choice had the highest share of search at 42%, whereas Betty Crocker had the lowest share of search at 12% between Jan’ 22 and Sep’ 22 in the Desserts Category.

    Availability Analysis

    Which products are widely available across e-commerce portals?

    The availability of the product on the e-commerce portal is one of the key indicators of meeting customer demand. Brands can use insights from DataWeave to strategize how to restock their inventory and ease customer demand. Based on data analysis, brands can also determine which products to prioritize on which platforms.

    By Category

    Availability analysis by Category over Time
    • Availability of all five categories was around 52% in Feb’ 22, which steadily increased to 61% until Aug’ 22 and has reduced to reach 55% availability in Sep’ 22
    • Sliced Bread category has seen the most drop in availability by 12% between Jun’ 22 and Sep’ 22
    • The tortilla category has the most rise in availability. It has increased by 16% between Feb-22 and May-22. It also showed an overall rise in availability of 5% from Feb-22 to Sep-22

    By Location

    Availability analysis by Location and Category
    • Across categories, Snacks & Candy had better availability at 73% than Bread & Bakery, with 56% availability.
    • By Location, New Brunswick had more than 65% availability across all three categories; the closest Location is Nova Scotia, with 63% availability.
    • Alberta had the highest availability of 100% in the Snacks & Candy category and the lowest availability of 21% overall in all three categories (weighted aggregate)

    Discounts Analysis

    Several discount-based insights can be studied on e-commerce platforms. From location-based trends, retailer-based trends, and manufacturer-based insights. These insights can help companies make the most of the revenue opportunity while creating an attractive value proposition for the retail consumer.

    By Category

    Discount analysis by Category
    • Discounts of all three categories were around 24% in Feb’ 22, which steadily reduced to reach 15% in Sep’ 22
    • Snacks, cookies & chips category has contributed the most to the drop in discounting, which dropped by 17% between Apr’ 22 and Sep’ 22
    • The Tortilla Category does not have any discount in the month of Jul’ 22

    By Retailer

    • Discount on Bread & Bakery category in Walmart Grocery was around 9% in Feb’ 22. It steadily increased to 13% by Jun’ 22 and thereon reduced to reach 11% availability in Sep’ 22.

    By Location

    • Across Retailers, Nova Scotia had the highest availability of discounts at 22%, whereas New Brunswick had the lowest with discounts at 9% in Bread & Bakery category.
    Discount analysis by Retailers and Locations – Alberta, Ontario, New Brunswick, Nova Scotia
    Note: Analysis does not cover all locations

    Bakery and snack product manufacturers on e-commerce platforms have access to a rich trove of insights they can leverage to benchmark their strategies. They can better understand customer demands, align their supply chain and critically understand the trends impacting their bottom line. Engaging with a third-party platform like DataWeave’s Digital Shelf Analytics  can help brands unlock tremendous value. 

  • Insights from the Digital Shelf of Indian FMCG Brands

    Insights from the Digital Shelf of Indian FMCG Brands

    Analyzing Search, Promotions and Availability for Chocolates, Biscuits, and Malt Drinks across BigBasket, Blinkit, Dmart, Swiggy etc.

    Imagine you log into an e-commerce portal with a list of food items you need for the month. You know what you want, and scroll through the platform to see if there are any discounts. You check competitor products to see if you can get better deals. And within no time, fill your cart with products that you need and proceed to check out. 

    It all happens quickly. It’s an online shopping experience that we are familiar with. But what exactly is happening in the background?

    Brands are tracking and ensuring the highest keyword ranking, optimal availability and competitive discounts to grab your order. And to enable this, Brands rely on Digital Shelf Analytics.

    The FMCG marketplace

    Source: NielsenIQ’s FMCG Snapshot for Q2 2022

    Here, we take a closer look at some of the key factors that Fast Moving Consumer Goods (FMCG) Brands on e-commerce platforms need to pay attention to – to ensure their products appear on the top of search items, to better understand competitor discounts and to monitor the availability of their products across regions.

    FMCG has experienced rapid growth in the last two years, largely attributed to digitalization, changing consumer habits, and increased spending post-pandemic.  Macro factors, including government impetus, inflationary pressures, and consumption recovery, indicate a double digital growth for FMCG brands in the country. According to NielsenIQ’s FMCG Snapshot for Q2 2022, the FMCG industry has grown by 10.9% in the quarter ending June 2022, compared to 6% in the previous quarter.  In the second half of 2022, consumers are expected to spend even more during the festive season. With these shifts underway, the growth opportunities in this sector can only be exploited by companies that can sense trends early – and take appropriate action.

    In addition to providing manufacturers and retailers with actionable insights into e-commerce trends, DataWeave’s tools also allow them to make informed business decisions and ultimately improve their bottom line. Data-driven insights on e-commerce products can help brands optimize their supply chain to maximize sales. A company can determine the key areas that need attention based on an analysis of the availability of products on specific e-commerce channels, associated discounts, as well as zip-code level demand and supply statistics.

    Here are a few sample insights and trend analyses for some popular FMCG brands in the Biscuits, Chocolate and Malt drinks categories spotted by DataWeave.  

    Analytics Methodology: An overview of the data set analyzed

    • Data Scrape period: January 2022 to August 2022
    • Grocery Retailers tracked: Amazon Fresh, BigBasket, Dmart, Jiomart, Swiggy, Milkbasket
    • FMCG brands: Britannia, ITC, Mondelez, Nestle, Parle, Complan, Boost, Amul, Hershey’s
    • Category tracked: Biscuits, Chocolate, Malt drinks


    Availability Analysis

    What is the availability of Biscuits, Chocolate and Malt Drinks on e-commerce portals?

    The availability of a product on an e-commerce marketplace is a key indicator of whether the product meets consumer demands.  DataWeave’s availability analytics can be leveraged by FMCG brands to strategize their inventory and stock planning.  Brands can also make data-driven decisions on product visibility, i.e. identify which products to prioritize on which platforms. 

    • Biscuits had a better availability at 63% when compared to chocolates at 56% across all retailers
    • Dmart and Swiggy had more than 85% availability across all three categories, with Bigbasket coming next at 67% availability 
    • Flipkart Grocery and Blinkit had the lowest availability at 46% and 50%, respectively.
     Figure 1: Availability Scores for Biscuits, Chocolates and Malt Drinks across Retailers

    Which manufacturers have the highest availability of products on e-commerce platforms?

    A study of the availability of products across different manufacturers can reveal brands that have successfully tapped the market opportunity. Here’s a look at brands that have steadily improved their availability on e-commerce platforms.

    Figure 2: Availability Trends for Biscuits across Manufacturers
    • In the biscuits category, all five manufacturers marked approximately 50% availability in Jan 2022. Availability steadily grew to 68% in June 2022, then declined to 63% in Aug 2022.
    • Unibic experienced the largest drop in availability, dropping 15% between May 22 and Aug 22.
    • Mondelez saw the largest rise in availability, an increase of  23% between Mar-22 and Aug-22.
    Figure 3: Availability Trends for Malt Drinks across Manufacturers
    • Except for Boost and Nestle, availability for all seven manufacturers of malt drinks was consistently above 50%. The average availability across all manufacturers rose gradually from 55% in Jan to 63% in Jul-22, followed by a small decline to 57% in August.
    • From 30% availability in January 22 to a mere 7% in August 22, Boost has seen the greatest drop in availability.
    • The availability of Amul has risen the most over the past year, rising from 51% in January 22 to 78% in August 22, hitting 80% in July 22.

    Chocolate: Which manufacturers have the highest availability of products on the e-commerce platforms?

    Figure 4: Availability Trends for Chocolates across Manufacturers
    • Chocolate availability across all manufacturers averaged 47% in Jan-22, reaching a peak of 64% in May-22 and dropping to 51% in Aug-22.
    • From 46% in Jan-22 to 74% in May, Mondelez saw the biggest increase in availability, followed by a decline to 68% in August.
    • Ferrero experienced one of the sharpest drops in availability. Although the brand’s availability steadily grew from 77% in Jan 22 to 94% in Jul 22., it registered a steep drop to 49% in August. 

    The drop in availability hurts the Brand’s eCommerce in two ways. Not only does the Brand lose sales directly. But poor availability also impacts the keyword search ranking, which further hurts the sales.

    Check out DataWeave’s Digital Shelf Analytics Product for insights on how Availability tracking can help reduce stock-outs and boost sales. Click here to know more.

    Discount Analysis

    Location-based, retailer-based, and manufacturer-based discount trends can be analyzed. These studies can help companies plan attractive and appropriate promotional and discount strategies to enhance their revenue opportunities. 

    Which manufacturer has been offering the most discounts?

    A study of discounts offered across manufacturers for chocolates, malt drinks and biscuits indicates that some brands have increased their discounts while others have reduced their discount rates. These decisions could be triggered by demand, availability, and production cycle. Parle, for example, has steadily reduced its discount rates. 

    Figure 5: Discount Rate Trends across Manufacturers

    Average discount rates across manufacturers were around 9% in Jan 2022 and rose steadily to reach 14% in Jul 2022. A small decline is observed post-July, with a 12% discount rate registered in Aug 2022.

    • In the biscuit category, Unibic offered the biggest discount of 28%, followed by ITC at 20%.     
    • In the Chocolate category, Hershey’s offered the largest discount of 14%, followed by ITC at 12%.
    • In the Malt Drink Category, Amul offered the largest discount of 16%, followed by Boost at about 10%. 

    Check out DataWeave’s Digital Shelf Analytics Product for insights to respond to Competitor’s pricing and promotions. Click here to know more.

    Share of Search Analysis

    Which brands feature within the top 5 on the first page of the search?

    A product that appears within the top 5 items on the first page of a search, has a higher probability of being purchased. Below is a study of the share of the search for biscuits across manufacturers and retailers. 

    Figure 6: Share of Search for Biscuits across Manufacturers and Retailers
    • Britannia dominates the top ten share of search across different online retail platforms.
    • Mondelez has the highest share of search at 62% in Amazon Fresh, whereas Parle-G has the lowest share of search at 7%.
    • In Bigbasket, Britannia has the highest search share of 62%, whereas Parle-G has the lowest search share of 7%.

    Check out DataWeave’s Digital Shelf Analytics to track the Share of Keyword and Navigation Search. Click here to know more.

    Conclusion

    FMCG is a rapidly evolving industry sector with a high potential for growth in the coming years. FMCG brands must compete with one another to fully tap this market opportunity on several factors to ensure that their products are visible, available, and attractive to consumers. Digital crawling and big data technologies have enabled manufacturers and retailers to collect publicly available e-commerce data for useful, actionable insights and trend analysis. To stay competitive, it is crucial for manufacturers and retailers to engage with analytics and data experts to seamlessly integrate e-commerce analytics into their short- and long-term business strategies. Whether it’s building keywords to increase the share of search, knowing the right discounts to attract customers in a particular city or increasing the availability of products on specific e-commerce platforms, companies need to invest in the right data intelligence!

    DataWeave for FMCG Brands

    DataWeave has been working with global CPG/FMCG brands, helping them drive their growth on eCommerce platforms by enabling them to monitor their key metrics, diagnose improvement areas, recommend action, and measure interventions’ impact. DataWeave’s KPIs enable Brands to fill in the blind spots in their funnel data and allows them to respond to competitors on a near-real-time basis.

    If you want to know to learn how your brand can leverage DataWeave’s data insights and improve sales, then click here to sign up for a demo

  • The Rapid Rise of Alcohol eCommerce in the UK

    The Rapid Rise of Alcohol eCommerce in the UK

    Alcohol eCommerce has been rapidly growing over the years, and like a lot of other industries, the pandemic accelerated its growth. Convenience, safety & home delivery became important criteria for customers in the post pandemic era and so the sale of alcohol via eCommerce went up. Kantar reported that UK booze sales were up £261m & online and convenience stores were the biggest winners. The latest IWSR Drinks Market Analysis Report 2022 reported on another interesting trend – when ordering alcohol online, consumers prefer using websites v/s apps in most parts of the world except China and Brazil. In the UK the largest chunk of online alcohol purchases happens on a retailer website instead of an app. 

    Platform used for last online alcohol purchase. Source

    To get a better understanding of this, we tracked 2 grocery retailers and 3 grocery Q-Commerce apps in the UK to get insights into Alcohol sales, pricing, trends & more! 

    Methodology

    • Data Scrape time period: Feb 2022 – June 2022
    • Grocery Retailers tracked: Tesco & Ocado
    • Grocery Apps tracked: Gorillas, Weezy & Getir
    • Category tracked: Alcohol

    Which retailer was the Price Leader in the alcohol category? 

    Before the pandemic Tesco was the only Big 4 retailer to increase their alcohol market share & Waitrose was the biggest loser, with its share of booze sales falling from 5.4% to 4.7%. Maintaining Price Leadership is a critical element and plays a big role in increasing sales & market share because consumers will buy the most competitively priced product. We wanted to track and see which retailer was the Price Leader in the alcohol category – i.e., had the most number of lower-priced items in the alcohol category. We also wanted to see if & how Tesco’s position had changed post pandemic. 

    Price Leadership
    • Tesco enjoyed price leadership in the Alcohol category from Feb – June 2022 with 38.9% products priced the lowest. This, followed by Ocado at 33.8%. Gorillas had price leadership for the least amount of products in the alcohol category at 5.6%. Tesco was the clear winner! 
    • Tesco’s Price Leadership kept declining through the months though – at the beginning of the year in Feb, Tesco had 44% products priced the lowest but by June, that number fell to a little over 36%. Ocado showed a reverse trend – in Feb they had price leadership on 32% items and by June that number rose to 35.3%.
    • One player Tesco could’ve potentially lost price leadership to was Getir. In Feb, Getir had price leadership on only 8.2% products but that increased gradually over the months to land on 14.5% in June. 

    Which retailers focused on Discounts to perk up alcohol sales? 

    Discounts are a great way to draw in inflation-hit shoppers. Loyalty card discounts, reward vouchers, and other promotional strategies retailers offer help make their products more competitive & attractive to customers. To stay competitive, retailers need to be aware of the discounts their competition is offering. They also need to understand the risk of deep discounting and the impact on margins. We wanted an insight into alcohol related discounts in the UK so we dug into our data. Here’s what we saw. 

    Average discounts across months by retailers
    • A host of European and UK based startups like Jiffy, Dija, Weezy, Zapp, Getir & Gorillas launched with the promise of delivering groceries the fastest & cheapest. 
    • Our data showed that Gorillas offered discounts in line with the competition, however, Getir likely went the deep discounting route. 
    • Getir offered the highest discounts across all months. And in the month of April they offered almost 9% more discount than Ocado – the retailer with the 2nd highest discounts. 
      Like we discussed above, Getir gained price Leadership from Feb to June. Deep discounting could have potentially played a role. 
    • Gorillas on the other hand had the lowest, almost non-existent discounts.

    Let’s look at Price Index trends across 5 months 

    We tracked the Price Index (PI) across these 5 retailers to measure how alcohol prices changed over a 5 month period from Feb – June 2022. 

    Note: Retailers selling at the 100% mark were selling at an optimal price & did not undercut the market. The pricing sweet spot is 95% – 105%. Anything lower would compromise margins, and higher would mean the retailer was not competitive. 

    Price Index across months by retailers
    • Weezy had a Price Index that was the most optimal, sitting in the 100% – 102% range.
    • Gorillas had the lowest Price Index, between 89% – 91%.
    • Getir had a low price index in Feb (96.1%) but slowly kept increasing to cross 110% in April, May & June.
    • What was interesting to see was the competition between the 2 retail giants Ocado & Tesco. Ocado had a lower price index at the start of the year at 105.1%, while Tesco was at 109.8%. In the subsequent months, Ocado kept increasing prices to be competitive with Tesco and Tesco decreased prices to likely match Ocado’s pricing. By June BOTH Tesco & Ocado had the exactly the same price index – 108.7%

    Which retailers were the quickest to make price changes?

    Competitive pricing is critical to eCommerce success. Competitive pricing involves tracking your competitor’s pricing & strategically tweaking your own prices without hurting margins. We tracked the month-wise average Price change from Feb – June across all 5 retailers to see which retailer was making price changes and at what frequency. 

    Average price change across months by retailers
    • Most retailers did not make massive prices changes, they were ballpark competitive with each other from a pricing standpoint. 
    • However, Gorillas made significant changes in the month of March when they dropped prices by 3.8% and in May when they increased prices by 5.5%!
    • In May, the same month Gorillas made a big price hike, Weezy dropped their prices significantly by 10% widening the gap between the 2 retailers. 

    Which retailers avoided lost sales by maintaining stock availability?

    Having a near real time view on stock availability is crucial to driving sales. Customers can buy products only when they’re available! So, we went ahead, looked into our data to see how each of these retailers managed stock availability from Feb to June.

    Average availability across months by retailers
    • Our data showed varying availability levels across retailers with Ocado having the highest availability across all 5 months. They had a robust stock at the beginning of the year at 100% but kept dwindling through the months to land at 95.8% by June. 
    • Tesco had a sharp drop in availability in May & June – from 97% at the beginning of the year to the 92-93% range.
    • Gorillas had the lowest availability across months between 90 & 94%.
    • Weezy consistently maintained availability at 95% across all 5 months.

    Conclusion

    For the most part, the UK market has a positive outlook towards buying alcohol online thanks to changes to shopper behavior arising from the pandemic. As per the IWSR Drinks Market Analysis Report 2022 in website-led markets, such as the UK, breadth of product range is important to customers along with price. These 2 play a key factor in purchase decisions. By contrast, consumers in app-driven markets have different preferences. While price matters, it is less important than convenience and speed. 

    As an alcohol retailer, if you need help tracking your competitor prices, discounts and product assortment, reach out to the team at DataWeave to learn how we can help!

  • 5 Ways to Manage and Improve Stock Availability

    5 Ways to Manage and Improve Stock Availability

    Stock availability is the degree to which a brand or retailer has inventory of all their listed items to meet customer demand. Product availability becomes even more critical when they have to respond to unforeseen changes in demand and supply. To maintain the ideal stock availability levels for all items, they need robust inventory management tools to ensure real-time updates on current stock and accurate insights into upcoming demand.

    However, managing stock availability is not a clear-cut science. Retailers must balance the change in demand and keep stock availability in check. 

    Why Stock Availability Matters

    One of the challenges of running a retail business is to optimize inventory and associated costs. Maintaining stock availability in stores is critical for offline retail businesses. And when selling online, making sure products are available across different retailers and marketplaces can have a huge impact on sales and conversions. 

    1. Understocking: It’s when a brand’s product fails to meet consumer demand. If this happens often enough, customers may not return to the brand’s website or app because of the initial experience. Understocking is not a brand’s fault entirely since they might not always be able to anticipate a change in demand. However, it’s about a their ability to adapt to a quick change in the market trends through historical analysis and accurate forecasting. 
    2. Overstocking: It’s when a company orders too much inventory. Holding too much stock will lead to higher storage costs, shrinkage, and obsolescence losses. Another loss occurs if the brand can’t quickly sell the items — diminishing the value of the products. 

    We gathered data to see the impact of a short-term stockout on Amazon for one of our customers. Read more about what we uncovered & how deep the damage was, here.

    7 Ways to improve stock availability 

    1. Collect Accurate Data

    Availability across Brands and Categories

    When multiple items are moving through a supply chain, companies can easily run into inventory inaccuracies. Discrepancies between the values of your system and the actual inventory of products can lead to understocking or overstocking. The best way to avoid discrepancies in inventory is to invest in an inventory management tool that gives you real-time updates on your stock. This is applicable for offline retail businesses. 

    2. Managing eCommerce inventory

    Availability at Individual Product Level
    Availability at Individual Product level by regions

    Effective eCommerce inventory management is as important as making sure products are available in stores. Keeping track of your inventory levels and ensuring that you’re always well-stocked can avoid lost sales and keep your company running smoothly. Brands must ensure their stock is available across all the online platforms they sell. Access to real-time inventory data can help to keep a close eye on stock status across all marketplaces & retailers the product is available. Retailers also need to keep track of market trends to ensure they have the right inventory assortment to match customers’ demands. 

    3. Understand Consumer Demand

    The only way to accurately predict future demand is to rely on historical data about your customer purchase trends. What do your customers purchase during holiday seasons? What are the upcoming trends in your category? Having data-backed answers to such questions will help brands and retailers properly stock up their inventory.

    4. Adequate forecasting 

    Anticipating demand will help determine which products should be stocked during which seasons. Tracking past sales and metrics such as economic conditions, seasonality, peak buying months, and promotions will help brands predict demand. Analyzing such statistics will also help you get insights into the target market.

    Availability across regions

    5. Improve supplier relationships

    It’s important to rely on a supply chain that delivers your shipment promptly. In fact, you should foster close relationships with your suppliers to trim costs and improve stock availability. You should be able to share key details such as future demands, so suppliers can ensure timely delivery. 

    Availability Analysis
    Availability Analysis across Retailers and Categories

    Consequences of Inefficient Inventory Management

    What are the effects of overstocking?

    Tied-up cash: Money spent on overstocking is tied-up money that your company could have put to better use. You can use it to pay off debts, wages, and rent. Inventory often has a limited shelf life due to material degradation, changing consumer trends, spoilage, and obsolescence.

    Product expiration: If your brand offers time-sensitive goods or perishable items, overstocking can lead to product obsolescence and expiry. eCommerce platforms that also sell time-sensitive goods or grocery delivery apps are forced to sell products at below-margin prices to free up resources, leading to losses. 

    What are the effects of understocking?

    Poor customer experience: Poor product availability will lead to low customer satisfaction & dropping customer loyalty. 

    Missed sales: Customers could gravitate towards the competition to make their current purchase if a product is unavailable at your online store. The more freequent the stockouts, the more lost sales. 

    Conclusion

    To avoid the knock-on effects of overstocking and understocking, companies need a real-time view of their inventory, both online & offline. At DataWeave, we help companies decrease their latency period between stock replenishment and efficiently plan their supply chain. If you need help tracking your eCommerce product availability, reach out to the experts at DataWeave to know how we can help!

  • 5 Ways DataWeave Helps Brands Drive Growth With Amazon Ads

    5 Ways DataWeave Helps Brands Drive Growth With Amazon Ads

    Consumers are discovering and trialing new eCommerce marketplaces, brands and products at a faster rate than ever before, given the vast amount of choices encountered browsing for products online. A recent analysis shows how events like Amazon Prime Day, Black Friday, and Cyber Monday are especially fruitful for new-to-brand customer advertising, encouraging B2C marketers to increase their digital advertising spend to fuel product discovery, sales and market share for their brands.

    Amazon advertisers grow market share and brand loyalty with ecommerce intelligence
    DataWeave joins Amazon Advertising partner network

    The majority of eCommerce consumers are discovering products via relevant keywords attributable to their needs, with most clicks happening on page one results for the first few products listed. Simplifying the digital shopping experience is critical for brands to be in the consideration set for the majority of consumers who won’t venture past page one results. 

    An internal analysis conducted shows getting a product to page one on retailer websites can improve sales by as much as 50 percent, but figuring out the right levers to pull to get there organically—without paid advertising—is a real challenge, especially given fast-changing algorithms. While more than half of all retail related online browsing sessions are “organic”, sometimes brands need to boost their product visibility by investing in sponsored (paid) opportunities to improve a product’s rank.

    Data analytics can equip brands with intelligence to help them decide when, where, and how to make digital advertising investments profitably, while simultaneously acting on insights that help drive organic growth. Considering a majority of U.S. consumers begin their product discovery on marketplaces like Amazon, it makes sense for brands to prioritize digital advertising opportunities with Amazon.

    Maximize Return on Ad Spend (ROAS) with Amazon Ads

    Brands use Amazon Ads to drive brand awareness, acquire new customers, drive sales and gain market share, with the goal of furthering their marketing return on investment. Top performing advertisers average 40 percent greater year-on-year (YoY) sales growth, 50 percent greater YoY growth in customer product page viewership on Amazon, and 30 percent higher returns on ad spend (ROAS) with Amazon Ads, according to a recent analysis. Sponsored Products, Sponsored Brands, Amazon DSP and Sponsored Display are among the types of Amazon Ads options cited that produce maximum return.

    Ensuring your product listings appear at the top of page one results on Amazon for the most relevant discovery keywords is therefore the most important determinant for maximizing ROAS. DataWeave has become a vetted partner and measurement provider in the Amazon Advertising Partner Network, with the goal of supporting brands to optimize digital advertising campaigns by providing visibility to Digital Shelf Analytics (DSA) key performance indicators (KPIs), like Share of Search, Pricing and Product Availability, Content Audits, Ratings and Reviews, and Sales Performance and Market Share.

    Below is a summary of how our Digital Shelf solutions, in partnership with Amazon Ads, can improve the performance of your Amazon Ads campaigns

    1. Keyword Recommendations Improve Share of Search

    With the DataWeave Share of Search solution, brands can monitor their placement of both organic and paid discovery keywords relative to their competition. Once your keywords are determined, you are also provided a weighted Share of Search score that helps measure how well each keyword performs relative to product discoverability. Below is an example of insights you’d gain.

    Share of Keyword Search

    Brands can provide their own list of keywords to monitor, or through our Amazon Ads collaborative solution, learn which keywords are the “best” for them to measure in the realm of Amazon. Performance results are based on data that shows which keywords consumers are actually using when browsing online alongside other keywords brands request to measure. Users are able to see exactly which keywords are most popular, competitive (and even unexpected), and relevant at an Amazon Standard Identification Number (ASIN) level of granularity. 

    We can also estimate the degree of relevance and estimated traffic for the recommended keywords. Brands can then use these insights to adjust campaign strategies based on these parameters, which can boost product discoverability and rank visibility. A brand could assume people find its products by brand name, yet traffic insights may reveal a majority of people look for a generic product type before they end up buying that particular brand. 

    2. Content Audits Increase Discovery Relevancy Scores

    Strong product content is critical to succeeding on Amazon. Thorough, accurate, and descriptive content leads to better click through rates (CTR), conversion rates, more positive reviews, and fewer returns, which results in increased discoverability. DataWeave’s Content Audit solution reviews existing copy and images on a per-attribute basis to highlight any gaps essential to improving visibility, as seen in the example below.

    Content Analysis

    To further growth, it is equally as important that your product content aligns with your advertising strategy. With Amazon Ads partner add-on, our solution can also audit your content to measure how effectively you are incorporating Amazon Ads keywords into your product content to enhance discovery relevancy.

    3. Discover More Opportunities with Pricing and Product Availability Insights

    Quality content and keyword updates will only get you so far if your products are not consistently available and priced competitively. With DataWeave’s Pricing and Promotions and Product Availability modules, advertisers can monitor their selling prices and availability trends alongside their competitors to uncover more opportunities to incorporate into advertising campaigns, as seen in the Pricing and Promotions dashboard example below.

    Promotion Analysis

    Additionally, product targeting recommendations can be utilized to target a competitor’s ASIN that may be overpriced or that is having issues staying in stock. Alternatively, broaden your strategy to target specific brands, complementary products, or category listing pages.

    You can also create alerts on your own products to monitor when items are low on inventory or out of stock to ensure key products are consistently available when customers are shopping.

    4. Leverage Ratings and Reviews to Increase Conversion

    Product ratings and reviews are also a critical component to running a successful Amazon Ads campaign. A large number of reviews and a positive star rating will provide customers with the confidence to purchase, resulting in higher conversion rates. Conversely, negative feedback can have a detrimental impact, resulting in lost sales and wasted ad spend. DataWeave’s Ratings and Reviews module can help you monitor your reviews and extract attribute-level insights on your products. This information can then be utilized to further optimize your advertising strategy.

    If you see consistent feedback in your reviews on aspects of a product not meeting customer expectations, address them in your product content to prevent potential misplaced expectations. Alternatively, if customer reviews are raving about certain product features, ensure these are promoted and relevant keywords are populated throughout your descriptions and feature bullets. Below is an example of insights seen within the DSA Ratings & Reviews dashboard.

    Ratings and Reviews

    5. Correlate Digital Shelf KPIs to Sales Performance and Market Share

    The newest DSA module, Sales Performance and Market Share, provides SKU, sub-category, and brand-level sales and market share estimates on Amazon for brands and their competitors, via customer defined taxonomies, to easily benchmark performance results.

    This data can also be correlated with other Digital Shelf KPIs, like Content Audit and Product Availability, giving brands an easy way to check the effect of attribute changes and how they impact sales and market share. Similarly, brands can see how search rank, both organic and sponsored, affects sales and market share estimates.

    Understanding the correlation between your advertising campaigns and your Digital Shelf brand visibility will help you identify which areas to prioritize to drive sales and win more market share.

    Digital Shelf Insights Help Brands Win with Amazon Ads

    The need for access to flexible, actionable eCommerce insights is growing exponentially as a way to help brands drive growth, increase their Share of Voice, and to gain a competitive edge. As a result, more global brands are seeking Digital Shelf Analytics for access to near real-time marketplace changes and to develop data-driven growth strategies that leverage pricing, merchandising, and competitive insights at scale.

    By monitoring, measuring and analyzing key performance indicators (KPIs) like Sales Performance and Market Share, Share of Search, Content Audits, Product Availability, Pricing and Promotions and Ratings and Reviews alongside competitors, brands will know what actions to take to boost brand visibility, customer satisfaction, and online sales. 

    DataWeave’s acceptance into the Amazon Advertising Partner Network enables Amazon advertisers to effectively build their Amazon growth strategies and determine systems that enable faster and smarter advertising and marketing decision-making to optimize product discoverability and overall results.

    Connect with us now to learn how we can scale with your brand’s analytical needs, or for access to more details regarding our Amazon Ads Partnership or Digital Shelf solutions.

    UPDATED: Read the full press release here

  • Prime Day India 2022 – highlights from the 2 day annual shopping festival!

    Prime Day India 2022 – highlights from the 2 day annual shopping festival!

    Amazon India’s much-awaited annual two-day shopping event, Prime Day, kicked off with a bang on July 23rd & 24th this year & was one of the most successful Prime Day events yet! Amazon reported that more than 32,000 sellers saw their highest ever sales day during the event. Interestingly 70% of these sellers who received orders during Prime Day were based in Tier 2 cities in India, further validating how the post-pandemic eCommerce boom has spread across the country. Also, Indian exporters saw 50% business growth on Amazon on Prime Day as customers across markets like North America, Europe, Australia, and Japan continued to purchase Made In India products.
    It was a great 2 days for Indian sellers, but what about customers who were waiting in anticipation for the great deals typically offered on Prime Day? We dug into our data to take a look at the deals, discounts, and brands that shone bright on Prime Day in India.

    Methodology

    • In addition to Amazon IN, we also tracked Flipkart on 23 & 24th July 2022, on Prime Day.
    • Categories tracked – Electronics, Grocery, Fashion & Beauty.
    • We looked at Additional Discounts offered on Prime Day: Additional Discount is the extra discount on an item during Prime Day when compared to the Pre-Prime Day price. 
    • We also looked at Post Prime Day Discounts, which were the discounts offered after the 2-day event ended.

    Amazon v/s Flipkart – who offered better discounts?

    Prime Day discounts are legendary. And across the globe, during Prime Day retailers try and compete to see if they can offer better deals than Amazon. Forbes even published an article on the 36 Prime Day competitor sales that were way more enticing than what Amazon had to offer. In India, we wanted to see if Amazon’s homegrown rival Flipkart might give it a tough fight, so we tracked the volume of discounts across categories on both retailers. 

    Discounts on Amazon & Flipkart across categories
    Discounts on Amazon & Flipkart across categories
    • Out of the 4 categories we tracked, in spite of Prime Day, Amazon offered discounts higher than Flipkart in only 2 categories – Electronics & Beauty. 
    • … while Flipkart offered higher discounts than Amazon in the Grocery & Fashion category. For groceries, Flipkart offered a 3.2% additional discount v/s 2.2% on Amazon. However, in the Fashion category, the difference was marginal – 8.1% on Amazon v/s 8.6% on Flipkart
    • Post-event, both Amazon & Flipkart went back to the original pre-event prices. This made it clear that Flipkart was tracking and making price changes based on their closest competitor. It’s what smart eCommerce businesses do to stay ahead in the race. 
    • Interestingly, post-event, in the fashion category, not only did Amazon revert to the original pre-event price, they even increased prices by close to 2%.

    Let’s take a look at discounts across 4 categories & the Brands that WON in each category.

    From Electronics to Fashion, Beauty & Groceries, let’s deep dive into the data to see which products were highly discounted within each category and brands that sprinted ahead to win the race on Amazon on Prime Day 2022.

    ELECTRONICS

    Tech publication Gadgets360 reported on the biggest Smartphone deals right from Brands like Samsung, Redmi, Oppo, and more. There were some fab deals on earphones too with Boat taking the lead. We wanted to take a look at electronics on Amazon and see which products had the heaviest discounts & if discounts were more lucrative than Prime Day 2021

    Discounts on Electronics on Prime Day
    Discounts on Electronics on Prime Day
    • Amazon India released highlights from Prime Day and reported that Smartphones & Electronics were among the categories that saw the most success in terms of units sold.
    • From the 6 product categories we tracked within electronics, we saw the highest additional discounts on Smartwatches (13.4%), followed by Bluetooth headphones (10.5%)
    • TV, Smartphones, cameras, and laptops had an additional discount of between 3 – 5.5%

    ELECTRONICS Brands that had the highest Share of Search on Amazon during Prime Day

    Research shows that on Amazon, the first 3 products garner 64% of business generated. This is why it is critical for brands to appear in the top few listings when consumers are searching for products. Being on top helps shoppers find your brand with ease & increases the chances of a sale. 

    On Prime Day 2022, Amazon India reported that the top-selling consumer electronics brands were HP, Lenovo, Asus, and Boat to name a few. Our assumption is, these brands must’ve had a high Share of Search (SoS), which played a massive role in increasing sales, so we looked into our data to see which brands had the highest SoS against specific keywords related to electronics. 

    Brand Visibility against the Keywords
    Brand Visibility against the Keywords
    • Our data aligned with what Amazon reported. HP had high sales, perhaps because they occupied the premium #1 spot in the laptop category with a 44% SoS! Simply put, this means of the 100 laptops that appeared on a page, against a search for the keyword laptop, 44 products were listed by HP! Consumers always gravitate towards buying products they can find with ease. 
    • Lenovo had a 32% SoS for Laptops. Asus at 14% 
    • The top selling smartphone brands reported by Amazon included OnePlus, Redmi, Samsung, Realme & iQOO – our data showed that 3 out of these 5 brands were in the top 5 listings on Prime Day! Redmi had a whopping 30% SoS against the keyword smartphone, Samsung at 15%, and iQOO at 5% – clear validation that a high SoS can positively impact sales.

    BEAUTY & GROOMING

    Now let’s look at discounts in the beauty & grooming category. 

    Discounts on Beauty Products on Prime Day
    Discounts on Beauty Products on Prime Day
    • The highest additional discounts were given on shampoos (9.3%), followed by Lipsticks (6.6%)
    • Shaving kits for men were at an additional discount of 3.4%. Hair gel at 4.9% & Face Masks at 4.3%

    BEAUTY Brands that had the highest Share of Search on Amazon during Prime Day

    Brand Visibility against the Keywords
    Brand Visibility against the Keywords

    In the beauty category, Amazon India reported that top-selling brands included Head & Shoulders, Dove, Biotique, L’Oreal, Sugar Cosmetics, and Mamaearth to name a few. Once again, we looked into our data to see the sort of brand visibility & SoS each of these brands had.

    • All the top-selling brand’s Amazon reported on we noticed appeared in the top 5 search results. 
    • Head & Shoulders & Dove were the top 2 listings against the keyword Shampoo at 26% & 16% SoS respectively. Biotique came in at #5 with a 7% SoS
    • Bombay Shaving Company, Gillette, and Axe were the top grooming brands for men in the Shaving Kit category. 
    • Lakme made a clean sweep with a 19% SoS against the keyword lipstick, which speaks volumes, considering the aggressive competition from D2C beauty brands in India today.

    GROCERY

    According to the New eCommerce in India report by consulting firm Redseer, grocery has been a major contributor to the growth of ecommerce in India & Amazon Fresh used Prime Day to grab a larger piece of that pie! As part of the Prime Day sale, Amazon Fresh also pushed discounts on groceries, as well as fruits and vegetables. We tracked products that fell into the “snack” category, and here’s what we saw.

    Discounts on Snacks on Prime Day
    Discounts on Snacks on Prime Day
    • Given changing lifestyles & healthy food fads, it was no surprise that we saw the highest additional discounts were given on Healthy Snacks (3.2%) & Diet Food (2.7%)
    • Chocolates and chips saw much lower additional discounts at 1.2% each.
    • Drinks were additionally discounted by 2.5% during Prime Day.

    SNACK Brands that had the highest Share of Search on Amazon during Prime Day

    Brand Visibility against the Keywords
    Brand Visibility against the Keywords
    • Cadbury had a 69% share of search against the keyword Chocolate, leaving some of its key competitors way behind. Amul had a 20% SoS, while Hershey’s was at just 4%. 
    • According to an article in the Economic times, YogaBar tripled sales in FY22, which is why we were not surprised to see the brand at #1 when users were searching for “Healthy Snacks” during Prime Day. YogaBar products typically enjoy high visibility year-round, which clearly helped with brand awareness on Amazon & sales.

    FASHION

    Amazon reported that Men’s t-shirts and polos, denims, Kurtis, tops, and dresses for women, designer wear, and clothing for kids were some of the most-loved fashion categories on Prime Day. We looked into our data to see the trends that emerged.

    Discounts on Fashion on Prime Day
    Discounts on Fashion on Prime Day
    • From the categories we tracked, women’s handbags had the highest additional discount (11.8%), followed by watches (9.1%)
    • Sneakers & jeans had additional discounts in the ballpark of 7% and sunglasses at 4.4%

    FASHION Brands that had the highest Share of Search on Amazon during Prime Day

    Brand Visibility against the Keywords
    Brand Visibility against the Keywords
    • Some of the usual suspects made it to the top 5, but what really stood out for us were brands that popped up against the keyword Jeans. While Levi’s came in at #2 with an 11% SoS, 2 Private Label Amazon brands featured in the top 5! Symbol at 27% SoS and Inkast Denim at 9%
    • Against the keyword Handbag, Lavie had a massive lead at 38% v/s the #2 brand – Caprese, at 13%
    • Boat found a #2 spot against the keyword watches, racing way ahead of the age-old popular brand Fastrack at #5 with a 4% SoS.

    Conclusion

    Amazon Prime Day 2022 in India came to a successful close as shoppers across India discovered the joy of the 2 day celebration with the best deals, savings, new launches, and more. Prime members from 95% of pin codes in India made purchases, there were 1000’s of deals and 500+ new product launches from brand partners & sellers. Nearly 18% more sellers grossed sales over INR 1 crore, and close to 38% more sellers grossed sales of over 1 lakh vs Prime Day 2021. Local neighborhood shops that sell on Amazon witnessed 4x sales growth. And start-ups and brands under the Amazon Launchpad program witnessed a growth of 3x. All in all, a successful event for everyone involved! 

  • Prime Day Germany 2022 – highlights from the 2 day annual shopping festival!

    Prime Day Germany 2022 – highlights from the 2 day annual shopping festival!

    In 2022, Amazon sold 300 million products during Prime Day – selling roughly 100,000 items per minute. Since Amazon started Prime Day in 2015 to celebrate its 20th birthday, the shopping festival has grown into a holiday and rivals Black Friday and Cyber Monday in the U.S. and Singles’ Day in China. 

    According to RetailDetail, the leading B2B retail community in Benelux, Amazon is planning a 2nd Prime Day shopping festival in the autumn, just a few months after its annual Prime Day event. The retailer has asked its sales partners to prepare for a promotional event in the autumn where they have until the beginning of September to propose attractive discounts, with at least 20% discounts. This year’s second Prime Day may occur in October, with or without the same name. 

    But before that, let’s examine what happened in Germany this year on Prime Day 2022.

    Methodology

    • We tracked Amazon.de both before & on 12 & 13th July 2022, on Prime Day.
    • Categories Tracked – Electronics, Wine & Spirits, Grocery, Furniture, Fashion, and Beauty. 
    • We looked at Additional Discounts offered on Prime Day: Additional Discount is the extra discount on an item during Prime Day when compared to the Pre-Prime day price.
    • We also looked at Post Prime Day Discounts, which were the discounts offered after the 2-day event ended.

    What kind of Discounts did Amazon.de offer?

    Amazon Prime Day will be significant, especially for customers hoping to get discounts amid soaring inflation. Both Amazon as well as other sources reported that electrical and electronic items were the most popular purchases, followed by general retail products. Electrical and electronics saw the value of transactions soar 90% on the first day. Mobile phones and accessories were the most popular, with transaction values almost doubling to 96% on day one.

    Discounts across Categories on Amazon.de
    Discounts across Categories on Amazon.de
    • Based on trends from past events, Amazon likely knew electronic items were going to be best sellers. Keeping this in mind, they made sure to offer high discounts in the electronics category. They offered a 6.5% additional discount on electronics on Prime Day. And once the sale ended, they continued to discount electronics by 1.3%.
    • The Fashion category also had a fair bit of discounts and came in at a close second at 5.9%
    • Looks like Amazon discounted everyday use items minimally. Groceries had an additional discount of just 1.8% on Prime Day, and wine and spirits had 2% extra discount.  
    Discounts on Electronics Category on Amazon.de
    Discounts on Electronics Category on Amazon.de
    • Within Electronics, in the four categories we tracked, we saw the highest additional discounts were offered on Bluetooth earphones (10.6%) and Smartwatches (9%)
    Discounts on Fashion Category on Amazon.de
    Discounts on Fashion Category on Amazon.de
    • Jeans and Sunglasses had the highest discounts at 8.6% & 7.6% respectively.
    • Sneakers & Watches too had additional discounts of 6.6% on Prime Day.
    • Post the Prime Day event, Amazon retained an average of 1.5% discount across all products in the fashion category instead of pricing them at the original price. 
    • However, in the case of women’s T-Shirts, they increased the price by 1.7% from the pre-event price.

    Discounts across Price Tiers

    Retailers must consider several factors when making strategic discounting decisions, including customer buying behavior, the type of discount offered & the volume of discount offered. The best discounting approach will vary depending on the product and other factors like the original selling price of the product.

    Now let’s compare the discounting strategy Amazon used in the Electronics v/s Fashion category on Prime Day.

    Discounts across Price Ranges
    Discounts across Price Ranges
    • Interestingly, in both the Electronics and Fashion categories, Amazon increased prices for the lowest-end products between the €0-10 range by 3.6% and 13.2%, respectively, during the sale instead of discounting them! Maybe this was a strategy to drive consumers to higher-value products with greater discounts? 
    • Another similarity in strategy was that most of the mid-priced items had maximum discounts. In electronics & fashion both, the maximum discounts were given to products between the € 30-100 range. 
    • Here’s a difference that stood out – for Electronics in the higher price range between €100 – 500, the volume of discounts dropped a bit which meant Amazon gave moderate discounts on high-end electronics. But the trend flipped for Fashion as luxury fashion items were made to look more attractive with higher discounts.

    Monitoring stock availability during key sales days is critical

    Brands need to have the right stock availability, especially during sale events, because more customers shop online during sales. What’s worse, non-availability of products may drive customers to competitors that are stocking the same product.  Out-of-stock situations lead to missed opportunities & lost sales! Let’s take a look at our data and see how Amazon planned product availability across categories on Prime Day. 

    Availability Analysis across Categories on Prime Day
    Availability Analysis across Categories on Prime Day
    • Amazon was betting big on 2 categories – Electronics & Home. This meant they needed to keep a keen eye on availability in these categories, especially since they forecasted the highest sales to be generated here.
      … it was no surprise that the Furniture category had almost 100% availability during Prime Day! Electronics too had a high availability at 94% during the event.
    • Generally, our data showed that availability across multiple categories we tracked seemed robust and above 80% in more cases. Only Beauty & Grocery had 79% availability.

    Conclusion

    Prime Day sales reached an estimated 12 billion U.S. dollars worldwide, 9.8% higher than last year, making it the most successful shopping event in Amazon’s history. If you’re a brand selling on Amazon or a retailer trying to compete with Amazon, reach out to us at DataWeave to know how we can help!

  • The Role of eCommerce in Sustainable Fashion

    The Role of eCommerce in Sustainable Fashion

    Today, environmental damage is rapidly occurring on a global scale. And there are many reasons and causes for this. Global warming is one, deforestation, over population are some others. The list is long. In a small way, the retail & clothing industry contributes to environmental damage too. The good news is that sustainable fashion addresses this issue. Sustainable clothing is designed using sustainable fabrics like organic cotton, hemp, and Pima cotton that have less of a negative impact on the planet. 

    sustainable clothing and its benefits
    Sustainable clothing and its benefits

    In this blog, we will discuss the rise of sustainable clothing and its benefits. We will also discuss marketplaces for sustainable fashion.

    Benefits of Sustainable Fashion

    a. Reduces carbon footprint

    The fashion industry emits numerous greenhouse gases annually. Most clothes are made from fossil fuels and require significantly more energy in production. Sustainable brands often use natural or recycled fabrics that require less chemical treatment, water, and energy. Organic fabrics such as linen, hemp, and organic cotton are biodegradable and environmentally sound.

    b. Saves animal lives

    Leather isn’t a by-product of the meat industry, and it’s estimated that it alone is slaughtering and killing over 430 million animals annually. Sustainable fashion brands are increasingly embracing the use of cruelty-free alternatives. Various alternatives include polyester made with ocean trash, plant-based compostable sneakers, bags from recycled seatbelts, silk created from yeast, and bio-fabricated vegan wool. Another interesting leather alternative comes from pineapples, where the fabric is produced using the leaves of pineapples.

    c. Requires less water

    Water is used in the dyeing and finishing process for nearly all items in the fashion industry. It takes 2,700 liters of water to produce a single T-shirt. Cotton is highly dependent on water but is usually grown in hot and dry areas. Linen, hemp, Refibra, and recycled fibers are some other sustainable fabrics that require little to no water during production.

    d. Supports safer working conditions

    Endless working hours, unacceptable health & safety conditions, and minimum wages, are the reality for most garment workers in the fast fashion sector. A few informative documentaries like “The True Cost” or “Fashion Factories Undercover” document the social injustices of the fast fashion industry. Eco-ethical brands advocate for sustainable fashion, health care, humane working conditions, and fair wages for their workers. 

    e. Healthy for people and the environment

    Fast fashion products often undergo an intense chemical process where 8,000 types of chemicals are used to bleach, dye, and wet process garments. Those chemicals often lead to diseases or fatal accidents for workers and inflict serious congenital disabilities on their children. These chemicals harm our health, as our skin absorbs anything we put on it.

    5 Sustainable & Ethical Online Marketplaces

    Here is a list of five earth-minded and socially responsible marketplaces that have sustainable and fair trade brands for the discerning and mindful shopper:

    1. thegreenlabels

    Netherlands-based webshop thegreenlabels is a sustainable fashion retailer that sells sneakers, womenswear, and accessories from various “green labels” brands. Founded in 2018, this is a marketplace where people can buy products from brands that care about a positive impact on the environment. All brands featured here guarantee fair working conditions and represent at least one of these 4 values – “CLEAN PROCESS” environmentally friendly production, clothes that support “LOCAL” communities, “VEGAN” brands to assure no animals were harmed and “WASTE REDUCTION”

    2. LVRSustainable

    LVRSustainable
    LVRSustainable

    Luisa Via Roma started as a family-owned boutique in the early 1900s. They have grown into a luxury e-retailer and created an LVRSustainable section for people trying to insert sustainability into their wardrobes. They have brands rated ‘Good’ or ‘Great.’ The site offers a wide range of products like bags, accessories, sports, shoes, lingerie, and much more for men, women, and kids. You can find organic, vegan, eco-friendly, ethical, and recycled & upcycled items here.

    3. Brothers We Stand

    Brothers We Stand
    Brothers We Stand

    Brothers We Stand is a retailer set up in solidarity with the people who make our clothes. This retailer conducts rigorous research to ensure that every product in their collection meets the following three standards: designed to please, ethical production, and created to last. It’s a great platform to shop for ethical and sustainable menswear. They also have their private clothing line along with other brands.

    4. Labell-D 

    Labell-D was launched with a clear mission to reduce the negative impact of fast fashion on the planet. This retailer wants to make Responsible Fashion the new norm. They intend to make sustainable clothing and fashion easy for both brands and consumers. Labell-D has a transparent accreditation process where they evaluate the brand’s carbon footprint and environmental impact. Their verification assessment includes animal welfare, emissions, materials, production processes, chemical usage, waste management, and traceability.

    5. Cerqular

    Cerqular wants to make sustainable shopping affordable and accessible for all. The retailer promises that every product and seller is verified as organic, recycled, sustainable, carbon-neutral, eco-friendly, vegan, or circular. They have a wide range of sellers and do not limit products only from luxury brands, so sustainable shopping is no longer expensive or inconvenient.

    Conclusion

    The fashion industry is a contributor to worldwide carbon emissions. Sustainable fashion is the new big thing giving rise to more and more sustainable brands and marketplaces. 

    To stand out and shine in the crowded eCommerce space is not easy. Having a robust Digital Shelf becomes critical for brands. A brand’s Digital Shelf is all of the ways their customers digitally interact with the brand, not only on marketplaces but on the brand’s DTC website & shoppable social media. This is why brands need to closely track & optimize their Digital Shelf KPIs like assortment, availability, pricing, ratings & reviews, product discoverability & product content to increase their online sales.

    Want to learn how DataWeave can help you win the Digital Shelf? Sign up for a demo with our team to know more.

  • U.S. Prime Day Deals 2022: Promotion Intelligence First Look

    U.S. Prime Day Deals 2022: Promotion Intelligence First Look

    As inflation hits another 40-year high at 9.1 percent, U.S. consumers geared up for their first sign of hope and relief in the form of anticipated discount buys – 2022 Amazon Prime Days, or so we thought. While Prime Days have grown to become a promotional period almost as important as Black Friday to digital shoppers, the combination of economic uncertainty, inflationary pressures, and supply chain challenges seemed to alter the discount strategy expected given activity seen during 2021 Prime Days.

    Our analyst team has been hard at work aiming to provide a ‘first look’ at 2022 Prime Day Promotional Insights, tracking discounts offered across 46,000+ SKUs within key categories like Electronics, Clothing, Health & Beauty and Home, on seven major retailer websites – Amazon, Target, Best Buy, Sephora, Ulta, Lowe’s and Home Depot. Our analysis compares prices seen during Amazon Prime Day 2022 on July 12th, to pre-Prime Day maximum value prices seen in the ten days leading up to Prime Days, to determine the average change in discounts offered during the promotional period. Below is a summary of our findings.

    Competitive Promotions Give Amazon a Run for their Money

    Amazon offered the greatest average discount enhancements for Electronics at 5.6 percent followed by Health & Beauty items at 5.1 percent, and Home products at 4.2 percent versus pre-Prime Day discounts seen across the categories considered within our analysis. The only category reviewed where average discounts were greater on a competitor’s website was on Target.com within the Clothing category. As seen below, Clothing on Target.com average discounts were 6.8 percent greater than pre-Prime Day offers, which was 2.6 percent higher than the average discounts offered for Clothing on Amazon.

    Target Capitalizes on Growth Opportunity in Clothing Category

    Diving deeper into the details of where Target won within the Clothing category, you can see a majority of their promotional activity took place within Women’s Accessories where discounts offered were 18.5 percent greater than those seen pre-Prime Day 2022, which was almost 15 percent greater than the discount enhancements seen on Amazon for Women’s Accessories. In fact, Women’s Shoes and Sneakers were the only two categories where the average discounts offered were greater on Amazon than on Target.com.

    Overall, the discounts offered on Target.com within the Clothing category were primarily concentrated within items priced $40 and lower, but what was most interesting is that within the $10 and under price bucket, Target offered average discounts of over 11 percent whereas Amazon increased prices for these items on average by over 9 percent.

    While most of the Clothing available on both Amazon and Target.com during Prime Days 2022 were offered without a price change, the greatest discount percentages tracked were within the range of 10-25 percent off on Amazon whereas Target chose to offer the bulk of their promotions at 25 percent off an up.

    Strategic Promotional Strategies Defined at the Electronics Subcategory Level

    When it comes to the Electronics category on Prime Day, the big question is always who will win the battle of the brands. Below shows the difference in average pricing and promotions discounts offered between products manufactured by Samsung versus Apple across each retailer platform, noting discounts were almost 3 percent greater on average for Apple versus Samsung products on Amazon, and Apple discounts were almost 5 percent greater on Amazon versus than those seen on Target.com.

    Amazon wasn’t going all in on Apple however, as we saw ‘Alexa’ devices (Amazon products) available on Best Buy and Target websites also, but the discounts were almost 4 percent greater on Amazon versus Target and over 7 percent greater than the discounts seen on BestBuy.com.

    While the average discounts offered within the Electronics category were greatest on Amazon (5.6 percent) versus Best Buy (3.9 percent) and Target (3.4 percent) as noted within the first chart of this blog and across brands and technologies considered above, the discounts offered on Amazon were strategically focused between 10-25 percent as seen below.

    Amazon’s Electronics promotions were also targeted at smaller price points, items priced between $20-500, whereas Best Buy and Target offered greater promotions for electronics priced $500 and up than Amazon.

    Below is a snapshot of price buckets tracked for Electronics available on BestBuy.com, highlighting where most of the promotional activity was targeted at products priced $50 and up during Prime Days 2022, with discounts ranging from 10 percent up to greater than 25 percent greater than pre-Prime day prices.

    The standout categories were TVs on Target.com with discounts averaging nearly 12 percent greater than those seen pre-Prime day, and smartphones on BestBuy.com with discounts averaging just over 11 percent greater than those seen pre-Prime Day. The category with the greatest average discount enhancements seen on Amazon during Prime Days 2022 was for Wireless Headphones with an average discount of 8.7 percent.

    Home is Where Amazon’s Heart Was on Prime Day

    Amazon dominated offers within the Home categories, especially for products within mid ($40-100) and higher price ranges (items priced $200-500), with the bulk of the discounts offered between 10-25 percent. There was little to no promotional activity seen across all price points on Lowe’s or Home Depot’s websites within the categories we tracked, and most other competitive offers on Home products were seen on BestBuy.com for products priced from $50-500. Even a subcategory like Tools offered deeper average discounts on Amazon (4.7 percent) than discounts seen on HomeDepot.com (1.1 percent) or Lowes.com (0 percent).

    For Large Appliances, Amazon was the only retailer to off any significant discount across each major subcategory with the greatest average discount being on Ovens at 6 percent, followed by Refrigerators at 4 percent. One caveat with this category, when we reviewed Large Appliance prices two weeks prior to Prime Days, we saw average price increases around 16.7 percent occurring on Amazon.

    During Prime Days 2022 however, Amazon also offered top average discounts for small appliances, except for on Instant Pots which appeared to have greater average discounts on Target.com (5.9 percent versus 4.2 percent on Amazon), and Vacuum Cleaners which appeared to have the best promotion of appliances small and large at 13.8 percent average discount on BestBuy.com. Another subcategory deeply discounted on BestBuy.com was weighted blankets, which averaged discounts around 18.5 percent versus Amazon’s average discount at only 6.2 percent.

    Health & Beauty Retailer Pricing Strategies Revealed

    Given the importance Health & Beauty Brands placed on Prime Day sales last year, we had anticipated to see more offers, especially within pure-play beauty retail channels, than we did for this booming category.

    Amazon drove most of the Health & Beauty offers seen averaging 5.1% discounts versus other retailers only offering less than 1% on average, but discounts were aimed at a targeted group of SKUs on Amazon, bringing the average discount lower overall. Most of the promotions offered on Amazon fell within mid-range price points ($20-50) and were discounted between 10-25 percent versus pre-Prime Day prices.

    Target.com offered the most comparable discounts to Amazon for Health & Beauty products on average, but their strategy primarily focused on items within the $20 and lower price range with discounts ranging primarily between 10-25 percent.

    More 2022 Prime Day Insights Coming Soon

    We know the significance visibility to critical pricing and promotional insights play in enabling retailers and brands to offer the right discounts to stay competitive, especially during promotional periods like Prime Days. While this blog is intended to provide a ‘sneak peek’ into 2022 Prime Day insights for the U.S. market, we will be providing more extensive, global coverage and will proactively share new insights with the marketplace as they become available throughout the month of July.

    Be sure to also check out our Press page for access to the latest media coverage on Prime Day insights and more. Don’t hesitate to reach out to our team if there is any particular category you are interested in seeing in more detail, or for access to more information on our Commerce Intelligence and Digital Shelf solutions.

  • The challenges in scaling a ‘House of Brands’

    The challenges in scaling a ‘House of Brands’

    Let’s start with the basics – what is a ‘House of Brands.’

    House of Brands is a portfolio management strategy that defines how a family of brands owned by one parent company, each independent of one another and each with its own audience, marketing, look & feel operate in harmony with each other. 

    Advantages of a House of Brands Strategy

    • The Profit Playbook: The playbook generated by the success of one brand can be leveraged to scale other brands.
    • Economies of Scale: Cost across Marketing, Supply chain, Advertising, and Operations gets shared across multiple brands helping optimize costs.
    • Market Coverage: Multiple products enable brands to cover multiple market niches and audiences while maintaining unique messaging for each niche. 
    • Future-Proofing: By hedging bets across multiple brands, it cushions the parent company against changes in customer preferences and trends. 

    … for these reasons and more, it’s no surprise that every digital-first consumer brand today aspires to leverage a portfolio strategy to become a House of Brands.

    More and more companies are slowly adopting this strategy

    • In the US the brands like P&G, Newell, and Unilever which found early success in the online space are quickly acquiring more brands and betting on the “House of Brands” strategy to scale.
    • In India, Unicorn D2C start-ups like MamaEarth, Good Glamm Group, Sugar Cosmetics, Rebel, Boat, and Lenskart to name a few, are already knee-deep into this strategy as their brand portfolio keeps growing.
    • And then there are brand roll-ups like Thrasio, Perch, HeyDay in the USA, Branded, Hero in the UK and Mensa, and GlobalBees in India which started as a House of Brands from the get-go.

    More Brands. More Data. More need for Monitoring!

    You cannot improve what you cannot measure! In order to scale these brands, the first thing needed is DATA. Data across all digital platforms – data on social media performance, customer engagement, eCommerce sales, product stock availability, pricing, reviews, and customer sentiment to name a few. This data will unlock huge value for brands and it gives them a sense of what’s working and what needs to be improved in order to increase sales & scale. 

    All brands need to track this information – but here’s a challenge unique to a House of Brands – it is the sheer volume & scale of data needed across multiple brands across multiple digital platforms! For example, a House of Brands with let’s say 10+ brands, each brand with 50 SKUs, selling on 10 eCommerce platforms is the equivalent of managing 10 retail shops with 500 SKUs! 

    Let’s look at some of the questions the analytics, marketing, and brand management teams at House Of Brands would ask. And the data they would need almost on a daily basis for every single brand. 

    • What is the search ranking for all of our SKUs across each and every single eCommerce store it is available on? How does this benchmark to the closest competitor? And are competitors using aggressive advertising strategies to outperform & overshadow our SKUs?
    • Are competitors offering discounts? Are those discounts higher than what we’re offering leading customers to purchase their products instead of ours?
    • Are my products & SKUs available and not out of stock across every single marketplace and online store?
    • Are positive ratings & reviews driving my customers to purchase my product? Or do our competitors have a better customer perception than my brand does?
    • Are Amazon and other marketplaces displaying my product content correctly so customers have enough information to make an informed purchase decision?

    … if the sheer scale across multiple brands was not a big enough challenge when this data needs to be tracked hyper-locally for each brand, it becomes anyone’s worst data nightmare!

    Need Data? Lots of it? No problem!

    To get ample data, across key KPIs brands need to invest in a Digital Shelf Solution. However, traditional Digital Shelf Solutions were built for brands that got a majority of their revenue from in-store sales and only a part of their revenue was being generated online. 

    That’s where DataWeave is different. DataWeave’s AI-Powered Digital Shelf Solutions was built with Digital Native brands in mind. 

    What KPIs do we help House of Brands track?

    • Keyword Search Ranking: Track & improve your search rankings for priority keywords. Boost product visibility and sales
    Keyword Analysis
    Keyword Analysis
    • Content: Optimize your brand’s product content to drive up conversions
    Content Quality Analysis
    Content Quality Analysis
    Availability Analysis
    Availability Analysis

    The following metrics are available to view in one single dashboard, across multiple online stores and multiple geographies making it so easy to get a consolidated view of the health of the entire portfolio of products! What’s more, we’ve created a dashboard with multiple views – brand-wise, function-wise & even hierarchy-wise. This means a brand manager can see all KPIs specific for only the brand they manage, while the marketing team can look at keyword search rankings across all brands and the leadership team can see a brand-level daily scorecard for a quick health check. And that’s not all! Our dashboard highlights insights that can be “actioned asap” to make it easier to understand what critical tweaks and changes can help improve sales. Lastly, as a House of Brands adds more Brands & SKUs to its portfolio, our solution has the full flexibility to add and delete SKUs on the go!

    If you are a House of Brand and wish to explore how some of the problems you face daily can be solved – please email: contact@dataweave.com.

    Brand Roll-Ups and House of Brands are always scouting for new brands to acquire. DataWeave has a unique product to help you track a category daily, highlighting brands that show exceptional KPIs across – Ranking, Reviews, Ratings, Bestseller ranks, Sales Estimates, etc. Read more about how VC’s & Brand Rolls up are using Data for faster Acquisitions. 

  • How short term Stockouts on Amazon can have a long-term impact on your eCommerce business

    How short term Stockouts on Amazon can have a long-term impact on your eCommerce business

    It’s common knowledge that upward of 70% of Amazon customers never scroll past the first page of search results. And that the first 3 products garner 64% of business generated. This is why it is critical for brands and businesses to make sure they rank well on Amazon. A good search ranking helps customers find your product with ease. And findability is fundamental! Having a better ranking is also a driver of the “flywheel effect” at online retailers. According to this effect, products that sell more tend to rank better in search results, and products that rank well in search results tend to sell more.

    Negative impact on Sales Ranking due to Stockouts

    If you want to stay on top of search rankings on Amazon, one of the things you need to keep an eye out for is your product stock availability. It’s not the ideal customer experience to have to click on a product listing only to find out it’s currently out of stock. This is why Amazon will not rank products at the top if they’re not available & customers cannot buy them immediately. Not only does this lead to a lost sale for a brand, to make things worse, but customers also end up buying a competitor’s product instead. 

    We were tracking product availability on Amazon for one of our customers in the CPG space. We tracked availability for products across varying ranks & looked at how going out of stock impacted their search rankings.

    Product Availability
    Product Availability

    Impact on products with a Search Rank between 1 to 10:

    • Our data showed that when products that ranked between 1-10 went out of stock for just 1 day, their rank fell by over 28%. After 3+ days of being out of stock, their rank fell by 83% and after being out of stock for over 10 days their rank fell by close to 150%! 
    • This clearly illustrates that when the longer top-ranking products are out of stock, the greater the impact on search rank and product discoverability.

    Impact on products with a Search Rank between 10 to 20:

    • The impact of being out of stock on products that ranked lower, i.e. between 10 to 20 was much lower. After being stocked out for 1 day, the ranking fell 17% compared to the 28% dip for products in the top 10 ranks. 
    • Incremental change was minimal, too. After 3+ days of being OOS, search rank dropped by 22% and by 53% after 10+ days v/s close to 150% for higher-ranked products.

    Impact on products with a Search Rank between 20 to 30:

    • These products had the least impact but there was an impact nonetheless. 
    • After being OOS for 5+ days, search ranking fell by close to 8% and to close to 30% after 10 days of product unavailability.

    Avoiding Stockouts with better Inventory Management

    Customers can buy your product only when it is available. Failing to provide products at the right time will lead to losing sales to your competitors. If your products become unavailable, you’ll notice a drop in customers’ overall satisfaction and shopping experience too in addition to a lost sales rank on Amazon. In fact, your reputation and sales will take a beating long term in case of consistent product unavailability. Moreover, once the product is back in stock, the climb back to the top ranking is a slow and not-so-easy process. This is why brands need to maximize conversions by tracking product availability on a constant basis.

    Conclusion

    Stockout is a critical issue that has a significant impact on sales, brand image, and customer loyalty. Items ranking higher on eCommerce platforms take the biggest hit when they get out of stock. Brands can recapture their search share after restocking their inventory. 

    Want to maximize sales by reducing latency periods between stock replenishment? Reach out to our Digital Shelf Experts to know how! 

  • Feminine Hygiene Products Face Supply Chain Shortage and Price Increases

    Feminine Hygiene Products Face Supply Chain Shortage and Price Increases

    Last week the DataWeave analytics team identified the states most impacted by the baby formula shortage, only to see feminine hygiene products following similar trends with price increases occurring alongside a supply chain shortage. In this analysis, the team has identified over four hundred feminine hygiene products made available across eighteen retailer and delivery intermediary websites from August 2021 through June 2022, to see how product availability and price changes correlated.

    Within the feminine care products analyzed, both tampons and sanitary pads show to have under 58% availability as of June 2022. For sanitary pads, June 2022 shows the lowest level of product availability at around 58%, which has steadily declined each month from August 2021 where product availability started around 69%. Tampons however, reached their lowest level of availability in April 2022 at 45%, and appear to be slowly recovering each month, now reaching around 53% availability in June 2022.

    Product Availability for Feminine Care Products - June 2022
    Product Availability for Feminine Care Products – June 2022

    The Evolution of the Tampon Shortage by Retailer

    Looking at tampons in more detail and at a retail level, we can see how much and how often product availability fluctuated from August 2021 through June 2022 across Kroger, Meijer, Baker’s Plus, Target and Walmart websites. Baker’s Plus, for example, shows the lowest product availability, maintaining an average of around 39% from October 2021 through June 2022. Kroger appears to be a notable exception only facing stock availability issues in March and April 2022, achieving nearly 78% availability in June 2022, which is 16% greater than the other retailers analyzed.

    Product Availability for Tampons by Retailer - June 2022
    Product Availability for Tampons by Retailer – June 2022

    Feminine Care Product Price Changes Over Time

    When looking at Pricing Intelligence insights and average price changes occurring alongside declining product availability for tampons and sanitary pads combined, we see a very different story. Tampons have seen steep price hikes from December 2021 onward, increasing the most in June 2022, up 6% compared to prices seen in November 2021. This steep price increase could be attributed to consistently low availability for tampons that has been seen in recent months.

    To the contrary, sanitary pads have seen a price reduction of around 1.25% as of June 2022 compared to average prices seen in November 2021. While prices are lower in June 2022 for sanitary pads, the percentage by which they are lower is shrinking in recent months, potentially for the same reasons related to decreasing product availability.

    Price Change for Feminine Care Products - June 2022
    Price Change for Feminine Care Products – June 2022

    When looking at month-over-month average price changes for tampons only, we can clearly identify which months had the biggest price changes, noting price hikes that lead to the currently high prices seen in June 2022. In March and May 2022, over 10% of tampons offered had seen a price increase, and around 8% had seen significant price increases of more than 10%.

    Month-Over-Month Price Changes for Tampons - June 2022
    Month-Over-Month Price Changes for Tampons – June 2022

    eCommerce Intelligence Provides Early Visibility to Evolving Trends

    Price increases don’t seem to be stopping anytime soon given there was a 3.6% price hike seen on average in May 2022 versus April, with June seeing yet another .6% increase from May’s prices. That being said, as the market evolves and feminine hygiene products stabilize, our team will continue to provide visibility to critical pricing and product availability changes to enable our clients to stay ahead of the curve.

    From a baby formula shortage to a tampon shortage, what category will be next to follow the supply chain shortage trend? Follow our blog for access to the latest insights and be sure to reach out to our team if there is any particular category you are interested in tracking next, or for access to more information on our Commerce Intelligence and Digital Shelf solutions.

  • 7 Key Metrics that QSRs want (but may not get) from Food Delivery Apps

    7 Key Metrics that QSRs want (but may not get) from Food Delivery Apps

    The Quick Service Restaurant market is projected to be valued at $691 billion by 2022. As the QSR industry grows and the market becomes even more competitive, restaurant chains continuously seek ways to increase sales via food aggregators to market their business. To improve ROI and sales, having data and insights into key metrics could help QSRs to boost their success rate.

    QSRs would like to know how they stack up against their competition regarding discoverability on cluttered food aggregator apps. Restaurants want to know the gaps in their product assortment to understand what drives customers to their competitors. Getting insights into delivery time and competitors’ delivery fees will help QSR improve delivery ETAs and optimize fees. They can also set competitive pricing with insights into their competitors’ pricing. In addition, they can use data to optimize their ad spending on food apps and improve marketing ROI.

    In this blog, we will discuss the relationship between QSRs and food aggregators and how getting data about key metrics from these food delivery platforms can help QSRs scale their revenue. 

    Data: The Key Ingredient to increasing sales

    According to Statista, online food ordering revenue is expected to grow at a robust CAGR of 10.39% between 2021 and 2025. Food Aggregators apps like Uber Eats, DoorDash, and GrubHub offer convenient meal delivery options from various QSRs within a single app. Food aggregators provide a multitude of benefits for QSRs. They give access to a huge customer base, quick delivery, and an easy entry into quick commerce, helping QSRs increase visibility. Although QSRs rely on food aggregator platforms for hassle-free ordering, tracking, and delivery, they can’t always rely on them to share critical data that could help them optimize their operations & increase sales. 

    Online food ordering revenue
    Online food ordering revenue

    1. Data on Product Assortment

    QSRs need assortment insights to understand their competitor’s menu assortment. Assortment analytics plays a crucial role in ensuring that QSRs aren’t losing sales because their competitors are offering cuisines and dishes that they aren’t. Understanding gaps in menus helps QSRs to better plan their menu. However, food aggregator apps can’t share competitors’ assortment data with QSRs for a multitude of reasons, guidelines, and privacy laws. Thankfully, at DataWeave, our QSR intelligence solution can! We help restaurants improve their assortment by sharing insights into the dishes and cuisines their competitors’ have on display.

    Menu Assortment
    Menu Assortment

    2. Data on QSR Discoverability

    QSRs would love to know how to increase discoverability on food aggregators, as it will help them to appear ahead in search results and beat the competition. Improving visibility on these apps directly impacts sales and drives more orders for restaurants. Some aggregators offer discoverability information but give it on demand, usually after 20-30 days, making it irrelevant due to the enormous time gap. They also don’t provide information about the change in the discoverability of your competition. All these data points are so critical, and understandably so, Food Apps can’t share this level of information with restaurants. However, DataWeave’s QSR Intelligence solution can! It provides real-time discoverability insights into your restaurant and competitor’s visibility so that the data is actionable, and QSRs can use insights to improve visibility. 

    Read how DataWeave’s QSR Intelligence helped an American QSR Chain and how their ranking on search results page on Ube rEats, DoorDash & Grubhub impacted outlet discoverability & sales!

    3. Data on Pricing & Promotions

    Pricing a QSR’s menu is tricky. If you price too high, you’ll turn off new customers. If you price too low, you’ll cut margins & may even come off as low-qualify. Customer Price Perception is greatly influenced by the Price-Quality relationship. To add to this, restaurants are often up against stiff competition from restaurants with similar cuisine offerings so it’s critical that prices are competitive. Understanding competitor pricing doesn’t imply that you have to beat their prices. You can compensate for any price differences by offering higher quality cuisines, better customer service, and quicker delivery. Once again, food apps can’t share competitors’ pricing data with QSRs. But DataWeave’s QSR & Pricing Intelligence solution can! QSRs can use these insights to drive more revenue & margins by pricing their menu right.

    4. Data on Delivery Time

    QSRs must be able to deliver hot meals, in a timely manner to customers because customers want to quickly dig into the delicious food they ordered. Quicker deliveries within the ETA will also help earn the trust and loyalty of customers. However, food aggregators don’t share information on the delivery times with restaurants – not their own delivery time or their competitors. DataWeave can help QSRs to understand their peak hours and optimize their service to ensure quick ETAs. They can also get detailed insights into competitors’ delivery times to make sure they’re competitive. This is important because customers will often pick restaurants with quicker ETAs.


    Read how DataWeave’s QSR Intelligence helped an American QSR Chain understand the correlation between delivery time & sales volumes

    Delivery time trend by urbanity
    Delivery time trend by urbanity

    5. Data on Delivery Fee

    As a thumb rule, customers will always compare delivery fees across apps. They’re conscious of delivery dollars included in their bill and often choose a restaurant with lesser delivery fees. This makes it even more critical for restaurants to understand how they stack up against their competitors. Understanding competitors’ delivery fees could potentially help QSRs to optimize their rates. And once again, food aggregators can’t share information on competitors’ delivery fees with restaurants. However, DataWeave’s QSR Intelligence can provide all delivery-related insights – be it Delivery etas or fees. 

    Delivery fee trend by urbanity
    Delivery fee trend by urbanity

    6. Data on Ad Performance & ROI

    Getting ad analytics will help QSRs better manage their budgets & increase the ROI on their Ad spends. For example, wouldn’t it be great if QSRs were able to understand which ad formats or promotions led to the most sales? Or which carousal ads had the most visibility in key zip codes where your QSR is expected to do maximum business? Or even insights into a competitor’s ads and promotions on food apps. Knowing this information will help restaurants spend sensibly when buying media on Food Apps & get the most bang for their advertising buck. Food apps do provide standard ad analytics – a number of clicks, CTR, and so on, but for more complex, insightful & actionable insights, there’s DataWeave’s QSR Intelligence! 

    Read how DataWeave’s QSR Intelligence helped an American QSR Chain understand the ROI delivered on ad spends across Food Delivery apps.

    Insightful & actionable insights for QSR Chains
    Insightful & actionable insights for QSR Chains
    Insightful & actionable insights for QSR Chains
    Insightful & actionable insights for QSR Chains

    7. Data on Outlet Availability / Availability Audit

    To avoid lost sales, being available & “open for business” on Food Apps during peak lunch & dinner hours is critical. Also on weekends, when order volumes are usually high. Sometimes because of technical glitches, QSR outlets appear unavailable on Food Apps. A glitch like that can lead to lost business, and the longer the glitch stays undiscovered, the greater the impact on revenue. While Food Aggregators do their best to make sure all QSRs are up and running on their app, using DataWeave’s QSR Intelligence, restaurants can now do an outlet audit to make sure that’s the case. With just a mere 2.8% unavailability, we saw a 28% drop in the sales for one of our QSR customers! That’s how critical Availability insights are. 

    Conclusion

    Analyzing and optimizing sales, delivery, discoverability, availability & customer data is one of the fastest ways to help grow your QSRs revenue. However, the biggest challenge QSRs face is that it isn’t always easy to get this information. With DataWeave’s QSR Intelligence now some of that data is a little more accessible as we discussed in this blog. And additionally, here are the 7 Tricks we recommend QSRs to use to win on Food Apps. 

  • Baby Formula Shortage Continues Alongside National Price Increases – June 2022

    Baby Formula Shortage Continues Alongside National Price Increases – June 2022

    As the baby formula shortage continues, retailers and brands are working quickly to meet evolving consumer demand, considering supply chain driven headwinds, a baby formula recall, and inflationary-driven impacts. The DataWeave analytics team has actively tracked marketplace changes, alongside reports from the FDA, for the baby formula category at a state-level, and has shared the latest snapshot of product availability through June 7th, 2022, below.

    Average Baby Formula Product Availability by State - June 2022
    Average Baby Formula Product Availability by State – June 2022

    While the U.S. has reached an average of 84% baby formula availability the first week of June 2022, given recent news headlines related to the baby formula shortage, and tracking out of stock encounters by state, we see a continued decline in availability throughout the Midwest versus product availability levels seen in May 2022.

    Wisconsin, Michigan, Illinois, Indiana, Ohio, and Kentucky all show average availability for baby formula to be less than 50%, with Wisconsin being impacted the most at less than 18% average availability. While Texas shows an average availability improvement of 3.5% from the first two weeks of May 2022 to the first week of June 2022 as noted in the below chart, availability is also very low overall at less than 60%.

    Average Change in Baby Formula Product Availability by State: May-June 2022
    Average Change in Baby Formula Product Availability by State – May 2022 to June 2022

    Outside of the Midwest and Texas, the other states for consumers to be cautious in are California, Virginia, and South Carolina as their month-over-month average change in availability also declined 4%, 12.6% and 8.2% respectively. Below is a snapshot of where the baby formula availability average started as of May 1st through the 15th, 2022.

    Average Baby Formula Product Availability by State - May 2022
    Average Baby Formula Product Availability by State – May 2022

    Baby Formula Product Availability Changes – March 2021 through May 2022

    At an aggregated level overall, the availability for baby formula was relatively stable across all retailers considered within our analysis from March 2021 through September 2021, but has been on a steady decline ever since, starting at 81.7% availability in September and ending at 53.8% availability in May 2022 as noted in the below chart.

    Monthly Average Availability for Baby Formula Across Major Retailer Websites
    Monthly Average Availability for Baby Formula Across Major Retailer Websites

    Looking at baby formula availability at a retail level, we saw yet again not all availability challenges were alike, by month or retailer. Costco.com lead the other retailers within our analysis for greatest average availability from March 2021 through May 2022, but had one of the lowest availability percentages at 62.7% in May 2021, and dropped to the lowest availability of the group in May 2022 at 37.5%.

    Average Availability for Baby Formula Across Major Retailer Websites
    Average Availability for Baby Formula Across Major Retailer Websites

    Baby Formula Prices Increase as Availability Changes

    While unnecessary price gouging is prohibited, price increases are still happening at a slow and steady rate across all the accounts included within our Pricing Intelligence analysis given external market factors outside of baby formula recall related stockout scenarios.

    Kroger.com experienced the greatest average price increases overall, with the peak being in May 2022 at a 19% increase, 8% higher than other retailers on average, versus prices seen in March 2021 for the same baby formula products. The most significant price hike occurred on Kroger.com from December 2021 to January 2022. Other retailers like H-E-B, Target and Wegman’s have had minimal price changes from March 2021 through May 2022. 

    Average Price Inflation for Baby Formula, Indexed to March 2021
    Average Price Inflation for Baby Formula, Indexed to March 2021

    Address the Baby Formula Shortage With eCommerce Intelligence

    As the market continues to evolve and baby formula supply works its way to catching back up to demand, our team will continue providing critical pricing, merchandising, and competitive insights at scale, to enable retailers and brands to develop data-driven growth strategies that directly influence their eCommerce performance, accelerate revenue growth and drive profitability.

    Be sure to reach out to our Retail Analytics experts for access to more details regarding the above analysis, or for more information on our Commerce Intelligence and Digital Shelf solutions, and let us know what other category insights you’d be interested in seeing this year.

  • eCommerce in South Africa: Data-Driven approach to getting ahead

    eCommerce in South Africa: Data-Driven approach to getting ahead

    What an exciting month we’ve had at DataWeave! Our team flew down to gorgeous Cape Town, South Africa to attend the 8th edition of #EcomAfrica! After months of Zoom calls and virtual events, it was a refreshing change to see our customers in person and meet some of the movers and shakers in eCommerce and some of the top South African brands. 

    Top eCommerce Companies in South Africa
    Top eCommerce Companies in South Africa

    My last visit to South Africa was before the pandemic. Things have changed since then, & the difference was stark! The eCommerce landscape had a paradigm shift during Covid-19 and grew exponentially. My customers spoke to me about the new opportunities, growth potential as well as challenges that came in because of this boom. For one, eCommerce in South Africa has become more competitive than ever – from online retail to grocery and food delivery to even alcohol delivery! All retail businesses seem to have jumped onto the eCommerce bandwagon.

    A recent Deloitte report found that over 70% of South Africans shop online at least once a month & 2 out of 3 respondents said they plan to increase their frequency of online shopping. 65% said they know what they want, search online & check all stores that stock the product to compare prices. Price is one of the key factors that influence consumer purchase decisions. Other critical factors include delivery fee, delivery time, promotions & discounts & product assortment to name a few. In order to stay ahead in this highly competitive arena, both retailers and brands need to make data-driven decisions about critical KPIs like pricing to stay ahead of the competition.

    Increased Online Shopping & Online Shopping Frequency
    Increased Online Shopping & Online Shopping Frequency

    We’ve been working with customers in South Africa for over 4 years now, even before the pandemic. So on Day 2 of the event – S.Krishnan Thyagarajan “Krish”, President & COO, Dataweave had a chance to share our learnings and experience from all these years and how user data is critical to getting ahead & winning the eCommerce race in South Africa.

    For the purpose of Krish’s keynote address, we tracked pricing insights for a finite set of categories across key South African retailers like Checkers, Pick n Pay, EveryShop, Incredible, Makro, Waltons, Shoprite & Dis-Chem to name a few over a period of 16 months from Dec 2020 to April 2022. We highlighted price increase and decrease opportunities and how each retailer reacted in order to stay competitive, increase sales and protect margins. 

    BATTLE of the eCommerce GIANTS!

    Key Highlights from the Keynote

    • Increasing prices where an opportunity exists helps retailers increase their margins exponentially. Pick n Pay had the highest action rate (73%) when it came to capitalizing on price increase opportunities v/s Dis-Chem at 11%. 
    • When it came to price decrease opportunities (in order to stay competitive with rival brands) Takealot was the most responsive retailer – they capitalized on 30% of the opportunities, followed by Pick n Pay at a close second (28%) and Shoprite & Dis-Chem at just 4%.
    • Most retailers took between 1 – 5 days maximum to make price changes which means responsiveness to the market among all retailers is high making it more important for online retailers to always be on their toes.  
    • The 2 categories where most retailers capitalized on Price Increase Opportunities were Sauces & Condiments and Crackers & Biscuits.

    Want to watch the Keynote video on Demand? Click here to register & watch.

    Price Increase & Decrease Opportunities
    Price Increase & Decrease Opportunities

    Bonus video content! 

    • Watch the Impact of price increase & decrease opportunities on Private Label brands! 
    • See how product stock availability impacts price changes over a 16-month period. 
    • Find out which brands are in the lead in the Skin Care, Pet, Baby, Laundry & Cleaning Aid categories 

    If you’re an online retailer in South Africa & need insights on staying competitive with the right pricing, product assortment, delivery time, delivery rates, and the other key influencers that affect customers’ choice of online retailers, sign up for a demo with our team at DataWeave to know how we can help!  

  • The Rise of South African eCommerce : The Growth, & the Future

    The Rise of South African eCommerce : The Growth, & the Future

    2020 onwards, the South African economy was crippled due to the pandemic and lockdowns. However, according to StatsSA, South Africa’s online retail market share grew to 2.8% in 2020, double that in 2018. After the pandemic, South Africa’s eCommerce industry grew by 66% in 2020 compared to the year before. This increase was primarily because of restrictions on traditional stores that led to a 30% reduction in in-store purchases. 
    According to a Deloitte study, over 70% of South Africans shop online at least once a month because of convenience. Household appliances, footwear, clothing, electronics, and health products are the most popular categories among South African online customers.

    Top Categories
    South African Ecommerce
    South African Ecommerce


    These eCommerce stores account for 15% of online revenue in South Africa

    1. Takealot.com: Revenue US$602 million 
    2. Superbalist.com: Revenue US$85 million 
    3. Woolworths.co.za: Revenye US$57 million

    In this blog, we will discuss emerging eCommerce trends in South Africa and their impact on the various retail segments. 

    Trends to watch in 2022

    Trends to watch
    Trends to watch

    1. Quick commerce

    Quick delivery, especially when it comes to groceries, medicines, and food has become a customer expectation now. Q-commerce, a trend that capitalizes on optimizing delivery time, has become common in food tech companies and is now gaining traction in grocery delivery too, especially after the pandemic. UberEats, Checkers, Pick ‘n Pay, and Jumia is some of the country’s biggest Q-commerce players.

    2. Omnichannel eCommerce

    Omnichannel experience has taken center stage for retailers in South Africa after the pandemic. According to Nielseniq’s study, 30% of South African consumers indicated they had shifted their shopping habits to online shopping from in-person grocery store visits between March 2021 and 2022. 

    3. Digital Payment Trends

    The digital payment ecosystem in South Africa has seen a massive growth trajectory after the pandemic. Customers seamlessly use digital payments across shopping, entertainment, groceries, food, health, and wellness – a trend we suspect is here to stay.

    4. Buy Now Pay Later

    Buy now pay later is an interest-free mode of payment that is popular worldwide for helping customers who cannot make high-value purchases. Consumers don’t have to pay any price upfront and pay off the amount in interest-free installments over a predefined period. The BNPL is forecasted to account for 13.6% of global eCommerce payments by 2024.

    5. Chatbots

    Quick response to customer queries and problems is instrumental in increasing conversion rate and sales. However, it can be difficult to respond to emails and instant chat 24/7 for small businesses. This is where automated chatbots are helping South African retailers answer customer questions promptly and correctly.

    The 4 Fastest-Growing Retail Segments

    4 Fastest-Growing Retail Segments
    4 Fastest-Growing Retail Segments

    1. Online Retail

    eCommerce & online retail grew 20% YOY after the pandemic. Retailers saw a huge increase in the adoption of online shopping by consumers. Traditional brick-and-mortar stores looked for omnichannel opportunities to keep up with online retailers. Mr. Price, a clothing retailer in South Africa, saw a surge in online sales by a massive 90% between April and June 2020. There is a similar success story where OneDayOnly, another South African online retailer, saw 40% growth during the same period.

    … but this growth surge brought in some challenges for retailers too. With more and more customers shopping online, competition increased. Price-sensitive customers would constantly compare prices across online retailers before making a purchase. It became critical for retailers to price their products right to beat the competition & win the sale, without hurting their margins! 

    2. On-Demand Grocery Delivery

    Groceries saw an increase of 54% from 2019 driven by the pandemic & lockdown restrictions.

    South African eCommerce companies offer a wide range of on-demand services, from taxi rides and grocery orders to liquor delivery. Retailers fulfill orders from stores to offer affordable rates and quick delivery across South Africa. It replicates the instant gratification of purchasing products from brick and mortar stores and the added benefits of the hyper convenience of shopping from a mobile or a computer. 

    Read quotes from our customers at Talabat, Glovo & Grab Food – we worked closely with them & helped them in their efforts to scale through this global Q-Commerce boom.

    3. Online Food Delivery

    According to Statista, revenue in the online food delivery segment in South Africa is projected to reach US$0.87bn in 2022. As competition heats up and more and more players enter the market, staying competitive is becoming increasingly challenging for food delivery businesses.

    Bolt Foods SA said they grew 50% month on month in mid-2021 and said they had to bet on making sure they were offering competitive prices in order to get ahead. Additionally, in their quest to have a stronger competitive advantage, Bolt Food says it is also offering customers a very low delivery fee, lower than Uber Eats & Mr. D since delivery costs are a major consideration for customers when using food delivery apps.

    The right price, product assortment, delivery fee, and delivery eta are critical to scaling a Food Delivery business. If you’re in the food-tech business, reach out and we can tell you how DataWeave’s Food Delivery Intelligence can help you scale quickly and profitably! 

    4. Social Commerce

    With approximately 41.19 million South African customers engaging in online activity, there is a huge shift in user behavior as customers get comfortable purchasing directly via social platforms instead of online retailers or physical stores. Social commerce uses networking websites such as Facebook, Instagram, and Twitter as vehicles to promote and sell products and services.

    What matters to South African online shoppers?

    Between June and November 2020, South African consumers mostly used online retailers monthly (42%), food delivery services weekly (36%), and online classifieds less than once a month (34%). 

    Here is a summary of things that matter to South African shoppers when they shop online:

    1. Easy product discovery and competitive pricing

    Most customers start their online shopping with a product in mind and look for discounts and sales across retailers. More than 67% of respondents of a survey have said that they go to a specific online store and search for the product they want. Almost the same share of consumers said they compare online stores to find offers for products they want. Price plays an important part in product selection. 

    In order to offer the most competitive pricing, retailers in South Africa need to keep a keen eye on competitor pricing. They need to identify gaps and opportunities to make price changes to not only offer the most attractive price to customers but also drive more revenue and margins by pricing products right.

    2. Reliable Delivery time

    81% of South African consumers say that unreliable delivery time is one of the reasons that affect their choice of an online store. Quick delivery time has become a differentiator in the eCommerce space, where ‘next day delivery or even ‘same-day delivery’ have become the norm. South African online shoppers want reliable delivery times that suit their busy schedules. 

    Read more here, about how DataWeave helped an America QSR understand the correlation between their delivery time & sales volumes! 

    3. Low delivery fee

    86% of South African customers believe that high delivery fees impact their online stores’ choices. The high delivery cost is a problem for low-income customers and customers who shop daily.
    If you want to track how your delivery fee compares to your competition and how it’s impacting your sales, our Food Delivery Intelligence solutions are for you!

    4. Customer Service

    Your company’s customer service should be responsive, smooth, omnichannel, and hassle-free. 78% of South African customers are frustrated with delays in customer support from online retailers. Slow response times and lack of communication in case of delays, delivery, and refunds hamper the customer experience drastically.

    Customer Service
    Customer Service

    Conclusion

    eCommerce in South Africa is growing at unprecedented rates. There has been a surge in the appetite of South Africans for online shopping and online retailers across the board are gearing up to meet this demand. 

    If you’re an online retailer in South Africa & need insights on staying competitive with the right pricing, product assortment, delivery time, delivery rates, and the other key influencers that affect customers’ choice of online retailers, sign up for a demo with our team at DataWeave to know how can help!  

  • The Future of eCommerce is Social: Demystifying the Social Commerce Revolution

    The Future of eCommerce is Social: Demystifying the Social Commerce Revolution

    Social commerce is the selling of goods and services within a social media platform. Brands use social platforms such as Instagram, Facebook, Snapchat, and Twitter to promote and sell products. These platforms have become an integral part of consumers’ everyday life because they continue to engage users with relatable content, making them scroll their feeds for hours. 

    The Social Commerce model capitalizes on this high user engagement & moves social media beyond its traditional role in the top-of-the-funnel marketing process by encouraging users to shop without leaving their preferred apps. According to the Social Media Investment Report, 91% of executives agree that social commerce is driving an increasing portion of their marketing revenue, and 85% report that social data will be a primary source of business intelligence.

    Let’s talk a little bit about why brands should consider selling via social media platforms:

    Social Commerce vs. eCommerce vs. QCommerce

    While they may fall under the same umbrella of online selling, social commerce, quick commerce, and eCommerce are three very different concepts

    • eCommerce refers to online shopping via a (retailer or brand) website or app. Customers can access these platforms via desktop or mobile devices. However, the sales funnel generally looks the same. These brands and retailers use top-of-the-funnel tactics like social media content, digital ads, and other marketing strategies to encourage customers to visit the online store. There are three main types of eCommerce businesses: Business-to-Business (Alibaba, Amazon Business, eWorldTrade), Business-to-Consumer (websites such as Amazon, Rakuten, and Zalando), and Consumer-to-Consumer (platforms such as eBay & Etsy).
    • Quick Commerce (or QCommerce) refers to eCommerce businesses that deliver goods within a couple of hours or even minutes. Although it’s sometimes used interchangeably with on-demand delivery or instant commerce, the idea of quick commerce has been around in the food industry for ages now. It has been recently ushered into the mainstream by evolving consumer preferences for quicker delivery of groceries and FMCG goods.
    • Social commerce brings the store to the customer rather than redirecting customers to an online store. It removes unnecessary steps and simplifies the buying process by letting the customer checkout directly through social media platforms, creating a frictionless buying journey for the customer. Additionally, social media platforms are mobile-friendly, a huge benefit for brands because increasingly more and more customers are accessing the internet through mobile devices.
    Social Commerce
    Social Commerce

    Rise of Social Commerce

    First used in 2005 by Yahoo!, ‘social commerce’ refers to collaborative shopping tools such as user ratings, shared pick lists, and user-generated content. Social media networks snowballed throughout the 2000s and 2010s, alongside a general increase in eCommerce, leading customers and merchants to quickly recognize the benefits of buying and selling through social media networks. Social media platforms have since evolved from merely a showcase tool for brands. They now serve as virtual storefronts and extensions of a company’s website or brick and mortar stores, capable of handling the buying experience.

    Top Social Commerce Platforms

    Social media platforms aim to keep visitors engaged on their platforms for as long as possible. Increased time in-app or on-site maximizes their opportunity to serve ads, a primary source of revenue generation. Social media platforms have millions of active users and they have a great power to help companies and individuals build their brands, interact with consumers, and support after-sales. Here are the top social commerce platforms:

    • Facebook

    Facebook introduced Facebook Shops to capitalize on the commercial opportunity by allowing vendors to advertise and sell directly through the platform. Facebook integrates social commerce with shopping, allowing users to purchase products smoothly. Facebook shops offer a smooth user experience where users can review products and get recommendations from trusted acquaintances. Customers can directly interact with the merchant’s customer service department post-purchase. 

    • Instagram

    60% of people discover new products on Instagram. Owned by Facebook, Instagram facilitates in-app shopping and handles the entire transactions within the app itself. Users scrolling on Instagram often wants to follow trends and replicate the looks of their role models or favorite influencers. By offering purchasing options in the app, Instagram benefits from the platform’s rich visual imagery and videos, allowing businesses to sell an idea rather than the traditional process of selling a product. 

    • TikTok

    Shopify partnered with TikTok to introduce shopping and drive sales through the younger and seemingly ever-expanding TikTok audience. With TikTok for Business Ads Manager, brands and merchants can create in-feed video-based content depending on their product offering. This partnership allows Shopify merchants to expand to the TikTok audience.

    • Snapchat

    Snapchat has recently launched Brand profiles, a feature that allows users to scroll through a merchant’s products and buy them in-app. This new experience is powered by Shopify too. Merchants can create Brand Profiles or Native Stores that allow users to purchase products from the app. 

    Pinterest users are there for Shopping Inspiration
    Pinterest users are there for Shopping Inspiration
    • Pinterest

    Pinterest is also an image-based platform where users create boards of their favorite wedding accessories, home decor, fashion trends, etc. Pinterest doesn’t specifically offer social commerce for the global audience. Rather, it allows business accounts to create ‘Product Pins’ that are displayed in the brand’s Pinterest shop. Only U.S. customers can purchase within the app. Users from other countries are redirected to the eCommerce site to complete the sale. We have added Pinterest to this list because 89% of Pinterest users are there for shopping inspiration.

    Pinterest is an image-based platform where users create boards
    Pinterest is an image-based platform where users create boards

    Why Should Brands Care About Social Commerce

    • To enhance social media presence and brand awareness

    If your target demographic is in the 18-to-34 age range, they’re already on social media and waiting to shop while they scroll. According to Sprout Social, over 68% of consumers have already purchased directly from social media and nearly all (98%) consumers plan to make at least one purchase through social or influencer commerce this year. You can enhance brand awareness by selling on social media platforms. Influencer marketing is an amazing way to build brand awareness since customers are now seeking authenticity from micro-influencers rather than big-name celebrities. 

    • To generate social proof

    90% of online shoppers say that they read online reviews before making an online purchase. Whether it’s an automated follow-up email or a message through the social media platform, ask for a review after your product has been delivered to the customer. You can also offer incentives like a contest to encourage previous customers to weigh in and share their experiences. These steps will allow you to collect social proof since it’s vital to build a positive reputation online. You can also ask customers to create small product review videos that you can share on your social feeds in creative ways. You can also post user-generated content, create a carousel of positive comments, or host a live video with happy customers.

    Social Proof
    Social Proof
    • To simplify the buying process for consumers

    Traditional eCommerce involves several steps. It starts with displaying ads on social media platforms and customers being redirected to the business website for completing the transaction. To complete the transaction, customers also have to create an account or manually fill in the credit card details and delivery address. On the other hand, social is only a three-step process — find, click and buy. 

    Counterfeit Products
    Counterfeit Products

    Conclusion

    While social commerce is proliferating, it also has a few setbacks like the rise of counterfeit products. Counterfeiting has expanded into social media and has become an under-reported but vital hub for counterfeiters. A counterfeit detection solution can help brands and merchants identify & remove fake and unauthorized products. Technologies like image recognition can help in counterfeit detection by capturing fake logos and discrepancies. Removing counterfeit products will help brands safeguard customer loyalty and prevent fake products from harming your bottom line. 

    Here’s how DataWeave helped Classic Accessories, a leading manufacturer of high-quality furnishings & accessories identify counterfeit products across multiple retail marketplace websites eliminating 22 hours of time spent per week conducting manual audits – read the case study here. 

    Are you a brand or a retailer worried about counterfeits? Sign up for a demo with our team to know how we can help you track, identify and eliminate fakes! 

  • How Inflation has hit the Retail Industry

    How Inflation has hit the Retail Industry

    Inflation has resurfaced after a decade of tranquil price increases. The persistent COVID-related supply chain disruptions have been a driving factor in increasing consumer costs since some commodities are harder to come by. While inflation is a normal economic phenomenon, the current 3.81% inflation rate has increased the cost of living for families across the globe.

    Global Inflation Rate
    Global Inflation Rate. Source: Statista

    Worldwide inflation is expected to remain near 5.0% in early 2022 before gradually easing in response to industrial and agricultural commodity price declines. Additionally, the global consumer price inflation peaked from 2.2% in 2020 to 3.8% in 2021 and will average 4.1% in 2022 before subsiding to 2.8% in 2023.

    In this blog, you’ll learn about the impact of inflation on the Retail Industry. 

    What is Inflation?

    Inflation is an economic term that describes an overall increase in the price of goods and services in an economy, and a by-product of inflation is the devaluation of the currency used within that economy. For example, a clothing retailer that used to pay $8 for a t-shirt two years ago will now have to pay $10 for that exact product. The t-shirt hasn’t changed at all. However, it has become 25% more expensive. Inflation and the devaluation of currency are part of the reasons why they’d now pay $2 more for that same T-shirt.

    Also Read: Top 7 strategies to sell effectively on Amazon

    Impact of inflation on Retail

    FMCG

    The Fast-moving consumer goods (FMCG) sector will continue to grow because there is growth in household goods spending despite the Russia-Ukrainian crisis, global interest rate, and rising fuel prices. In fact, the demand for consumer packaged goods rose sharply in countries heavily affected by the pandemic. However, the FMCG sector will see a rise in prices of commodities because crucial resources such as cooking oil, tea, cocoa, etc., become scarce. The persistent shock to the supply chain has forced various FMCG companies to increase their prices. For instance, Mondelez, a Fortune 500–listed snack and beverage company, announced a 6-7% price increase. 

    Inflation for Fashion & Pharma Industry
    Inflation for Fashion & Pharma Industry

    Fashion

    The global fashion industry posted a 20% decline in revenues in 2019–20. Inflation in fashion is caused by transportation bottlenecks, material shortages, rising shipping costs, and straining supply and demand. The global fashion industry will see complete recovery in 2022. COVID-caused supply and demand constraints have eased, but shoppers will have to reconcile to price jumps in everything from bags to shoes.

    Pharma

    Pharmaceuticals are recognized as an essential commodity and therefore have a massive impact on the household budget. Vizient has projected a 3.09% increase in the inflation rate in drug prices from July 1, 2022 – June 30, 2023. It shows how inflation has a direct impact on prescription drug costs. Notably, retail prices for some of the most widely used prescription drugs are expected to increase 2x as much as inflation. The demand for pharmaceutical drugs has been higher post-pandemic, ensuring that consumers’ total demand and spending in this vertical will remain unchanged. 

    Comparison of New, Used & Electric cars
    Comparison of New, Used & Electric cars
    Highest & Lowest Inflation in Beauty category. Source: nielseniq.com

    Automotive

    The rise of both new and used cars has been steeply increasing partly because of the shortage of semiconductors and the backlog from the closure of factories during COVID-19. According to the Bureau of Labor Statistics, there has been a 24.4% inflation in the used car purchase prices and an 8.8% increase in the new car purchase price. Rising oil prices across the globe and the historical oil crisis fuelled by the Ukraine-Russia war have strained many people’s budgets. However, the automobile market is seeing an uptake in demand for electrical vehicles (EVs). EVs represented 14% of car sales between January and June 2021. 

    Beauty

    COVID-19 brought new challenges to the cosmetics industry, chief among this being face-covering required by law. In light of social distancing and lockdowns across the globe, consumers were buying less makeup. The rising cost of labor, energy, and raw materials used in beauty products have resulted in a “once-in-two-decade” backdrop for price hikes. The cost of palm oil, a common material in beauty products, has soared 82% in two years due to Indonesian labor shortages. Nevertheless, consumers will spend more time outside the house. Beauty price per unit changes shot up 17% in-store and online in 2021.

    5 Things that will help retailers during inflationary times

    1. Observe Competition

    Retailers should follow their competitors closely—when they start to raise/lower prices, consider following suit. Using competitive data to gauge price changes will help in managing price parity. However, excessive discounts and lower prices to gain an advantage over your competitor could backfire in various ways. For example, low pricing may convey that your products aren’t as good as your competitors’, impacting your long-term brand image. Moreover, lowering prices to sell more doesn’t necessarily mean higher profits, especially during high inflation. To leverage this strategy effectively, retailers must first identify SKUs that have the highest impact on their pricing.

    2. Build a structured and targeted pricing strategy

    An effective pricing strategy that leverages differences in product, channels, and customers will help retailers to maintain long-term value for their business and customers. However, customers might react differently to a steep price increase. Broad price increases will demonstrate insensitivity and erode customer trust. Instead, retailers can thoughtfully tailor their inflationary price increases for each customer and product segment with a competitive pricing strategy. With a competitive and historical pricing strategy, brands can examine their customers’ end-to-end profitability and willingness to pay relative to a comparable peer set. 

    Price Competitiveness for the right items
    Price Competitiveness for the right items

    3. Rethink commercial positioning

    The pandemic and rise of inflation during 2020–2021 have profoundly impacted how consumers live and what they value. Understanding how your consumer’s needs have shifted and used a promotion strategy to manage today’s inflationary pressures is crucial. As new behaviors emerge post-pandemic, retailers must prepare for the potential top-line impact of demand shifts. Rethink commercial positioning and review marketing and packaging strategies, including the potential use of nonuniform and, in some cases, nonprice mechanisms.

    4. Ensure price competitiveness on the right items

    The Key-Value Item (KVIs) list should be reviewed again, considering changing shopper needs and habits during the pandemic, plus the supply and demand shock that the industry is currently experiencing. Price-sensitive and vulnerable shoppers are finding this inflationary period particularly tough, so brands might require an even deeper investment in KVI pricing. Reinvest base prices on essential products to drive volume for your best price-sensitive (PS) customers. Compete only where you need to be without overspending. Online channels should continue to reflect in-store prices and diverge during this time. Pricing Optimisation software enables best practices to simultaneously manage a high number of price increase requests.

    5. Revisit promotions to conserve costs and preserve stock availability

    Increasing the number of promoted products is a reflexive response to inflation, but it’s not the right response for building sustainable sales or longer-term loyalty. Inflationary times offer an excellent opportunity to reset promotional strategies to save money and margin. Retailers can increase sales and seize opportunities with a promotional pricing strategy. Increased promotional activity has a knock-on effect vs pricing position in high-low strategies and erodes overall value perception, creating a vicious circle of more promotions equals poorer value.

    Conclusion

    Today’s economic climate and associated pricing pressures are challenging for retailers and customers. Some companies have responded by announcing an increase in prices across product categories. Companies can manage pricing margins responsibly and profitably during inflation. Determining how and where new opportunities exist can help companies control inflation, drive growth, and remain profitable.

    Need help to arrive at the right pricing & discounting strategies to counter inflation? Sign up for a demo with our team to know how we can help!  

  • Share of Keyword Search Cinco de Mayo 2022

    Share of Keyword Search Cinco de Mayo 2022

    As inflation continues to hike costs for consumers and supply chains challenge them to maintain loyalty, there is still an active audience willing to pay the ultimate price for the convenience of food and alcohol delivery. That being said, we analyzed 8 popular Retail and Delivery Intermediary websites and 11 popular ‘Cinco de Mayo’ keywords to see which Brands are predicted to win the battle of Digital Shelf Share of Search this holiday.

    2022 Cinco de Mayo Share of Search Insights - Top Brands for 'Cinco de Mayo'
    2022 Cinco de Mayo Share of Search Insights – Top Brands for ‘Cinco de Mayo’

    Opportunities for Food & Bev on Cinco de Mayo

    While most of our analysis focused on popular Cinco de Mayo food and beverage products, none of these brands populated on either Target (pictured on left below) or Walmart (pictured on right below) page 1 search results for the term ‘Cinco de Mayo’. Keyword search results for this term are dominated primarily by décor brands as indicated below.

    Brands Achieving Top Share of Search for Food and Beverage Categories on Cinco de Mayo 2022
    Brands Achieving Top Share of Search for Food and Beverage Categories on Cinco de Mayo 2022

    Share of Keyword Search Results – Alcohol Category

    Three of the most popular alcohol types sought out during Cinco de Mayo are ‘Mexican Beer’, ‘Mezcal’, and ‘Tequila’. Below are the brands dominating Share of Keyword Search results on each of the major retail websites we researched.

    AmazonFresh, Meijer, Kroger, and Sam's Club Share of Search - Beer, Mezcal, and Tequila Keywords on Cinco de Mayo 2022
    AmazonFresh, Meijer, Kroger, and Sam’s Club Share of Search – Beer, Mezcal, and Tequila Keywords on Cinco de Mayo 2022

    We also reviewed the same keyword performance across popular delivery intermediaries to see how Share of Keyword Search altered for ‘Mexican Beer’, ‘Mezcal’, and ‘Tequila’. The results are below for TotalWine, Instacart, Drizly and GoPuff:

    TotalWine, Instacart, Drizly, and GoPuff of Search - Beer, Mezcal, and Tequila Keywords on Cinco de Mayo 2022
    TotalWine, Instacart, Drizly, and GoPuff of Search – Beer, Mezcal, and Tequila Keywords on Cinco de Mayo 2022

    The keyword ‘Agave’ is also a popular search term within the alcohol category during the time leading up to Cinco de Mayo. We reviewed keyword search performance at various zip codes to see how price points that populated on page 1 search results varied given the change in median income. Below are the results:

    Share of Search for Alcohol by Price Point and Zip Code on AmazonFresh
    Share of Search for Alcohol by Price Point and Zip Code on AmazonFresh

    Share of Keyword Search Results – Grocery Categories

    We also reviewed some of the most popular grocery items purchased during Cinco de Mayo by Keyword Share of Search results to see which brands are primed to win the Digital Shelf this year. Below are the results for Target.com and Walmart.com.

    Walmart and Target Share of Search - Food and Beverage Keywords on Cinco de Mayo 2022
    Walmart and Target Share of Search – Food and Beverage Keywords on Cinco de Mayo 2022

    Below are the results for the same popular grocery items and alcohol keywords related to Cinco de Mayo and the page 1 results seen for Brand Share of Search on Safeway.com.

    Safeway Share of Search - Food and Beverage Keywords on Cinco de Mayo 2022
    Safeway Share of Search – Food and Beverage Keywords on Cinco de Mayo 2022

    Access to these types of real-time digital marketplace insights can enable retailers and brands to make strategic decisions and help drive profitable growth in an intensifying competitive environment. Be sure to reach out to our Retail Analytics experts for access to more details regarding the above analysis, and let us know what other holiday insights you’d be interested in seeing this year. Happy Cinco de Mayo!

  • What is Customer Price Perception and why it is important

    What is Customer Price Perception and why it is important

    Finding the right price often requires a trade-off between margin and price perception. Brands may want to defeat competitors’ prices on all their products, but that can often lead to losses because sales directly link to price perception. Instead of trying to stay competitive across the board on all products, brands must identify key value categories (KVCs) and key-value items (KPIs) whose prices buyers tend to remember and price those products competitively. In this scenario, they can make up for lowered prices on key products by fixing higher prices on other products. 

    Consumers’ perception of price fairness largely determines their experience with a brand. Brands selling online can often have a disconnect between their prices and what customers expect their prices to be. However, that does not mean spiraling downwards by getting trapped in discounting cycles and heavy promotions that can harm your bottom line. Instead, brands require real-time monitoring across thousands of stock-keeping units (SKUs) to identify key categories and items they need to price with care. In this blog, you’ll learn about price perception and the factors that influence it. 

    What is Price Perception?

    Price perception is the perceived worth of a product or service in the consumer’s mind. It is one of the leading variables in the consumer’s buying process. Buyers are unaware of the true cost of production for the products they buy. Instead, they make buying decisions based on an internal feeling about how much certain products are worth and which brand offers them the best value. To offer competitive prices and yet obtain a higher price for products, brands often pursue marketing strategies to improve the price perception of their brand and products.

    Price Perception
    Price Perception

    However, brands should not fall into the trap of assuming that price perception is a competitor’s price index. It’s not about offering the lowest price on certain SKUs. Not every brand strives to offer the lowest prices. Some brands take a slightly different approach to ensure the right value for their products. For example, take a look at Trader Joe’s, a grocery chain that has never claimed low costs. They’ve always taken a holistic approach to their pricing and customers to build a loyal following. And it worked well for them. Trader Joe’s can boast one of a high-value perception score, despite not having rock-bottom prices. 

    Marketplaces such as Walmart and Amazon may not have the best prices on every item. Still, customer perception is that they will have the lowest prices and will often shift the share of sales towards such platforms over businesses that offer the same or even lower prices. 

    Some things to consider:

    • What do your customers think of your brand?
    • What are the key factors that are driving your customers’ price perceptions?
    • Is your product mix properly aligned with your brand perception?
    • Are you communicating the most important and relevant information to your customers?
    • Is your message being received and understood?
    • Who do your customers see as your competitors, and why?

    Also Read: 11 Reasons why your eCommerce Business is fail 

    What is Price Positioning?

    Price positioning is pricing products or services within a certain price range. It indicates where certain services or products lie in relation to competitors’ pricing and in the mind of different customers. A brand’s price positioning has a huge impact on whether the products are seen as priced low or not. The following is a great way to understand the price-value matrix:

    Price Positioning
    Price Positioning

    Your brand’s position in this matrix will depend on your pricing objectives, competition, and customer loyalty. Price positioning helps the marketing and operating teams understand customers’ perceptions of your brand and convince customers to buy your products. Brands need a holistic approach toward setting prices for their products in order to drive conversions through intelligent pricing and competitive insights. 

    Factors that influence Price Perception

    Price-Quality Relationship

    Price is often an indicator of product quality. The general rule is that the higher-priced products are perceived to have better quality, implying that brands should consider a rational quality-price relationship in their pricing or promo strategy. For example, it might not be best practice to have similar prices for both good and low-quality products because customers will perceive low-quality products as overpriced and might not purchase from you.

    Price-Consciousness

    Customers aren’t price conscious about every product. Instead, they are only price conscious about certain products under the best price guarantee or BGP. For instance, if buyers find your BGP products more expensive than your competitors, the cheaper products in your assortment will still be perceived as expensive. 

    Value-Consciousness

    During markdown periods, ensure that you are not undermining the efforts to shape and maintain price perception by offering extreme or complex discounts. In an attempt to clear stocks, promotions simply confuse the shopping experience for customers and further deteriorate trust in your brand. Your promotional offers should keep price perception during the holiday season or clearance sales by offering a simplified promotional program. Start by understanding which price mechanics and SKUs work best for your target customer segment. You should also reduce over-communication on hero deals else buyers will assume that you incorrectly price products during new seasonal launches. 

    Prestige Sensitivity

    Gerald Zaltman, a Harvard professor, argues that 95% of all purchasing decisions are subconscious. Luxury brands are a great example of how psychology directly links to price perception. Customers buy premium or luxury products to demonstrate their social status. In this scenario, buyers don’t hesitate to buy expensive products from certain brands even if they are explicitly overpriced. Thus, brands selling premium products will have to ensure pricing is coherent with buyers’ expectations. 

    Every customer wants to know they’re getting the best value. They use the highest and lowest prices in a range to understand how expensive a product or brand is. So, by removing high price point lines with low volume, customers will see more minor price points around the store. Brands must merchandise entry price points to help customers identify the lowest prices and improve the perception of their product ranges. 

    Product Range
    Product Range

    How to adjust Price Perception

    Here are three ways for brands to improve price parity:

    • Marketing to influence Price Perception

    An efficient pricing management strategy will focus on competitiveness and establishing the right price perception among your customers. You can influence customers’ price perception by improving the look and feel of your online stores since simpler designs are often reflections of lower prices. Another great way to influence price perception is to offer loyalty and reward programs that also improve brand loyalty and reinforces the vision of an economy store irrespective of the prices of your products.

    • Competitive Analysis

    Brands can understand price differences after a competitive analysis. Customers often search for similar products across brands to find the best deals, and you will be able to understand customer opinion through competitor analysis.

    • Price Management Automation

    A price monitoring platform can help brands to stay on top of promotions and discounts offered by their competitors. A price intelligence software will help brands associate products by similarity criteria and compare the pricing of their products with those of competitors. It offers a detailed view of the market and ensures that brands take care of their bottom line.

    Conclusion

    When a consumer comes across a similar low-priced product or service from a different brand, they may see it as a good deal or might perceive it not worthy of their time or money. What consumers think about your brand’s price is just as important as the actual price of that product. A buyer may sense a company as “upscale” and assume that they have high prices, or they may see a brand as a discount retailer whose prices are too high for its reputation. At times, consumers might also see cheaper alternatives as inferior. It’s not easy for a brand to understand its customers’ perception of price vs. value it offers. Brands need a long-term, dynamic pricing strategy that matches the demands and trends of a global, competitive market. And in order to drive sustainable growth, they need to make smarter pricing and promotion decisions with insights into competitive pricing. 

    Learn how DataWeave can help make sense of your and your competitor’s pricing & promotional strategies and help your brand build the right Price Perception. Sign up for a demo with our team to know more.

  • Top 7 strategies to sell effectively on Amazon

    Top 7 strategies to sell effectively on Amazon

    According to MarketingCharts, 63% of online shoppers start their buying journey on Amazon. This shows that customers believe they will find the products they are looking for with competitive prices and excellent customer service on Amazon. Amazon is one of the most dominant eCommerce marketplaces with 197 million users and 112 million Amazon Prime members. Brands can sell on Amazon to capitalize on this vast customer base by showcasing and promoting their products properly. 

    In this article, we’re going to take a look at the top 7 strategies to sell effectively on Amazon:

    1. Boost Product Discoverability using Ads

    Amazon Advertising helps sellers, brands, and agencies to drive profitability by making sure product discoverability is high & shoppers are able to find their brand with ease. The ads on Amazon fuel product discovery and improve conversion rate. The advertising options on Amazon are designed to help brands increase exposure, generate incremental sales, boost organic rankings, and drive growth.

    Amazon has three PPC programs: sponsored product ads, sponsored brands ads, and sponsored display ads. Brands can increase visibility on Amazon with these three paid campaigns. You can sponsor products or your brand for related searches on Amazon. Businesses only pay for clicks received. 

    Sponsored products are for individual product listings that appear on shopping results pages and product detail pages. Sponsored brands are for showcasing brand portfolios such as logo, custom headline, and a selection of products on the shopping results page. The last is sponsored display, a self-service advertising solution for displaying ads on and off Amazon. 

    Promotions for Brand and SKU's
    Promotions for Brand and SKU’s

    2. Improve your Amazon SEO using effective Product Descriptions

    To effectively sell on Amazon, businesses first have to understand the A9 algorithm. Amazon uses A9 Algorithm to decide which products are ranked in search results, emphasizing sales conversions. This algorithm helps Amazon promote listings that are more likely to result in sales. 

    Keywords in product descriptions are one of the main driving factors that the Amazon A9 algorithm looks for in determining relevance to search queries and setting rankings on its results pages. Therefore, brands must integrate high volume and significantly relevant keywords as part of their listings. Crafting product descriptions with the right keywords will provide compelling reasons for buyers to purchase the product and for the A9 algorithm to better rank the brands. Brands can analyze and optimize their content to improve discoverability across Amazon. Accurate product descriptions help users make informed decisions and allow brands to deliver a consistent customer experience.

    Detailed Descriptions and Highlights
    Detailed Descriptions and Highlights

    3. Improve your Product Visuals

    Avoid using standard visuals when displaying your products in Amazon’s image gallery. Product images are the hook that encourages visitors to click on your products. However, Amazon has specific image requirements that you’ll need to adhere to while presenting products. When shopping on Amazon, potential buyers are looking for high-definition and clearly visible photos. Thus, you will need diversity in images if you want your product and photos to stand out.

    In addition to images, brands can make their product descriptions better through video content. Videos help your brand to stand out, build a more personal relationship with customers, and lead to increased sales. One study on eCommerce sellers found that using product videos increases sales for online stores by 144%.

    Product Images
    Product Images

    4. Switch to Intelligent Pricing & Win the Buy Box

    Intelligent and competitive pricing is the most essential lever for revenue growth. With advanced technology like AI and analytics, brands can get insights into competitive pricing and develop an intelligent pricing strategy to calculate real-time changes in pricing optimally. 

    Amazon wants to give the consumer the best value for their money and thus has a Buy Box option. The white box on the right side of the Amazon product detail page is called the Buy Box, and customers can directly add items for purchase to their cart. However, not all sellers are eligible to win the Buy Box. 

    Thanks to Amazon’s customer-obsessed approach and high competition, only businesses with excellent seller metrics have a chance to win a share of Buy Box. Amazon weighs low prices with high seller metrics. If your brand has near-perfect performance metrics, having higher prices can still get you a share of the Buy Box. In contrast, brands with mid-range metrics will probably need to focus on offering the most competitive price.

    But, why is the Buy Box important? According to BigCommerce, 82% of sales on Amazon go through the Buy Box, and the rate is even higher for mobile purchases. Getting insights into your competitor’s pricing with our Digital Shelf Solution will help you improve seller metrics and find the right pricing strategy for your products.

    5. Provide Plenty of Social Proof

    Testimonials can increase sales page conversions by 34%. Social proof has emerged to be of great importance in the eCommerce world, and it isn’t limited to recommendations from people customers know in the “real world.” A survey conducted by BrightLocal revealed that 31% of consumers reported that they read more online reviews in 2020 than ever due to Covid-19. 

    Product ratings and reviews on Amazon are at the center of the recommended products section, product listing page, and search results. Interestingly, customer feedback also has a huge impact on a brand’s ODR or Order Defect Rate. It is one of the most critical measurements tracked by Amazon. ODR is a measure of customers who have had a negative experience with you as a seller. Amazon uses it to assess a brand’s health as a seller. The ODR indicator is driven by customer feedback, so review management is the primary step for brands to avoid an Amazon ODR warning and improve their order defect. 

    6. Go Global

    The Amazon marketplace is available in countries and markets worldwide, allowing brands to explore new territories and sell their products globally. Each foreign territory has a unique Amazon site that resonates with its culture and audience, making it easy for global sellers to compete with other brands. If your eCommerce brand has the operation capacity to expand globally, Amazon offers state-of-the-art international logistic capabilities. 

    Brands can expand in European countries like France, Italy, Netherlands, Germany, Spain, etc., and Asia Pacific locations like India, Japan, and Australia. Amazon is also available in emerging eCommerce locations like the Middle East, Brazil, Turkey, and Singapore. 

    7. Build a Branded Store

    One of the best strategies to stand out on Amazon is to feature your products on a branded Store. Amazon has free tools that allow grants to build an online store where brands and sellers can showcase products and connect with customers. These stores look different from the typical Amazon listing layout and also have the option to create detailed pages with A+ content. 

    Build your Brand Page
    Build your Brand Page

    For instance, Netgear, a company that offers technology-related products has an excellent branded store on Amazon. The brand has embedded images and videos that address buyers’ needs and how users’ lives are affected by using their products. The most attractive feature about this store is that they have integrated the value offered by their products into new use cases because of the current pandemic. For example, they’ve used phrases like “Make Online Learning fast and fun” and “Work from office at office speed.” Additionally, the categories and search tab help buyers search for specific products easily.

    Creating branded stores allows you to build a beautiful brand experience for customers and offers a multi-page, immersive shopping experience. Brands can pick unique designs, integrate promotions, and use rich media to create a custom curation of handpicked products. 

    Conclusion

    Amazon has 9.7 million sellers worldwide, of which 1.9 million are actively selling on the marketplace. The competition on Amazon is fierce, and it’s continuously increasing. Despite a large number of active sellers on Amazon, only a tiny fraction generates a significant portion of its total sales. Fewer than one in ten active Amazon sellers generated over $100,000 in annual sales, and only one percent of them hit the $1 million sales mark. Use these strategies to develop a comprehensive understanding of the Amazon platform and how to sell effectively on the platform while maximizing your presence amid rising competition. 

  • 11 Reasons why your eCommerce Business is failing

    11 Reasons why your eCommerce Business is failing

    No matter where your eCommerce business sells, there are some fundamentals that brands have to get right to achieve sales targets. Brands need to find the right product/market fit, nail their lead acquisition strategy, and design a qualified sales funnel to turn prospects into leads and eventually returning customers. They will also have to analyze their customer’s buying journey and get insights into competitors’ strategies to understand what works for their business.

    If your eCommerce business is struggling, read this blog to learn about steps you can take to increase sales and keep your business afloat. 

    1. Lack of social proof

    Customers often check for reviews or testimonials before making a purchase. Our decisions are consciously or unconsciously influenced by the opinions, choices, and actions of people around us. Social proof helps brands build customer trust, adds credibility to their business, improves brand presence, and validates customers’ buying decisions. 92% of consumers are more likely to trust user-generated content (UGC) and non-paid recommendations than any other type of advertising. Additionally, brands should also find ways to combat negative reviews since bad reviews can sometimes be extremely damaging. 

    Understanding these reviews or the impact of your brand’s social proof is critical. At DataWeave, we help brands analyze online reviews to understand customer sentiment and adapt to feedback to enhance their experience with your brand. 

    2. Slow site speed

    Site speed of the home page and checkout page on your D2C website can be a roadblock. Slow sections on your site like My Accounts, checkout, and cart are often overlooked when it comes to tracking site speed. Brands should run their checkout process at least once a month to ensure it’s fast, smooth, and bug-free. You can optimize images, strip unused scripts, implement HTTP/2, etc., to improve site speed and performance. 

    3. Poor customer service

    69% of US consumers say customer service is very important when it comes to their loyalty to a brand. Guaranteeing a return customer is important to maintaining customer loyalty. While the focus is on the first purchase for new customers, your brand’s customer service will determine if first-time customers become repeat buyers. Loyal customers are known to spend 67% more on a brand product than new customers, even if they make up only 20% of your audience. 

    Types of customer service
    Types of customer service

    4. Failure to send traffic to popular products

    Be it your own D2C website, or when selling on a marketplace, you should be able to drive traffic to your best-selling products. One of the best ways for sending traffic to popular products on your website is to run paid ad campaigns and reach new audiences with influencer marketing on social media. Brands can also attract customers with organic media such as writing blogs and producing podcasts. 

    If you’re looking at driving traffic to key products on Amazon & other such marketplaces, sponsored ads are the way to go! Sponsored ads help your best-selling products more discoverable & helps shoppers find your brand with ease. 

    5. Inadequate pricing

    Finding the right pricing strategy for your eCommerce business is crucial for optimizing sales and increasing revenue. The first step is to perform a competitor and historical data analysis to get a general idea of the market and then develop a pricing strategy that is the right fit for your products. Brands also have to ensure that they have dynamic pricing that can adjust according to supply and demand. 

    Our Digital Shelf solution at DataWeave helps brands track pricing for products across different pack sizes & variants across multiple online retailers and marketplaces helping them stay competitive in the market. 

    Optimize the right pricing strategy
    Optimize the right pricing strategy

    6. Not targeting the right audience

    One of the biggest mistakes that eCommerce businesses can make is targeting the wrong audience. It’s crucial for brands to define that target audience and then tailor products and marketing toward them. To increase sales as an eCommerce business, brands have to understand their audience, their interests, and how to appeal to their interest. Start by creating ideal buyer personas that represent your ideal customers. Also, segmenting audiences and targeting various groups based on buyer personas for ad campaigns will lead to better sales and revenue. 

    Targeting the right audience
    Targeting the right audience

    7. Poor product descriptions

    One of the major and common mistakes by eCommerce brands is using irrelevant product descriptions that are not optimized for the product. Customers don’t add products to their cart if they have difficulty finding sufficient information relevant to the product. Brands should write attention-grabbing descriptions optimized for SEO that are informative for the users. Here are some tips to optimize content to drive more eCommerce sales.

    At DataWeave, our AI-Powered solution helps brands optimize content and visuals across product pages to improve discoverability. 

    8. Not having multiple revenue streams

    Due to COVID-19, many businesses have had to modify or temporarily shut down their daily operations. However, finding new revenue streams can be a great way for eCommerce businesses to make up for the lost income and keep the company afloat. The best solution is to diversify your product offerings by offering commonly purchased products in bundles. 

    9. Low-quality visuals

    Businesses fail to hit their sales targets because of low-quality visuals in product descriptions. High-quality and custom images can improve conversion rates from both marketplaces and image-based channels like social media. Social media users are attracted to exciting, high-quality content that conveys a desirable lifestyle. Brands should use high-resolution, attractive pictures of their products. Brands can also utilize UGC and influencers to help build up their content libraries.

    Low-quality visuals
    Low-quality visuals

    10. Wrong Assortment. Poor Availability

    When your target audience lands on your eCommerce store and cannot find what they’re looking for, it leads to a poor shopping experience, but more importantly a lost sale for your brand! While you cannot have endless inventory, it’s essential to optimize your assortment & product availability to decrease the chances of your customer walking away. Assortment & availability optimization begins with analyzing current and historical inventory trends. If done manually, assortment can be a time-consuming task. A healthy assortment can increase retail sales by creating a positive shopping experience for your customers and encouraging them to return to your store again.

    11. Bad eCommerce UX

    Offering a sub-standard user experience is a common reason why eCommerce businesses find it difficult to increase sales. According to a study, the conversions can fall by up to 7% for every one-second delay in page load time. Businesses can use a countdown clock on their landing page and exit pop-ups to improve conversations. Your landing page and product descriptions should provide information that helps your users make a better and more informed decision. 

    Conclusion

    If your eCommerce’s business sales are tanking, improving site speed, customer service, social proof, and product descriptions are some of the levers you can pull to remedy the situation. Brands should also work on improving online reviews & ratings, availability, assortment, visuals, and website UX to improve customer experience. These steps not only increase loyalty but also improve customer retention. 

    Need help tracking online pricing for your eCommerce business? Or decoding customer sentiment from reviews they’ve left for your products? Or do you need insights into your product assortment and availability? Sign up for a demo with our team to know how DataWeave can help!  

  • eCommerce Performance Analytics for CPG Private Label

    eCommerce Performance Analytics for CPG Private Label

    The combination of economic uncertainty, inflation, and perceived affordability has increased consumer’s willingness to buy and try more private label products, challenging National brands to differentiate their eCommerce strategies, especially those related to price positioning, in other ways.

    Our previously released report, Inflation Accelerates Private Label Share and Penetration, confirmed 8 out of 10 brands with the highest SKU count carried across all grocery retailer websites to be private label, signaling the strength of their digital Share of Voice. Given the growing shift in consumer preference toward private label brands, we are providing access to the latest trends seen from September 2021 through March 2022. Below you will find a summary of what the data revealed about the growing presence of private label brands on the Digital Shelf.

    Private Label Account and Category Penetration

    We analyzed private label penetration at an account level to understand which private label brands have the greatest presence on retailer digital shelves, and to see which retailers may be leaving product assortment opportunities on the table.

    Private Label Penetration Across Retail Grocer Websites

    As a retailer, it is important to understand how your private label penetration stacks up against the industry average at a category level, especially given the performance tracked for retailers included within our analysis and the vast number of SKUs they offer online (over 20,000).

    Private Label Penetration by Category Across Retail Grocer Websites

    The Private Label and National Brand Price Gap Widens

    Private label brands tried out of necessity mid-pandemic increased in popularity as grocery prices continued to rise, providing an opportunity for retailers to increase brand affinity and loyalty for their online shoppers. Retailers alike were able to keep affordability at the forefront of their strategies and maintain a price gap of 23% or more, despite inflationary pressures to increase prices.

    Private Label / National Brand Price Gap by Retailer

    Looking at the results at a category level, we can see that Meat is the only category found within our analysis where private label brands are priced higher than National brands at an average of 8% greater. The Alcohol & Beverages category tends to always see the greatest price gap between private label and National brands given the price variances by unit (ranging from under $10 to over $100), in this case averaging a 148% price gap.

    Private Label & National Brand Price Gap by Category

    Private Label Total Basket Value Comparison Across Retailers

    While SKU-level pricing is extremely important to product strategy, for a retailer, it is equally as important to be as mindful of the total basket value even more so now as consumers further their private label loyalty across various categories. A few SKU-level missteps in pricing decisions can exacerbate cart abandonment and negatively impact shopper loyalty in a world where prices can be compared instantly in the palm of your hand.

    Based on our analysis, Walmart and H-E-B private label products offered the lowest priced total basket of goods at $42.90 and $45.06 respectively, whereas AmazonFresh and Safeway offered the highest total at $73.19 and $69.52 respectively.

    Private Label Item Level Price Comparison by Retailer

    Inflation-driven Price Changes are on the Rise with Room to Grow

    Based on the 20,000+ SKUs analyzed, we saw a continual price increase every month since September 2021 when comparing future monthly prices to those we tracked in September. The greatest price increase happened in March 2022 at 12.5% on average, however, there are still 48% of SKUs that have yet to see a price increase even as inflationary pressures rise.

    When viewing the split between National and private label brand price increases in March 2022 versus September 2021, we saw National brands increased prices on average by 13% where private label brand prices only increased an average of 7%.

    Private Label & National Brand Price Change
    Private Label & National Brand Price Change (%)

    Price decreases are still occurring across all categories, despite inflation, but to varying degrees ranging from 5% for Deli items to 17% for Dairy & Eggs. Within the Dairy & Eggs and Pantry categories, private label brands reduced prices for an additional 10% of total SKUs compared to National brands.

    The greatest category of opportunity for price increases within private label were found within Beauty & Personal Care with 67% of private label products yet to see a price change since September 2021.

    Price Change (%) by Category and Brand Type

    Private Label Price Change Correlation to Product Availability

    The category with the greatest magnitude of price increase seen within private label brands occurred within Baby at 16.3% followed by Home at 14.3% on average. Private label products within Home and Baby categories were also showing the lowest availability rates, 75.9% and 79.5% respectively, indicating a high demand for these items even as prices increased.

    The private label categories with the smallest price increase on average were Dairy & Eggs at 2.4% and Other Foods and Pantry at 3.4% and 3.6%, respectively.

    Private Label Price Change Magnitude & Availability
    Private Label Price Change Magnitude & Availability

    While in many accounts both private label and National brands struggled with stock availability in March 2022, National brand availability is much lower (around 10% on average) than private label availability.

    H-E-B had the lowest overall product availability at 76% across both private label and National brands on average. Only Walmart had lower availability for Private Label at 75% compared to 93% for National brands, but they also had the greatest price gap between private label and National brands.

    Private Label & National Brand Product Stock Availability

    The Future of eCommerce Growth for Private Label

    Our greatest learning from this analysis is that it’s time for retailers to start thinking and planning more like the National brands they carry when it comes to positioning their private label brands for success. Successful retailers are taking this time to reset their private-label strategies and transfer short-term switching behavior into long-term customer loyalty.

    Retailers playing catch up have the opportunity to address some of the gaps highlighted throughout this analysis, for example, relative to pricing and assortment changes. Below are some of the highlighted opportunities:

    • Though inflation is driving price hikes, more than 50% of products analyzed have yet to see a price increase indicating an opportunity to protect margin
    • Narrowing the price gap between a store’s brand and National brands should not be the only focus as competitive private label brands are becoming a greater threat at a category and basket level
    • Modifying and expanding assortments as demand increases for private label can improve customer retention and loyalty, especially for cross-shopping consumers

    According to The Food Industry Association (FMI), only 20% of food retailers currently promote private brands on their homepages, and only 48% include detailed product descriptions indicating even more opportunities left on the table for retailers to optimize private label digital performance.

    Many leading retailers are leveraging real-time digital marketplace insights and eCommerce analytics solutions like ours to further their online brand presence and optimize sales performance. This report highlights only a small sample of the types of near real-time insights we provide our clients to effectively build competing strategies, make smarter pricing and merchandising decisions, and accomplish eCommerce growth goals. Be sure to reach out to our Retail Analytics experts for access to more details regarding the above analysis.

    For access to a previously recorded webinar presented in partnership with the Private Label Manufacturers Association and conducted by DataWeave’s President and COO, Krish Thyagarajan, click here.

  • The Rise of On-Demand Grocery Delivery after the Pandemic

    The Rise of On-Demand Grocery Delivery after the Pandemic

    Before the pandemic, the grocery industry was set around brick-and-mortar stores, and there was a slow movement towards on-demand grocery. Online grocery delivery was still considered a peripheral channel. However, grocery shoppers started turning to on-demand platforms since the onset of COVID-19. According to Acosta’s report, since the pandemic, 45% of customers prefer online grocery shopping over physical stores. 

    COVID-19 drastically accelerated the online grocery delivery trend, increasing 10% and 15% of total grocery sales during the peak COVID-19 time. In the U.S., online grocery shopping reached nearly $90 billion in sales in 2020, increasing by more than $30 billion. 

    In this article, you’ll learn about the early pioneers of online grocery delivery in the U.S., the modern players, and the impact of COVID-19 on grocery trends.

    Early pioneers of online grocery delivery

    Early pioneers of online grocery delivery
    Early pioneers of online grocery delivery

    In the late 1990s, consumers had just started ordering products online. Online grocery shopping was an early area of focus. It offered lucrative rewards to high-spending consumers, increased convenience, and saved them time. Peapod, founded in 1989 by brothers Andrew and Thomas Parkinson, was the first online grocery delivery service. Back when they started, users had to install software from CD-ROMs and then place orders. Though it took years to become a well-known name in the industry, Peapod is still in business.

    Webvan and HomeGrocer.com were two other early pioneers of online grocery delivery that started in 1996 in California and 1997 in Washington respectively. Webvan had a successful launch in California, and they had aggressive expansion plans to operate in 26 major cities around the United States. However, the company filed for bankruptcy less than two years later. HomeGrocer.com quickly created the infrastructure needed to support the business, including a fleet of vans and a huge warehouse. They had impressive early growth, and sales reached over $1 million a day by mid-2000. They expanded into other markets, including California, Georgia, Oregon, Texas, and Illinois.

    Modern players of the on-demand grocery delivery

    Modern players of the on-demand grocery delivery
    Modern players of the on-demand grocery delivery

    Online Grocery Trends Post-Pandemic

    When COVID-19 first began to engulf the world, supermarkets and grocery delivery platforms like Amazon Fresh and Instamart became overwhelmed with huge demands. To handle the surge of online orders, stores had to make drastic changes to accommodate the switch to on-demand delivery requests. Popular grocery delivery brands had to introduce waitlists and online queues for new customers. According to a poll, 53% of shoppers would continue online grocery shopping because they had a good experience, indicating that the on-demand grocery trend will continue post-pandemic. 

    mckinsey grocery report
    Mckinsey Grocery Report

    As shoppers prefer more digital channels in their path to purchase, the on-demand grocery trend is becoming much more significant for both consumers and brands. According to a McKinsey and company survey, frozen fruits, health care items, fresh fruits and vegetables, packaged foods, household care items, beverages, and deli meats categories are likely to remain popular among U.S. consumers post-pandemic. Meanwhile, CoreSight Research found that fresh fruits and vegetables were the biggest bestsellers from 2020-to 2021 followed by fresh dairy, meat, eggs, frozen food, and bread and baked goods. 

    Why Grocery Shoppers are going digital

    Online ordering offers a more personalized experience to shoppers as they get recommendations for products that are often bought together. When paired with data analysis and AI-powered algorithms, grocery stores could work on targeted marketing and offer quick delivery services. 

    1. Flexibility

    On-demand grocery shopping offers customers a wide range of delivery options, including subscription services, buy online pick up in-store, click and collect, option-based pricing, and much more. This offers choice and accessibility to modern customers looking for speed and convenience.

    2. Convenience

    With the increasing focus on social distancing and safety, shoppers started to rely on delivery services rather than waiting in long queues and risking exposure. The focus and priority of grocery shoppers shifted from discounts and pricing to convenience, speed, and safety. Online grocery shopping order methods also differ by generation. 40% of millennials prefer to shop groceries on mobile, and 52% prefer computers. Similarly, 66% of Gen X prefer to shop on computers, and only 27% prefer to shop on smartphones. 

    Grocery Shoppers are going digital
    Grocery Shoppers are going digital

    3. Speed

    The fierce competition in the on-demand grocery delivery space has led to small delivery times. Startups like GoPuff (30 minutes), and Jiffy (15 minutes) are competing with the big boys like Walmart and Amazon Fresh to deliver groceries in under an hour. Quick delivery options like two-hour delivery and same-day delivery have made it easier for customers to shop for fresh produce. Customers can quickly order a few items for a specific recipe and get it delivered within a few hours. 

    4. Multiple payment methods

    At store checkouts, cash and card are the only two acceptable options. Customers prefer to have more options in today’s modern world. Online grocery shopping makes buying easier by offering multiple payment options like PayPal, credit/debit cards, and monthly payment plans that negate the delivery fees for each delivery.

    How to successfully run a Grocery Delivery Business?

    The increasing demand for speed and convenience puts pressure on the grocery industry that faces inventory issues like fresh produce and product availability. However, the benefit of online grocery delivery services is that it provides insight into the end-to-end view of the customer journey. Grocery delivery brands can use the data to design services and models that meet customer demand and minimize costs across the supply and distribution chain. 

    If you’re a Grocery Delivery company and want to track your delivery time, or product catalogue so you can boost sales with an in-demand product assortment, or you want to drive more revenue & margin by making sure your products are priced right v/s your competition, reach out to us at DataWeave! Sign up for a demo with our team to know how we can help you optimize your online sales.

  • 9 Things to Build a Thriving Fashion eCommerce Brand

    9 Things to Build a Thriving Fashion eCommerce Brand

    According to the Statista Fashion eCommerce report 2021, the compound annual growth rate (CAGR) for online fashion is predicted to be 10.3% between 2018-2023. The widespread need for trendy fashion presents a challenge for fashion brands to succeed in a highly crowded and competitive space. With eCommerce shopping becoming more prevalent, fashion brands aren’t just competing for brick-and-mortar sales. Instead, they’re also competing for those late-night or impulse purchases from online customers.

    Looking to 2022 and beyond, this blog will highlight 9 things to build a thriving fashion eCommerce brand:

    1. Allow shopping on multiple channels

    Breakdown of Shopping journeys in Apparel
    Breakdown of Shopping journeys in Apparel

    Typically buyers from diverse age groups prefer different sales channels. Some prefer large retailers, and some choose web stores. If you know where your customers like to purchase your products, you can leverage the power of search engines and marketplaces to improve your sales. Multi-channel retailing helps fashion eCommerce brands to sell and promote products on a platform and device of the audience’s choice. 

    A brand should offer support and access to its products across all platforms, channels, and devices. It helps fashion brands to reach customers where they prefer to shop. If your customers prefer to shop on a computer or an app, your brand can offer a seamless customer experience. 

    2. Don’t sell on the Homepage

    Your online fashion store homepage is more about increasing credibility and trust among potential buyers. Your ideal home page shouldn’t display products or their prices. Instead, it would be best to integrate promotional and marketing strategies on the landing page to encourage visitors to explore your product categories and the rest of the website. You should have an intuitive interface that makes navigating the pages easier. You can also use the homepage to promote seasonal offers and new launches. Fashion brands can also display customer reviews, awards, brand achievements, and web security trust seals to increase the conversion rate.

    Don't sell on homepage
    Don’t sell on the homepage

    3. Product Descriptions with Unique Stories

    Product descriptions often get overlooked or underutilized even though they are important for eCommerce businesses. Your products won’t sell with spammy and same product descriptions. The modern product description is all about communicating a product’s worth and value with a story that captivates your buyer’s attention. Identify areas where your content & images don’t align with your product or represent it in the best light. Make sure to deliver an enhanced consistent brand experience across all online channels to improve your conversions.

    4. Focus on Review and Ratings

    Rating & Review of a fashion brand
    Rating & Review of a fashion brand

    Customer reviews have a huge influence on a buyer’s purchase decision, especially in the fashion industry. Encourage your consumers to leave reviews on your brand website. Reviews help fashion brands to build trust for their products and convert customers. Legitimate customer reviews help your shoppers to get crucial insights into what previous buyers liked or disliked about a particular product. 

    However, you should stay away from paid-for or false reviews usually encouraged by unscrupulous sellers as they are easy to spot and hurt your rankings. You must remember that receiving reviews also includes dealing with negative comments. They should be used to improve your upcoming product offerings. 

    5. Sell Looks

    Product can be combined with in the detail page
    The product can be combined with in the detail page

    Successful fashion brands don’t simply sell individual products. Instead, they sell complete looks that inspire shoppers to purchase the entire stylish look. As an online fashion brand, you’re not selling clothes; you’re selling an elegant collection of wearable art. When visitors reach your online store, you should appeal to their fantasies and sentiments through aesthetic look books that are both pleasing and congruent with your brand. Most successful online fashion shops are inspirational and visual. Look books help brands pair their previous season items or dead stock with new stock and increase sales. Brands can also share these look books on social media or in their monthly newsletters to increase reach. 

    6. Provide Promotions and Offers

    Fashion brands can take advantage of plenty of sales throughout the year, from New Year celebrations to Black Friday, Cyber Monday, and Christmas. Brands can leverage these high sales periods to sell looks and gift items to boost sales. Just make sure you’re measuring the effectiveness of your online promotions. Holiday and festive sales also offer an excellent opportunity to plan strategic discounts to get rid of old stock. Since trends in the fashion industry have been changing rapidly, you can use discounts to get rid of dead-stock or out-of-trend items each season. 

    7. Be active on social media

    Social media is a way to promote your brand, increase trust among your audience, and entertain your audience with exciting content. You can also engage the audience by providing gift coupons or giveaways. Brands can promote products while keeping their audience engaged with engaging content and promotional offers. 

    Social media is a great way to get influencer support, either organically or through a paid partnership. Brands have to focus on every element of social media marketing strategy, right from choosing a platform, creating Instagram/Facebook shops, jumping on trends/events, and tracking customer sentiment. 

    8. High-quality product photography

    Capture every detail of your product
    Capture every detail of your product

    Nothing is worse than ordering a piece of clothing online and not getting what you saw on the website. Not being able to accurately convey fashion products will hurt your bottom line. Fashion brands must use top-notch product photography that includes high-quality visuals, such as multiple angle views, 360-degree images of each product, accurate depictions of all color options, and the option to zoom in on product attributes.  

    High-quality product photography
    High-quality product photography

    A recent game-changer in the fashion industry has been including different sets of models to accurately feature clothes of various shapes, heights, and weights. Instead of displaying a dress in only one size, fashion brands can have multiple models wearing various sizes for the same article of clothing.  

    9. Stay up to date with new trends

    Fashion eCommerce brands have to be particularly careful of continuously updating their product offering with the latest fashion trends for each season. They can boost sales with an in-demand product assortment. Continuously updated fashion inventory signifies that the brand is up-to-date with the latest fashion trends in the market and has unique products to offer. You can always get creative with new styling, better looks, and personalized product recommendations. 

    Conclusion

    Fashion eCommerce is rapidly growing and transforming at a staggering rate as technologies continue to advance. Traditional fashion brands can now expand their reach from brick-and-mortar shops to digital and eCommerce platforms to reach shoppers across the globe. The new digital selling opportunities also come with considerable challenges – from staying up to date with ever-evolving trends to managing dead stock. 
    Are you a fashion brand that needs help monitoring your product content? Or measuring the effectiveness of your online promotions? Or decoding customer sentiment from reviews they’ve left for your products? Sign up for a demo with our team to know how DataWeave can help!

  • Fake Reviews: A Real Pain Point for Brands

    Fake Reviews: A Real Pain Point for Brands

    Online reviews have revolutionized how customers purchase products and services. In fact, eCommerce success for certain products hinges on the ratings and reviews. With this, have come the pitfalls of corruption in eCommerce.

    New brands trying to establish a presence and capture critical mass have been known to resort to soliciting fake and paid reviews to uplift their brand in search rankings. Similarly, these brands can also encourage fake negative reviews on competitor’s listings to bring down their value. Bots and paid manual reviews are usually employed to rake up the review count. Review sites like TrustPilot, Google Reviews, and marketplaces like Amazon are littered with fraudulent reviews. In fact, Guardian calculated that 3.6% of all reviews on TripAdvisor were fraudulent. According to a 2021 report by Statista, 46% of the 2.7 million online fake reviews that were removed were five-star reviews! 

    Fake online reviews are misleading since customers shopping both online and offline rely on reviews to make purchase decisions. Fake reviews also pose further problems because they deceive consumers into spending money on a product or with a company they may not have otherwise chosen. 

    Federal Trade Commission (FTC) made a recent announcement to send penalties to over 700 brands and retailers for fake endorsements and reviews. While this notice references influencer content and testimonials, it also applies to customer reviews. 

    In this blog, we will discuss the importance of reviews for brands and retailers, spotting fake reviews on Amazon, and steps that eCommerce companies can take to tackle fake reviews. 

    Importance of reviews for Brands and Retailers

    Customers do not make blind purchases. Consumers read reviews before buying products. Statistics show that irrespective of the industry, having a positive online presence is essential and has become an integral part of branding. It also indicates that customers have a high confidence level in fellow consumers’ opinions. Overall, positive online ratings & reviews can help skyrocket eCommerce sales.

    Customers are more likely to purchase if other customers, even strangers, agree that it was a great purchase. Reviews also make brands more visible. 

    Why are fake online reviews so resilient?

    A significant reason is that the ROI of getting fake reviews increases profitability & sales multifold. For example, an extra star on Yelp can increase a restaurant’s revenue by 5% to 9%. FTC has said that the expenditure on fake reviews can provide a 20x return. However, fake and incentivized reviews are a huge problem. Amazon, one of the largest eCommerce marketplaces, banned incentivized reviews in 2016. It took down suspicious reviews and has taken legal action against sellers who violate its policies. 

    Online Reviews
    Online Reviews

    How to Spot a Fake Review on Amazon

    Marketplaces, Google, and review sites like Yelp can get hundreds of thousands of reviews daily. In a survey by PCMag that interviewed 1,000 US shoppers who looked forward to shopping on Prime Day 2020, only 16% were very confident about detecting fake Amazon product reviews, and 24% were confident they could do it. The rest of the survey respondents were somewhat or not confident they could pick out the fakes on Amazon. Here are our best tips for spotting fake reviews on marketplaces like Amazon:

    • Duplicate Content: If you notice dozens of reviews with the same description and title as if they were copied and pasted multiple times, they’re most likely fake reviews. 
    • Multiple Reviews on the Same Day: Another identification of fake reviews is when there are dozens or multiple reviews on a single day. There can be a bunch of both positive and negative reviews for products.
    • Unverified or Anonymous Reviewers: You can see if the review is from a verified buyer on Amazon. Brands can also check if they have any record of the reviewer’s purchase to weed out fake reviews. 
    • Incorrect Language: Fake reviews can come from people outside your country. If you notice multiple reviews with similar incorrect words and common errors, there is a good chance those reviews are fake, and someone paid the reviewer to write them.

    What can eCommerce brands do to protect themselves against fake reviews?

    • Follow a zero-tolerance policy for fake reviews.

    The major step is to ensure that fake reviews are never posted on your site. Allowing fake reviews negatively affects your business and your bottom line. You can hire a third-party UGC moderator that uses data-driven, anti-fraud methods to evaluate reviews. It will be a much more successful and quicker step in protecting your brand’s reputation.

    • Don’t screen out negative reviews. 

    While receiving a negative review might be the worst nightmare, they’re necessary for a successful UGC program. Customers are more likely to purchase from a business that responds to all reviews, including negative reviews. Customers said that negative reviews have more detailed product information, while 32% of those customers think they’re less likely to be fake. Besides, brands that respond to negative reviews gain customers’ trust and loyalty.
    Here are some Tips on how to Respond to Negative reviews online. 

    • Be transparent about how you collect UGC.

    Brands can ensure that their customers trust user-generated content by being honest about how they collected it. Companies should never ask for paid or incentivized positive reviews. Instead, brands should empower their customers to leave honest feedback. If you’re offering free products, a chance to win something, or discount coupons in exchange for an unbiased review, then the review should specify how it was collected. For example, you can add indicators like “this reviewer received a coupon or a free product in exchange for honest feedback.

    • Maintain trust

    Having fake reviews causes a loss of trust, with many consumers believing that they have seen fake reviews for online and offline businesses. Removing fake reviews doesn’t only help with revenue and brand trust, but it also helps brands to maintain trust among their existing and future customers. 

    Conclusion

    Fake reviews are one of the biggest reputation killers and a huge problem for eCommerce platforms, brands, and customers. Brands must take the necessary steps to minimize the risk of fake reviews and expand businesses among authentic users. Although modern text generation tools are becoming more competent in writing realistic reviews, there are AI- and ML-backed tools that can accurately detect reviews written by other machines. 

    Need help tracking your online ratings & reviews? Or decoding customer sentiment from reviews they’ve left for your products? DataWeave offers a customizable and scaleable data solution to analyse ratings and reviews for online retailers and brands vis v vis their competitors.
    Sign up for a demo with our team to know how DataWeave can help.

  • How VCs and Brand Rollups are using Data for faster Acquisitions

    How VCs and Brand Rollups are using Data for faster Acquisitions

    When it comes to brands – the biggest story of 2021 was the astronomical growth of Brand Roll-ups. For the uninitiated, Brand Roll-ups are companies that acquire multiple digital consumer brands and then scale these brands 100x by leveraging their own operational expertise across eCommerce platforms, Supply Chain, Warehousing, Marketing, and so on.

    Thrasio is the poster boy for the Brand roll-ups and is valued at over 10 Bn USD.

    Brand rollups have raised over $12 billion in 2021 and the trend only seems to be accelerating in 2022. Not only Brand Roll ups, but VCs too have been pouring money into digital brands. In India, 77+ brands have raised more than 2B USD in 2021. In the US this number is estimated to be north of $10 billion.

    Cumulative capital raised by Amazon Aggregators
    Cumulative capital raised by Amazon Aggregators

    Scaling fast doesn’t come easy. It comes with its own set of challenges. So even with ample experience in running and scaling brands, Brand roll-ups are posed with unique challenges.

    Challenge of Scouting the right brand

    There are 1000s of online consumer brands and new ones are launching every day. Every Brand roll-up wants to be the first one to scout a brand – but this is not easy.

    The challenge here is to identify & pick the right brands without having access to any sales or financial data. Every Brand Rollup has a wishlist with regards to the number of SKUs, price points, reviews, and ratings as well – but don’t have tools in place to scout brands with these criteria in mind. And across multiple platforms and categories, the problem gets more complicated.

    This is an ongoing problem since a brand that was not selling well yesterday may start hitting higher sales numbers a week down the line – and that is why Brand scouting has to be a continuous process.

    One way these aggregators have solved this challenge is by offering mouth-watering referral fees for referring a brand. But this is not a sustainable long-term solution.

    Data Comes to the Rescue

    What Brand Roll-ups need is a continuous and automated data first Brand Scouting solution to enable them to scout the right brands.

    • What are all the brands in a category of interest?
    • Which of these brands is within the filters of Number of SKUs, Price Range, etc.?
    • Which brands have shown an exceptional rise in search rankings?
    • Which brands have shown the most increase in the number of ratings and reviews?
    • Which brands have the highest gain in the customer ratings?
    • What are the estimated sales and market share of the brands?

    DataWeave’s Brand Scouting solution solves exactly this.

    DataWeave’s Brand Scouting Solution

    DataWeave’s Brand Scouting Solution is a comprehensive solution to help Brand Rollups and VCs scout for the ideal brand that fits their acquisition profile. We leverage public data collected from multiple eCommerce platforms to get them the desired information on brands they’re looking for.

    For all the focused categories (Typically 30-40) – we collect data of all the SKUs (Typically 15,000-20,000) and aggregate that at a Brand level:

    • Ranking – Usually Brand Rollups are not interested in the Brands which are on the first page. But, they are interested in the brands which might be b/w 500 to 10,000 ranks but are showing an exceptional gain in ranking week on week.
    Brand Discoverability & Ranking on Amazon
    Brand Discoverability & Ranking on Amazon
    • Ratings – It’s important to look at brands that are showing high improvement in ratings or have consistently shown high ratings. The proportion of 5 stars vs. 1 star is an important metric here.
    • Number of Reviews and Ratings – We enable you to find brands that have both high ratings as well as a high number of reviews. This is a very good metric to find the brands in a category that are getting exceptional customer love.
    Brand Popularity Tracker
    Brand Popularity Tracker
    • Filters – We enable filtering in terms of – No. of SKUs, Price Range, Rating and Reviews and even can eliminate established brands so that you only see the brands which qualify your criteria. We also enable you to separately analyze brands that are buying sponsored ads in a category, so you have a clear distinction between organic and sponsored growth of these brands.
    • Trends – What is important is not just the static performance on the day of analysis – but a trend analysis over a period of time to find the brands which are growing exceptionally.
    Brand Score Trend, Average Rating trend & No of Reviews Trend
    Brand Score Trend, Average Rating trend & No of Reviews Trend

    … but, wait there’s more.

    We compliment Brand Scouting with three more solutions to provide the right context and further analysis needed to provide comprehensive insights into the category and platforms where you are scouting for brands:

    Category Analytics: When you are looking at a category and the brands in that category, it is often important to understand how dynamic that category is. We can help analyze:

    • If the category is crowded with more brands per product.
    • Does it have space for new brands?
    • What is the number of new brands entering that category?
    • What is the number of new SKUs entering that category?
    Category & Subcategory Evaluation
    Category & Subcategory Evaluation

    We can also help with benchmarking the category – to help understand how the brand that you are scouting is doing when compared to its category peers.

    Rank Group versus Price, Rating & No of Reviews
    Rank Group versus Price, Rating & No of Reviews

    Sales & Share: We can also provide a good directional estimate of the sales and market share of all the SKUs in the category wherein you are scouting for brands. These are estimates powered by our proprietary machine learning algorithms and can help you solidify your hypothesis around a blog or a category.

    Revenue by Price Points
    Revenue by Price Points

    Sentiment Analysis of Reviews: Customer reviews tell more about the qualitative aspects of the SKU and the brand itself. Our algorithms can help understand what features of a brand or a product do customers really care about. We can answer questions such as:

    • Which features are mentioned most commonly?
    • Which features are mentioned positively or negatively?
    • What adjective is used to describe that particular feature?
    Customer Sentiment Analysis
    Customer Sentiment Analysis

    The suite of Brand Scouting and complementary solutions is evolving rapidly as the space is evolving rapidly. We are supporting several VCs and Brand Roll-ups globally to scout for brands.

    The best aspect about DataWeave is our ability to scout brands across 2,000+ eCommerce platforms globally across geographies. We are super stoked to be playing an enabler in the Brand Rollup revolution.

    Beyond Brand Scouting – Digital Shelf Analytics

    The challenge for Brand roll-ups is not over by just scouting and acquiring a brand. The journey is just about starting – the next challenge that the Brand Rollup faces now is to scale up these brands.

    The challenge the Brand Rollup face is unique and very different from a single brand operator or even traditional CPG conglomerates.

    DataWeave’s flexible product philosophy enables Brand Roll-ups to diagnose and measure the performance of multiple brands across multiple platforms in one dashboard.

  • How Restaurants can use QSR Intelligence to Drive Sales

    How Restaurants can use QSR Intelligence to Drive Sales

    Quick service restaurants (QSR) are not only about delivering great food. They also have to overcome challenges like delivery, logistics, and affordable pricing, especially since covid-19 has staggered the entire industry. QSR intelligence helps restaurants get real-time insight into their performance across food delivery apps. With QSR intelligence, restaurants can identify the highest paying buyers across customer segments, demographics, and locations. Data-driven insights will help QSRs improve performance, decrease delivery time, optimize ad budget, and increase food quality – all with the goal to scale revenue and increase orders through food apps.

    The global fast food and quick service restaurant market are expected to grow at a CAGR of 5.1% from 2020 to 2027. The QSR industry is rapidly growing to encompass the changing needs of customers. 60% of U.S. consumers order delivery or takeout once a week and online ordering is growing 300% faster than in-house dining. With QSR intelligence, restaurants can get insights into metrics that will drive their profitability by helping them to fine-tune menus, enhance customer interaction, improve advertisements, and adjust inventory.

    Benefits of QSR Intelligence

    Continuous in-depth analysis of restaurant statistical data will help companies spot trends and devise strategies to improve sales via food apps. Here are a few benefits of QSR intelligence:

    a.    Improve estimates & minimize wait times

    QSR intelligence can help with accurate sales forecasting. With big data, restaurants can track their popular dishes or combos for various meal times to minimize wait times and increase delivery speed. It can also inform restaurants about upcoming trends, especially during holidays and festivals. Keeping an eye for trends will play a significant role in maximizing efficiency during food preparation and ensuring accurate food delivery ETAs.

    b.    Location-based promotions

    QSR intelligence allows restaurants to target customers based on their proximity to the restaurant. The food must be delivered at a particular time to the customers to enjoy the dish at the right temperature. QSRs can apply demographic intelligence to determine cancellation rates, delivery charges, and the proportion of demand and supply. These metrics will help QSRs to improve location-based promotions.

    c.    Increase ROI on deliveries

    To increase return on investment through food deliveries, QSRs can track metrics like location-based promotions, various payment options, ratings, etc. Tracking these metrics will help QSRs offer accurate ETAs, improve operational efficiency, and personalize services, which will increase revenue. Restaurants will also be able to understand where they can adjust their profit margins to increase revenue while maintaining a cumulative level of success.

    How to use QSR Intelligence

    a.    Assortment and availability

    The more restaurants can understand what and how their customers eat, the better they will be prepared to service those demands throughout the day. For example, QSRs can calibrate the menu, ingredients availability, and kitchen preparation time depending on their customers’ orders for lunch and dinner. This also helps optimize daily workflow, such as reorganizing staff to lower labor costs, optimizing the supply chain for ingredient delivery, and revamping the menu to offer better dishes. Another way to ensure your availability is to analyze your busiest hours and adjust the staff and delivery workforce accordingly. For example, if your customers tend to order more during breakfast, it’s worth considering opening your restaurant a bit earlier.

    QSR availability across 4 Food Delivery apps
    Availability across 4 QSR Food Delivery apps
    Availability trend during peak hours - Lunch & Dinner
    Availability trend during peak hours – Lunch & Dinner

    b.    Delivery time

    One of the most driving factors for the success of QSR is delivery time. Restaurants have to ensure the food is delivered as quickly as possible so customers can consume it at the right temperature. Data-driven insights can help restaurants track repeat addresses, find shortcuts or time-saving routes, and avoid unfamiliar or low delivery locations.

    QSRs have to analyze the entire delivery process from time taken to order on the app, how quickly kitchens can prepare orders, hand over to delivery partners, and get them to the customers. An essential part of QSRs is throughput, the speed at which they can process and deliver orders. During peak hours like lunch and dinner, faster service and quick ETAs ensure that customers do not choose other restaurants. If you have different menus for breakfast and other meals, ensure that your foodservice app can remove such menus when they are not available.

    Delivery Time Analysis
    Delivery Time Analysis
    Delivery Fee Analysis
    Delivery Fee Analysis

    c.    Pricing and Promotions

    QSRs have to understand customers’ price sensitivity while determining delivery costs and ensuring profitability for the business and delivery partners. Customers might look for free deliveries but not adding delivery charges might lead to loss. A deep dive into common transaction data across the locations will allow restaurants to understand the price sensitivity of all customer segments, helping them make intelligent pricing decisions.

    QSR intelligence can also help restaurants determine which delivery locations are most profitable. This helps to adjust the delivery radius, fee, and promotions. Restaurants can offer promo codes, coupons, referral codes, etc., to attract customers and encourage repeat purchases.

    d.    Discoverability

    Restaurants have to ensure that their dishes are on the first-page listing. With QSR intelligence on category analysis, keyword optimization, and competition analysis, restaurants can help their customers discover dishes. This also includes optimizing listings for pricing and rating and delivery fees and availability during peak times such as breakfast, lunch, and dinner.

    e.    Advertisement Optimizer

    QSRs can use data to optimize the advertisement budget and adequately improve return on investment. They can track the visibility of advertisement banners across locations and optimize them for different times of the day. Data analysis can also help restaurants understand which customer segments are more likely to convert to long-term loyalists. This data will help QSRs design personalized campaigns and align advertisement budgets while converting them to long-term customers, further improving the bottom line.

    Ad spends by identifying carousels with the highest visibility
    Ad spends by identifying carousels with the highest visibility
    Track QSRs performance across Carousels across multiple zip codes
    Track QSRs performance across Carousels across multiple zip codes

    f.     Growth & Expansion

    Upselling and cross-selling are two popular tactics that improve growth for quick-service restaurants. However, that requires a rich understanding of customers’ price sensitivity, preferences, and behavior. QSR intelligence can provide information about which upsell and cross-selling offers a customer segment is likely to value and which optimal channels for distributing the offer.

    Conclusion

    Quick service restaurants can track critical data points and use them to increase revenue and improve customer experience. Learning how to price, promote, and deliver food to customers during a pandemic can be challenging. QSR intelligence will help brands attract the right clientele, adjust inventory, reduce overall marketing costs, and increase order rates. This will also help increase customer loyalty across segments which can, in turn, increase the number of returning customers and profitability.

  • UK’s Biggest Sale Days: What we saw in 2021 and trends for 2022

    UK’s Biggest Sale Days: What we saw in 2021 and trends for 2022

    Customers love discounts, and promotions are the most effective tool to attract shoppers and increase sales during the holiday season and clearance sales. According to a survey, 76% of UK customers look for discounts before purchasing a product. Promotional discounts encourage customers to try new brands. And this is why brands often have a special coupon for first-time users. 

    According to Software Advice, discounting tops the pricing strategy for retailers across all industries. It is preferred by 97% of survey respondents over other promotional strategies. 

    Share of Respondents
    Share of Respondents

    Retail Trends in the UK for 2022

    The arrival of the Omicron variant in December 2021 slashed the shopping mood of UK customers and led to a 3.7% monthly drop in retail sales, but sales were still higher than February 2020 levels when Covid-19 first hit worldwide. Sales during the holiday season in 2021 took a hit due to a consistent decline in product availability and an increase in prices.  Inflation too started to rise in 2021 and is expected to increase by 7% by spring 2022. However, despite inflation, retail sales jumped back in January 2022. In fact, it is predicted that inflation will be a key driver of sales growth, with underlying demand across categories being uneven. Keeping that in mind, let’s look at sales growth across categories in 2021 and projected growth in 2022.

    Category Breakdown: Sales growth 2021/22
    Category Breakdown: Sales growth 2021/22

    Discounting Trends we saw in the UK in 2021

    Methodology

    • We tracked prices on the three biggest Sales Days in the UK
      – Amazon Prime Day, June 21st & 22nd 2021
      – Black Friday, Nov 26th, 2021
      – Cyber Monday, Nov 29th, 2021
    • Categories tracked: Beauty, Fashion, Electronics, Home Improvement, Furniture 
    • Websites tracked: Amazon UK, OnBuy, eBay UK, Etsy, Wayfair, Selfridges, John Lewis

    Prime Day, Black Friday, and Cyber Monday are three of the biggest sales days with comparable discounts. However, according to new research, in 54% of cases, it depends on the category of product you’re after that determines the volume of discount you get. For example, tech items such as smartphones, laptops, games consoles, smartwatches, and wireless speakers were cheaper on Black Friday but may not necessarily have been cheaper on the other sale days. 

    We wanted to see which sale period had the most number of products on discount during the three big sale events. We also wanted to see which of those three sales would’ve been the best for consumers to get a higher section of products at a discount. 

    How Big were the Discounts?

    Discount across 3 key Sale Days
    Discount across 3 key Sale Days

    32% of products went on discount during Black Friday, 35% on Cyber Monday, and only 6.6% on Prime Day. One factor contributing to the low Prime Day percentage is the fact that not all retailers participate in discounting wars during Prime Day since it’s an exclusive Amazon-only sale. Customers looking for the best deals would’ve gotten them during the holiday season with a combination of the Black Friday & Cyber Monday sales. 

    Another interesting thing to note is the percentage discount – on Prime Day, only 0.2% of products had a discount of over 50% of all the discounted products. While on Black Friday & Cyber Monday that number was 1.7% & 1.3% respectively. 

    In conclusion, more products were offered at a discount on Black Friday & Cyber Monday; and the total percentage discount on those products was also higher.

    Which Categories had the Maximum Discount?

    Discounts by category
    Discounts by category

    On Black Friday, an estimated 47% of consumers in the UK planned to shop for electronics, whereas 40% of customers planned to shop for clothing and footwear during Black Friday to Cyber Monday.  The top-selling categories across the 48 hours of Amazon UK’s Black Friday 2021 sale included Home, Toys, Beauty, Books, and Health & Personal Care.

    Our data shows that Categories with the highest discounts were Beauty and Electronics with the highest discount on all 3 sale events. These 2 categories had discounts on over 40% products on Black Friday & Cyber Monday while categories like Home Improvement were in the 30 – 35% range, Furniture in the 27 – 32% range and Fashion has the least products on discounts at a little over 15%

    In the fashion category in the UK, Amazon UK offered the highest percentage of items with a price decrease (31.6%), whereas eBay offered the most significant magnitude of price decrease (14.3%). 

    Which UK Retailers gave the most discounts?

    OnBuy is an emerging marketplace in the UK that offers impressive discounted prices and is taking on top UK marketplaces like Amazon. It’s ranked Britain’s fastest-growing eCommerce platform in 2020 and also the fastest grower by traffic. The low listing fees starting at 5% allow sellers to competitively price their products, making them more accessible to a greater number of buyers with huge discounts. The most prominent deals and discounts are highlighted on the landing page and featured across OnBuy’s social pages to grab the audience’s attention. 

    Discounts by Retailer
    Discounts by Retailer

    This was clearly reflective in the data we gathered from the 3 big sales in 2021. Most retailers in the UK, including Amazon offered at best 20% of their products, in the categories we tracked, at discount. The only outlier was OnBuy – OnBuy offered close to 90% of their products at discount! 

    OnBuy was able to offer a comparatively high number of discounted products than their competition because the magnitude of the discount was much much lower. The platform offered minimal discounts; out of the 90% of discounted products, 80% of those products had discounts that were less than 10%. As opposed to other retailers who had under 7% of their products on discounts of less than 10%.

    OnBuy’s discounting strategy built a perception that they were the biggest discounters, even when the discounts were not as deep.

    Black Friday v/s Cyber Monday – which one was better for holiday shoppers?

    Discount by category- Black Friday VS Cyber Monday
    Discount by category- Black Friday VS Cyber Monday

    Black Friday kicks off the holiday shopping season and is synonymous with some of the most significant sales after Thanksgiving. But until recently, Cyber Monday has become a great way for eCommerce retailers to capitalize on holiday discounts and expand their most beneficial sales events of the year.

    In 2021, retailers pulled in $8.9 billion in Black Friday online sales and a total sales of $10.7 billion on Cyber Monday. In the YOY review, Black Friday saw a decline of 1.3% from 2020’s record of $9.03 billion, and Cyber Monday saw a drop of 1.4%, only $100 million shy of $10.8 billion in 2020. 

    Across Beauty, Home Improvement, Electronics & Furniture categories, we saw that more products were on discount on Cyber Monday v/s Black Friday. However, the opposite was true for the Fashion Category. In the Fashion Category, we saw a marginally higher number of products on Discount during Black Friday than Cyber Monday.

    Discount percentages across categories
    Discount percentages across categories

    Across both sales, the Electronics category offered the highest discounts at over 40% of products discounted compared to other categories on both Black Friday & Cyber Monday. However, a very small fraction of the products had a discount of over 50%, indicating the lack of ‘BIG blockbuster deals’ in this category. At the same time, the Fashion category offered the least number of deals with less than 20% products on discount, but the highest magnitude of discount across the board! On Black Friday, 3.8% of products had discounts higher than 50%, and 2.6% of products on Cyber Monday. In most other categories, between 1 – 1.5% of products had over 50% discount. However, Fashion brands offered more than 50% discount on 2x the average number of products on both sale days.

    Why did the Fashion Category offer such high discounts? Brands are now capitalizing on customers’ need for instant gratification in the age of see-now, buy-now fashion trends by offering their products at high discounts. It also allows them to quickly eliminate overstock. However, this has given rise to fast fashion, a trend that focuses on rapidly producing low-quality clothes in huge volume. Fast fashion focuses on replicating trendy pieces like streetwear and fashion week designs, not four times a year but every week, if not daily. Fast fashion promotes brands to manufacture and sell low-quality merchandise that goes out of trend as soon as buyers wear it once. There is little to no time for quality control, and pieces are thrown away after a few wears. In the UK alone, 300,000 tonnes of used clothes are buried or burned in landfills each year. However, every element of fast fashion from rapid production, competitive pricing, to trend replication has a detrimental impact on the planet.

    Conclusion  

    The effects of COVID-19 can be seen far and wide in the UK retail industry, especially with a steep rise in inflation. Fortunately, even though retail sales in the UK declined during the 2021 holiday season due to the Omicron variant, they increased during Black Friday and Cyber Monday. Sales also jumped back in January 2022 and are further projected to grow by 5% in 2022. Additionally, brands can sustain the impact of disruptive factors throughout 2022 by ensuring their Digital Shelf is updated and flexible enough to react swiftly to both threats and opportunities in order to maximize the chances of success. 

    Reach out to the team at DataWeave if you’d like to make smarter pricing & discounting decisions with up-to-date competitive insights. 

  • Valentine’s Day eCommerce Insights

    Valentine’s Day eCommerce Insights

    Access to these types of real-time digital marketplace insights can enable retailers and brands to make strategic decisions and help drive profitable growth in an intensifying competitive environment. Be sure to reach out to our Retail Analytics experts for access to more details regarding the above analysis.         

  • What Historical Pricing Data can tell you & how to use it

    What Historical Pricing Data can tell you & how to use it

    For many brands, pricing strategy boils down to guesswork — shooting in the dark and hoping consumers are willing and happy to pay. However, the ‘throw it at the wall, and see what sticks’ pricing strategy leads to big pricing mistakes. Pinning down an optimal price for products requires a clear picture of ideal customers, understanding each customer segment’s behavior, a solid grasp of your product’s value, and an analysis of competitors. Pricing analytics can help brands track a wide range of pricing metrics with cutting-edge analytical tools and use insights to get ahead of their competition. This analysis uses historical data to understand how previous pricing and promotion activities affect brand, sales, and customer price perception. It often involves identifying opportunities and weaknesses in competitors’ pricing strategies and exploiting them to improve sales and revenue. 

    Pricing analytics helps brands understand how product pricing and promotions affect profitability and the steps they can take to optimize their pricing structures. Brands can leverage their pricing and consumer data to design appropriate pricing models for achieving their sales goals.

    Here is a brief overview of pricing analytics, its benefits, and ways to improve sales with historical pricing analytics.

    What is historical pricing data analytics?

    historical pricing data analytics
    Historical Pricing Data Analytics

    Pricing analytics uses historical pricing and demand data to understand how pricing activities have affected profitability and overall brand. It also helps to optimize a brands’ pricing strategy for maximum revenue. Manual tracking of pricing for brands with numerous product lines, multiple selling points, different customer tiers, and complex product bundles is a huge challenge. Brands from every sector and industry vertical, manufacturing and distribution to retail and eCommerce, can benefit from pricing analytics.

    There are three types of pricing analysis:

    Descriptive

    Descriptive pricing analytics involves analyzing historical data to evaluate how customers have perceived and reacted to pricing fluctuations in the past. It analyzes metrics such as month-on-month sales growth, average revenue per customer, year-on-year pricing changes, or changes to the number of registrations to a particular service over a specific period. 

    Predictive

    Although brands can’t accurately predict how pricing changes will reflect sales, they can use predictive pricing analytics to get insights into the best possible chance of doing so. Predictive pricing analyzes historical data with statistical algorithms and machine learning to predict the price and trends of products in the future. It also helps brands to optimize their prices with future goals.

    Prescriptive

    Prescriptive pricing analytics is the opposite of descriptive analytics. Unlike descriptive analytics that helps brands explore their historical data to understand customer response after an event, prescriptive analytics help brands design better and more informed strategies. With prescriptive analytics, brands can shape their growth strategies to achieve more sustainable results over the long term.

    Benefits of historical pricing data analytics

    Benefits of historical pricing data analytics
    Benefits of Historical Pricing Data Analytics

    Acquire insights into customers price perception

    While analyzing the metrics to understand pricing optimization, brands can also gather valuable insights into their customer’s price perception. Pricing analytics helps brands understand which customer segments are the most (and least) profitable and how each segment responds to specific pricing strategies. With historical pricing data analytics, brands can also intelligently link pricing and promotions by first determining customer price sensitivity then gauging the effectiveness of promotions. 

    Fully Optimized Pricing

    Historical pricing analytics means eliminating guesswork from deciding the optimal pricing for a given product. By analyzing historical pricing data, brands can discover how their past pricing and promotional decisions impact profitability. Based on this historical data, they can also test various pricing strategies like value-based and dynamic pricing. It also allows brands to learn which customer segments are most likely to respond positively to price change. These insights from pricing analytics will drive more effective (and profitable) pricing decisions.

    Recognize pricing tiers that work the best

    Many brands have gaps in their pricing strategy — underpriced or overpriced tiers, pricing leaks, markup errors, or neglected upsell opportunities. Tiered pricing models are prevalent in subscription-based brands where brands offer tiers to meet the needs of diverse customer segments. With historical pricing analytics, brands can improve their pricing tiers and get insight into the right number of tiers and optimal prices for each. Pricing analytics will comb a brand’s historical data to find tier pricing mistakes to improve sales and revenue.

    Planning Pricing Strategies and Promotions

    Promotional pricing decisions are critical for any brand, as pricing perception is directly linked to consumer demand and profits. Brands have to carefully plan promotions that include variables such as list prices, special offers, advertisements, and discounts while ensuring profit margins. With predictive analytics, brands can determine optimal discount levels, keep a close eye on the competition, and announce promotional offers when customers are likely to purchase. Historical pricing analysis also helps predict revenue and determine optimal locations and platforms for promotional ads.

    Discover profitable channels

    Not all sales channels bring equal revenue to your brand. Historical pricing analysis can help you determine the most effective quality, volume, and revenue channels. Brands must understand which marketing and sales channels bring quality leads that convert to paying customers. It also helps to determine which eCommerce channels are most profitable so you can optimize your budget and identify channels you should be investing in as a part of future customer acquisition strategies. 

    Metrics to track

    Metrics to track
    Metrics to Track

    Here are a few pricing analytics metrics that can help brands to understand customer behavior towards pricing:

    Willingness to Pay (WTP)

    WTP, also known as price sensitivity, is the maximum price your potential customers are willing to pay for your service or product. It is an essential part of pricing strategy since you have no other way of understanding whether your product can yield an augmented product value. Numerous factors are responsible for a customer’s willingness to pay, and it’s not static. Brands must track willingness to pay for all customer segments to ensure that the product is priced competitively and drives maximum profit while staying in line with current market conditions. 

    Feature Value Analysis

    Feature value analysis, also known as relative reference analysis, measures the most important features to customers in relation to other features of a product or service. Analyzing critical features to customer segments will help brands price products based on basic or premium components. It can also help to better bundle your services or products so you can drive the most revenue. 

    Average Revenue per User (ARPU)

    The average revenue per user is the revenue generated from the sum of active users divided by the total number of users in a monthly time frame. Delving deeper into ARPU can help brands compare numbers with rivals and check how all products or customer segments perform. 

    Lifetime Value (LTV)

    Lifetime Value offers a complete picture of a user’s journey and the average revenue that the user will generate throughout their engagement as a customer with your brand. It helps brands determine various economic decisions such as marketing budgets, profitability, forecasting, and resource allocation. 

    Customer Acquisition Cost (CAC)

    A successful and profitable brand needs to balance its customer acquisition cost or CAC. It is about spending the right amount of resources and time to drive new customers without jeopardizing their lifetime value and revenue. Correct calculation of CAC helps brands to quantify their sales funnel and determine the efficiency and profitability of their strategies.

    Conclusion

    Historical pricing analytics is a powerful tool, and it can make a huge difference to a brand’s potential by increasing sales and unlocking incredible profitability in a relatively short time. Historical analysis of pricing and promotions data will help brands get better marketing returns than relying on traditional pricing approaches. 

    Leveraging pricing analytics will prevent brands from blindly reacting to competitor price changes and support solutions for scaling up price transformation efforts. By using historical pricing data, brands can more effectively segment their customers for marketing and promotion strategies. Properly utilizing predictive analytics and past sales data can help cut costs and keep profit margins high by adjusting production and prices according to market trends.
    Need help tracking your competitor prices? Or want historic pricing insights for your own brand? Or need to track the efficacy of your online promotions?
    Sign up for a demo     with our team to know how DataWeave can help!

  • How to respond to Negative Online Reviews

    How to respond to Negative Online Reviews

    Most brand & marketing professionals fear negative feedback and reviews. Negative reviews and ratings can not only hurt your organic product visibility online, but they also impact real business outcomes and purchase decisions potential customers will make about your product. 

    … but getting negative reviews is not always a bad thing. These unflattering reviews help give consumers real insights into your product and help them understand their features, attributes, benefits, and downsides better as described by other customers to give them a more realistic picture. Shoppers trust user generated reviews more than content brands share with them, which is why it’s really important for brands to interject in these conversations, address negative reviews and nudge customers towards building trust in their products.

    Here are a few things to keep in mind when responding to negative reviews. 

    Be actionable and solution-oriented with your responses!

    Even the strongest brands can’t avoid negative reviews, but what sets one apart from the other is how they tackle these reviews. A prompt and solution-oriented response can actually help salvage a negative situation in a lot of cases. 

    build brand trust
    Build Brand Trust

    Let’s take a look at Clinique & the unique approach they took towards responding to negative reviews. Shown above is one of its bestselling products Moisture Surge™ 100H Auto-Replenishing Hydrator. This product got an average of 4.7 stars since its launch in early 2021. 99% of customers even said they would recommend this product. And, in comparison to the over 370 positive reviews, there were just 5 negative reviews! Instead of basking in the glory of the numerous positive reviews, Clinique chose to promptly reply instead & not dismiss negative reviews even if there were just a tiny number. This goes a long way for any brand. 

    Negative feedback
    Negative feedback

    Clinique not only addressed the customer’s concerns but also offered a ‘no questions asked’ refund and insisted that the customer take the conversation offline through a customer care agent. This action will help Clinique build long-term trust with not only the customers who had given them a low rating but the new ones too, who may stumble upon these negative reviews and see first-hand how customer-centric the brand is. 

    Respond promptly to keep things under control

    A quick response to a negative review is supercritical. Even if you’re unable to resolve the customer’s problem immediately, acknowledging the review promptly lets them know their concern is a priority. On the plus side, it may also help them calm down and hold them back from posting even nastier comments. Aim to respond within 24 – 48 hours from the time a negative review is posted. 

    The quicker a customer hears from you, the more sincere your words will feel to them.

    prompt response
    Prompt Response

    Here’s an example of how Chobani yoghurts tackled a negative review. You’ll notice, they responded almost immediately when a customer complained about the “RANCID” tasting yoghurt. Responding minutes after the review came in shows their seriousness towards dealing with the situation and that they value customer feedback. Apart from prompt response, they even offered to investigate and work towards a solution. 

    Look for a chance to take the discussion offline

    negative feedback system
    Negative Feedback System

    Take the conversation offline by giving a phone number or email where customers can connect with a real person or brand representative. The goal is to move the conversation from a public forum to a private channel where a personal touch can be added. It could be a customer care number, a DM on a social platform, or a direct call back to the customer to listen to the details of their complaint. Additionally, connecting offline helps resolve issues faster without letting the problem escalate. 

    Do NOT get defensive

    When it comes to responding to negative reviews, as a thumb rule pushing back or getting defensive is an absolute no-no. Being humble and accepting of negative feedback is important, and responding with grace, is even more important. 

    Let’s look at this example of a negative review left by an irate customer about the terrible IKEA customer service. Instead of getting defensive, IKEA politely acknowledges the feedback, apologies for the inconvenience, and offered a solution to help the customer sort out the issue with the order immediately! 

    customer feedback
    Customer Feedback

    A brand’s response to a negative review not only helps the individual who left the review in the first place but actually impacts other customers who will read it months down the line.

    Remember to follow-up

    Many times brands jump in promptly when a customer posts a negative review. They’re solution-oriented and some help resolve customer issues immediately too. The hard part’s done! However, where a lot of brands fall short, is when it comes to following up with customers once their concern has been addressed and they’re back to being brand advocates again. 

    Keeping that thought in mind, if it’s possible to get a customer who left a negative review to update or change it after their concern has been resolved could be a very impactful way to build brand trust. According to the Retail Consumer Report, 33% of customers turned around and posted a positive review, and 34% deleted the original negative review after having received a response from the brand or retailer in question. 

    Conclusion

    Even though brands have limited to almost no control over how customers perceive their products online, they can still participate and interact with customers to improve their online reputation. They can listen in on the online conversations and adapt to customer feedback promptly based on what shoppers are discussing via reviews. Also, don’t filter the types of reviews when responding to your customers, and aside from the positive and neutral reviews, treat your negative reviews with extra care. Resolve them responsibly to win a customer for life!

    If you need help tracking your online product reviews or analyzing the pulse of your customer sentiments to discover a wealth of insights, reach out to our Digital Shelf experts to learn more about our Review & Sentiment Analysis solution. 

  • Best Practices to avoid MAP Violations

    Best Practices to avoid MAP Violations

    Competition is a fundamental and healthy part of commerce that protects customers by keeping prices low and the quality of services (and choice of goods) high.

     Healthy competition drives prices down, but it can harm brands and their reputation without a pricing policy. The manufacturer or brand designs MAP or Minimum Advertised Pricing policies to stipulate retailers’ lowest price point to advertise the product. It is an agreement between distributors and manufacturers about the minimum price that retailers and resellers can advertise the product for sale. 

    Most legitimate brands have a MAP policy, especially brands that rely heavily on brand identity. It becomes critical that they maintain price parity across retailers. When a retailer violates MAP policies, brands can penalize them under the agreed-upon terms or terminate contracts. 

    In this blog, you will learn about MAP policy, its benefits, and tips on tackling MAP violations. 

    1. What is a MAP policy?

    MAP policy
    MAP Violations

    MAP stands for Minimum Advertised Price, and brands create MAP policies to ensure that retailers don’t advertise their products below the specified price. However, it only controls advertised prices, ensuring the retailers don’t display a lower price in online listings or advertisements. Since it doesn’t cover the checkout price, retailers can sell products at a lower price through promotional offers like discounts and cashback during checkout. 

    MAP policies ensure a price war between eCommerce platforms does not devalue products and that an even playing field is set among retailers that allow everyone to drive margins. Brands have a legal right to withdraw products if a retailer advertises products below the minimum advertised price. Brands can also restrict future sales or refuse to replenish products after the current stock has sold out if an eCommerce platform, reseller, or distributor violates MAP policies. 

    In the U.S., MAP policies fall under federal antitrust law since they restrict advertisement pricing rather than the last sales price. However, in the UK and the EU, violation of minimum advertised pricing is an infringement of current competition laws.

    2. Why Does Having a MAP Policy Matter?

    Having a MAP policy protects both brands and retailers while ensuring consumers get the best-priced items. Following are the benefits of having a MAP policy:

    a. Prevent margin erosion

    Although online retailers are willing to take a margin cut to attract traffic, selling products below MAP can significantly hurt a brand’s bottom line. Setting a minimum advertised price benefits both parties. It allows shoppers to purchase products at the best-valued price & also creates a balanced economy and prevents hyper-competition of products between retailers. However, manufacturers must set a realistic pricing policy that matches current market demand, ensuring eCommerce platforms implement MAP while taking care of the margins. 

    b. Retain brand identity

    pricing policy
    Brand Protection

    Price is one of the essential indicators consumers use to determine the authenticity and value of a product. Constant price fluctuations can negatively impact a brand’s reputation. Brands need to safeguard their pricing to create a consistent price perception. Price changes often make the buying decision complex since consumers no longer have a clear reference of prices. It also shifts purchasers’ attention from the brand and product features to its price. With price fluctuations, brands that were used to be differentiated for their features can be seen as commodities.

    Low prices & MAP violations on an online platform can even be a sign of counterfeit products or unauthorized sellers. However, customers might hold the brand responsible if they purchase counterfeit products from a retailer at lower prices. A negative product experience with a retailer will also reflect the brand’s reputation. An effective MAP policy that enforces consistent pricing will ensure that customers hunting for the best deals will stick with the most legitimate retailers.

    Read how DataWeave helped Classic Accessories, a leading manufacturer of high-quality accessories detect counterfeits and identify unauthorized sellers.

    c. Ensure price parity across retailers

    Comparing prices has become an essential and common milestone in every consumer’s purchasing journey. It’s imperative that a brand ensures price parity across platforms and stores because substantial pricing variations on different platforms can make customers suspicious of a brand. Consistent pricing across eCommerce platforms ensures brands maintain their identity. MAP policies also allow retailers to maintain profit margins while avoiding price wars.

    d. Combat revenue loss from illegitimate sales

    While most authorized sellers or distributors comply with pricing policies, unauthorized sellers or grey market sellers have no obligation to follow a brand’s MAP pricing infrastructure. Brands can reduce risk with an authorized seller badge on retailer websites. This will help customers to verify authorized retailers and resellers of your products & help safeguard your brand equity online. 

    3. Tips on Implementing MAP policy and Tackling violations

    Enforcing and tackling MAPs comes down to two things: monitoring the market for infringements and then acting on those violations. Here are a few tips for tackling MAP violations:

    price parity
    Implementation of MAP Policy & Tracking Violations

    a. Communicate actively with retailers

    To maintain a positive relationship with retailers and avoid confusion, brands should create proper communication strategies and channels to accompany the launch of the MAP policy. The policy should be easy to understand, but legal advisors are necessary to understand the jargon of the document. Brands can use checklists, videos, and well-briefed brand reps to communicate their policy clearly with retailers.

    b. Reward retailers for compliance

    Retailers who follow MAP guidelines can lose out to platforms that do not follow these pricing guidelines. Non-MAP following platforms undercut the price of products to drive sales and secure higher traffic. In such instances, brands can incentivize MAP following retailers to encourage them to comply with MAP guidelines while not affecting the competitive edge. It can be in the form of laxity of rules during promotion seasons like New Year, Christmas, and Black Friday sales. The laxity of rules for promotional seasons should be used as an exception to the general rule, and outlined in the guidelines.  

    c. Implement an AI-driven MAP monitoring

    When product distribution is spread across the globe through a network of resellers and retailers, keeping a close watch on all platforms for multiple products can become difficult. With the expansion of online marketplaces, manually tracking the pricing of numerous products on multiple platforms is time-consuming and unsustainable. An automated AI-driven monitoring platform can track the pricing of all products sold across hundreds of online platforms and identify violations around the clock. Such platforms can alert brands of violations, price inconsistencies, or suspicious activities in real-time. 

    d. Send cease and desist to MAP violators and unauthorized dealers

    Brands must enforce a MAP policy to ensure price parity among retailers and resellers. Brands must systematically monitor prices across retailers, social media, marketplaces, and price comparison websites. Whenever brands encounter a MAP violation, they should take action by sending a cease and desist letter to unauthorized sellers. For legitimate sellers, brands can notify them and outline the steps that will be taken if they don’t comply. Brands must be consistent in enforcing MAP policy violations, signaling retailers and unauthorized sellers that there will be repercussions for MAP violations. 

    Market Demand
    MAP Policy

    4. Conclusion

    The trend towards online shopping helps businesses to cut overheads, allowing their products to be sold at a significantly reduced price. Although price appears to be the most effective consumer attraction strategy, significantly lowering product prices can devalue products and hurt brand reputation in the long term. However, including and enforcing MAP policies helps brands to manage their reputation and allows retailers to manage their margins. 

    Want to see first-hand how DataWeave can help brands track MAP Violations, Counterfeit products, and identify unauthorized sellers? Sign up for a demo with our Digital Shelf experts to know more.

  • Quick Commerce in 2022: An Era of Hyperlocal Delivery

    Quick Commerce in 2022: An Era of Hyperlocal Delivery

    Busy lifestyles, urbanization, aging populations, and smaller households led to the preference for convenience and efficiency in eCommerce deliveries. However, the Covid-19 pandemic caused a massive shift in customer demand and buying decisions. The modern consumer journey moved from takeaway food to online shopping to quick or same-day deliveries. With evolving digital touchpoints, customers now favor fast deliveries and convenience. 

    According to a 2020 survey by KPMG in the UK, 43% of consumers chose next-day delivery, a 4% increase from last year. Interestingly, 17% of consumers abandoned a brand if they faced a longer delivery. Standard delivery time has shortened from 3 to 4 days and two-day shipping to next-day or same-day delivery. This increasing trend of quick delivery has led to the boom of quick commerce or Q-Commerce. Quick commerce or on-demand delivery refers to retailers that deliver goods in under an hour or as quickly as 10 minutes. The rise of Q-commerce is caused by changing consumer behavior and rising expectations since the pandemic. 

    In this blog, you’ll learn about quick commerce or Q-Commerce and its benefits. You’ll also read about factors to consider for quick commerce and tips to implement this business model. 

    1. What is Quick Commerce?

    on-demand delivery
    On-Demand Delivery

    Quick commerce or on-demand delivery is a set of sales and logistics processes that empowers eCommerce businesses, restaurants, grocery chains, and manufacturers to deliver products in less than 24-hours. A study shows that 41% of consumers are willing to pay for same-day delivery while 24% of customers will pay more to deliver their items within a one- or two-hour window.  

    Changing lifestyles and customer behavior directly impacted the rise of Q-Commerce. The takeaway food industry had used quick commerce for many years. But with Q-Commerce businesses consistently cutting delivery time, quick commerce for instant grocery delivery has become a new trend. For instance, India-based online grocery delivery firm Grofers rebranded to BlinkIt amid rising competition, promising 10-minute instant delivery. 

    2. How quick is Quick Commerce?

    The post-pandemic lifestyle & the rise in the number of small and single-person households has led to an increase in demand for products in small quantities that need to be delivered sooner than later. Sometimes in as little as 10 minutes! This trend is oriented towards specific products such as packed or fresh foods, Groceries, Food delivery, Gifts, Flowers, Medicines to name a few.

    quick delivery service
    Quick Commerce Categories

    Local shops that can reach more customers with less friction have swapped traditional brick-and-mortar warehouses to cater to an urban population. These online Q-Commerce stores can deliver goods from favorite stores and offer a vast choice of products that are available 24/7. However, it requires real-time inventory management, data-driven pricing management, innovative logistics technology, a fantastic rider community, and a proper assortment. 

    3. Factors to consider for Quick Commerce

    q commerce
    Competitive Assortment & Pricing

    a. Assortment

    With growing competition, getting product assortment right isn’t easy for quick commerce businesses, yet it’s critical to their success. To optimize assortment for quick commerce stores, they need to understand how demand differs between demographics and various stores. Since quick delivery involves packed and fresh products, it is even more essential to carry a unique assortment for each store. 

    Data analytics will help Q-Commerce businesses understand which products are repeatedly purchased in every store. It also helps identify high-demand gaps in your competitors’ platforms. Assortment analytics can help distinguish shifts in customer behavior across short- and long-term demands. The key to increasing sales is shaping inventory to match the overlap between market opportunity and consumer interest. With assortment analytics, they can determine the optimal mix of products for their daily inventory. 

    b. Pricing

    Pricing information is readily available on quick commerce businesses, allowing customers to compare prices before making purchase decisions. Before deciding on a product, shoppers actively track the best deals on platforms across various Q-Commerce delivery platforms. According to a survey, 31% of consumers rated price comparisons as the essential aspect of their shopping experience. Understanding price perception can help quick commerce companies to optimize their pricing strategy while remaining competitive. 

    A competitive pricing strategy does not imply that Q-Commerce businesses have to cut prices. Instead, it’s about adjusting prices relative to your competitors but not significantly impacting the bottom line. Competitive pricing provides real-time pricing updates, allowing quick commerce platforms to drive sales by nailing their pricing strategy. 

    c. Delivery Time

    delivery time
    Grocery Delivery Race In India

    Delivery time has become the game-changer in quick commerce, with platforms fighting over shorter delivery times. Unpredictable factors such as specific delivery windows, last-minute customer requests, and traffic congestion can wreak havoc in your planning. Optimizing your delivery time can improve operational efficiency through faster delivery, quick route planning, and driver monitoring. 

    Big eCommerce platforms like Amazon offer same-day or next-day delivery to prime members with no extra fee on minimum order criteria. The only demand of customers who do not worry about discounts or lower wholesale prices is quick delivery. The demand for quick delivery services has led to many global retailers offering same-day delivery to meet those expectations.

    d. Demand Forecasting

    Since quick commerce is a viable solution for certain products, businesses must determine what customers want and when they want it. Q-Commerce businesses can use historical data to predict future sales patterns with demand forecasting. It ensures that Q-Commerce businesses can limit wastages and their inventory can cater to a targeted market. Demand forecasting also helps to replenish stock based on real-time data. Furthermore, companies can identify bottlenecks and points of wastage in the supply chain with a demand-driven system in place.

    4. Benefits of Quick Commerce

    same day delivery
    Q-Commerce Benefits

    a. Competitive USP

    Q-Commerce businesses get new value propositions because customers that need immediate delivery are willing to try new brands and order from new stores. It also allows online Q-Commerce businesses to compete with global marketplaces and brick-and-mortar stores. 

    We at DataWeave have helped quick-service restaurants (QSRs) that are going the Q-Commerce route & selling via food aggregator apps to increase their revenue significantly. Our AI-Powered Food Analytic solutions have helped QSRs diagnose improvement areas, monitor key metrics, and drive 10-15% growth. Our data has helped them understand availability during peak times, monitor product visibility by region, track competitors, and choose suitable banners for promotion. Read more about that here.

    b. Increase margins

    A study from Deloitte suggests that 50% of online shoppers spend extra money to get convenient delivery of the products they need during the pandemic. These customers also paid extra for on-demand fulfillment and bought online pick-up in-store options. 

    Since the assortment of products in quick commerce is relatively small, Q-Commerce businesses can drive sales for their most profitable product lines. There is a potential for greater margins because wealthier demographics often require convenience. For instance, time-stranded professionals value convenience over discounts. 

    c. Customer experience is paramount

    With quick commerce, retailers can meet customer expectations and exceed them, fostering brand loyalty. Quick commerce addresses customer pain points such as running out of food before a small party or getting a birthday present for your friends. It can simply help people who cannot make it to the shop or stock up essentials.

    5. How to implement Quick Commerce

    quick delivery
    Implementation of Quick Commerce

    a. The need for local hubs

    To pack and deliver products in under an hour, businesses must be located close to the customers. Therefore, quick commerce relies on local warehouses that can serve customers in immediate proximity. Since the duration of two-wheelers is less likely to be impacted by heavy traffic or parking spaces, delivery services employ riders to deliver products.

    b. Ensure you have the right analytics in place

    Another essential part of running a quick commerce business is to have a web or phone application that can facilitate online ordering and offer accurate stock information to customers. Q-Commerce businesses also need a real-time inventory management tool that will provide insights into stock levels and allow for quick reordering and redistribution of products. This will also prevent deadstock and stockouts. 

    DataWeave’s Food Delivery Analytics product suite helps companies to increase order volumes, understand inventory, and optimize prices. It also provides access to discounts, offers, delivery charges, inventory, and final cart value across all your competitors. 

    c. It’s all about stock availability & assortment

    Q-Commerce in the Grocery Delivery space is excellent for specific product niches like packed or fresh foods and vegetables, drinks, gifts, cosmetics, and other CPG products that customers use every day.

    The stock assortment is as important in the Food Delivery space with restaurant chains like McDonald’s or Burger King that generate as much as 75% of their sales from online orders. These businesses have to make sure they’re carrying the most in-demand product assortment there is. 

    Conclusion

    same day delivery
    Same Day Delivery

    The rise of quick commerce represents the next big change in eCommerce, accompanied by a shift in consumer behavior towards online grocery shopping and food ordering. When positioned with proper assortment and pricing, instant delivery services can allow Q-Commerce businesses to capture the influx of consumers looking for speedy delivery. By tapping into big data from quick commerce markets, Q-Commerce businesses can gain insights into consumer demands. 

    If you’re a Q-Commerce business in the Food Delivery or Grocery Delivery space, reach out to our experts at DataWeave to learn how our solutions can help you understand the best Pricing Strategy, Delivery Time SLAs, Assortment Mix you need in order to successfully sell on Q-Commerce platforms. 

  • Beauty & Grooming Brands that are dominating on Amazon India

    Beauty & Grooming Brands that are dominating on Amazon India

    Growing awareness of personal hygiene and changing lifestyles has contributed to a significant development of India’s cosmetics, beauty, and personal care products. The Indian cosmetic industry reached a value of USD $26.1 bn in 2020. The major boom in sales is because of rising digitization, social media marketing, and the advent of eCommerce beauty platforms. However, the increase in demand and technological advancements has led to a competitive landscape for Indian and international brands competing for digital and physical channels. As of February 2019, 18.92% of respondents spent between 700 to 1700 rupees, and 43.9% spent up to 700 rupees monthly on cosmetics and personal care products in India.

    Personal care products in India
    Monthly spend on Personal Care Products in India

    Shattering stereotypes and gender norms, India is also seeing a revolution in the male grooming industry, which is expected to reach INR 319.82 bn by 2024. The D2C market is expanding beyond metropolitan cities, and at present both D2C brands and startups have launched over 177 new products for men. “We realized there is an opportunity to create India’s first experiential brand exclusive for men,” says Hitesh Dhingra, Co-founder, The Man Company. He adds ecommerce business has grown almost by 200 percent. In a similar vein, Shantanu Deshpande, founder, and CEO, Bombay Shaving Company, concurs and adds the pandemic boosted online sales. He says that it has become easier for the company to compete with big brands on marketplaces like Amazon and Flipkart.

    With the onset of the pandemic, it has become more and more important for these D2C brands to have a strong digital presence and an even stronger Digital Shelf when selling on platforms like Amazon, Flipkart, Nykaa, and the likes. On these marketplaces, brands need to track critical KPIs like product discoverability, stock status & availability, reviews and ratings, pricing & promotions to make sure they’re optimizing product performance across all online channels to amplify their eCommerce growth. 

    So which beauty and grooming brands and categories have a strong Digital Shelf and are dominating on Amazon? Let’s take a look. 

    Men's Grooming Brands and Categories Categories
    Men’s Grooming Brands and Categories

    Methodology

    • We tracked the first 250 products on Amazon against certain keyword searches specific to India’s Beauty & Grooming space. 
      – Keywords specific to women’s grooming: anti-aging Cream, Face Mask, Paraben-free Shampoo, Onion Hair Oil, Body Wash, Moisturizer
      – Keywords specific to male grooming: Beard Oil, Hair Wax for men, Shaving Cream, After Shave Lotion, Beard Trimmer
    • Share of Search (SoS) – The percentage of products that appeared on the search results page on Amazon belonging to a brand against a specific keyword or category. 
    • Data Scrape time period: From 14th Oct 2021 to 10th Nov 2021

    THE BEAUTY IS IN THE DATA

    On Amazon, brands use sponsored ads to increase visibility and drive more sales. When we looked at the product category with the most aggressive ad spends, products in the men’s grooming category came out on top and had the maximum number of sponsored products. 26% of beard trimmers were sponsored, followed by Beard Wax and Beard Oil at 25%. During the lockdown, more men started searching online for new products and watching instructional videos on how to groom their beards or how to get a salon-like shave at home. Demand for razors and trimmers is up by 50% compared to last year,” said Sidharth S Oberoi, founder and CEO, LetsShave. In contrast, we saw that only 11% of after-shave lotions and 15% shaving creams were discounted. 

    Sponsered Items per Product Category
    Percentage of Sponsered Items per Product Category

    For women, we saw a similar trend. 24% of products in the Paraben-free Shampoos and Onion Oil category was sponsored. In contrast, only 5% of anti-aging creams were sponsored. Additionally, 21% of products in the face mask category and 23% in body wash were sponsored. 

    Competition is fierce in these categories, making an artificial boost necessary for increasing discoverability. In fact, we saw that the competition was the fiercest in the face mask category, which had the highest “1st Page Change Rate.” It is an indicator of how much the results on the 1st page for a particular keyword change from time to time. This reflects higher competition and brands constantly updating their digital shelf KPIs to ensure their products appear on page 1. One of the biggest reasons why brands need to constantly gauge their online visibility is to track their sponsored & organic ranking compared to competitors.

    Driving sales using a smart Discounting Strategy

    Price can play a big role in the final purchase decision. So we looked at two things wrt price across all these beauty & grooming products.

    • Which product Category had the maximum number of products on discount? 
    • … & how large were these discounts? 
    Products on Discount
    Percentage of Products on Discount

    We saw that almost 55% of products in the body wash category & 46% of anti-aging creams were available at a discount. Beard Oil & Onion Hair oil had the least number of products discounted at 29% each.

    Magnitude of Discount
    Magnitude of Discount

    How high were these discounts? Let’s take a look.

    The highest discount was seen in the beard oil and moisturizer category, with an average discount of 17% across all products. The average discount trend across most product categories ranged between 14 to 17%, so we did see some consistency there.

    Digital channels provide transparent insights into pricing & promotions, which is why customers are constantly comparing prices across various brands before making a purchase. This is why it is crucial for brands to remain competitive by tracking & comparing promotional strategies with those of their rivals. 

    To Review or Not to Review?

    Consumers worldwide don’t make a purchase decision without reading online reviews. Online reviews and ratings have become a significant milestone in the modern consumer shopping journey, and eCommerce brands can leverage reviews as valuable sales tools. Given a choice between loyalty programs, discounts, reviews, and free shipping, online shoppers say reviews are the most important factor while making a purchase. Consumers trust user-generated content (UGC) more than product information and videos created by brands.  

    Number of Reviews per Product Category
    Number of Reviews per Product Category

    We looked at product reviews to check consumers of which categories are actively sharing their experience and found that three categories stood out — beard trimmers, moisturizers, and paraben-free shampoo. At the same time, beard oil was the product category with the least number of reviews. 

    Companies can build consumer trust by identifying and acting on negative feedback. But in order to do that, they first need to de-code and understand the collective sentiment behind these reviews. DataWeave’s AI-Powered solutions can help brands break down & analyze online reviews and give them a wealth of insights to enrich their market research as well as create a seamless customer experience.

    UNDERSTANDING THE COMPETITION ON AMAZON

    When selling on Amazon, brands need to make sure shoppers find their products with ease. Keyword searches are the top ways consumers discover and find products across eCommerce sites. We tracked search visibility for the following keywords to see which brands had the highest share of search and appeared on the 1st page on Amazon. 


    Be in any product category – moisturizers, shampoo, anti-aging cream, Mamaearth & WOW featured against most keywords, showing popularity among customers. WOW Skin Science raised $50 million in April 2021, and Mamaearth raised $50 million in July 2021. These two fresh-faced brands have built credibility among health- and environment-conscious users. They are big competitors when it comes to natural and toxin-free products. It’s their high product visibility in multiple categories that is likely leading to better discoverability, higher sales & increased valuation, and brand value. 

    Beauty and Grooming Brands
    Rankings of Top Brands in various cosmetic categories- (A)

    In the male grooming space, we observed that established brands like Nivea, Old Spice, and Park Avenue had a lower share of search than new D2C brands like Beardo, The Man Company, Bombay Shaving Company, and Ustraa. Here’s clear proof of concept that brands need to evolve and adapt their Digital Shelf to selling online if they want to beat the competition. 

    Beauty and Grooming Brands
    Rankings of Top Brands in various cosmetic categories– (B)

    Who were the Amazon Bestsellers?

    Products on Amazon that have the highest sales in their respective categories are called Amazon Bestsellers. The Amazon Bestsellers rank is based on product sales and sales history where the list undergoes an hourly update. The bestseller ranking or bestseller badge is available in the product information section on the product page. The rankings are determined by comparing sales and historical data with products in the same category or subcategory. 

    Brands can make it to Amazon’s bestseller list by optimizing their listings, encouraging reviews, and listing products in the relevance of categories. Although Amazon does not consider reviews for product ranking, they help users convince them to buy your product. 

    Here are the Brands we say that made it to #1 on the Amazon BestSeller List for the following product categories.

    Amazon Bestseller List
    Amazon Bestseller List

    Gillette made it to the top in the aftershave lotion and shaving cream category, while D2C brands Ustraa made its mark bearing number 1 on Amazon Bestseller list for hair wax for men and beard oil. 

    Amazon Bestseller List
    Amazon Bestseller List

    Products from Nivea and L’Oreal made it to #1 seller in 2 categories each. Interestingly, in the Paraben-Free shampoo category, when D2C brands like WoW, Mamaearth have a stronger value proposition, traditional brand L’Oreal had the best-selling product. 

    L’Oreal must’ve pulled various levers and built a robust Digital Shelf to get to the top – from optimizing their content, ensuring product availability, tracking ratings and reviews, and proper competitive pricing. 

    Conclusion

    An increase in new D2C brands in popular and trending categories has led to increasing competition. Unless a brand can position itself in front of the target audience and command their attention right away, another brand can step in and grab the sale. Do you know if your brand is prepped and ready to make an impact on marketplaces like Amazon? Or simply just wondering if your Digital Shelf is optimized with the right price, discounts, reviews, and keywords? Our team at DataWeave can help! Reach out to our Digital Shelf experts to learn more!

  • 2021 Cost-Push Inflationary Trends Ran Rampant, Impacting Holiday Discounts

    2021 Cost-Push Inflationary Trends Ran Rampant, Impacting Holiday Discounts

    Business has been anything but usual this holiday season, especially in the digital retail world. The holiday hustle and bustle historically seen in stores was once again occurring online, but not as anticipated given the current strength of consumer demand and the reemergence of COVID-19 limiting in-store traffic. While ‘Cyber Weekend’, Thanksgiving through Cyber Monday, continues to further its importance to retailers and brands, this year’s performance fell short of expectation due to product shortages and earlier promotions that pulled forward holiday demand.

    Holiday promotions were seen beginning as early as October in order to compete with 2020 Prime Day sales, but discounting, pricing and availability took an opposite direction from usual. This shift influenced our team to get a jump start on our 2021 digital holiday analysis to assess how drastic the changes were versus 2020 activity, and to understand how much of this change has been influenced by inflationary pressures and product scarcity.

    Scarcity Becomes a Reality

    Our initial analysis started by reviewing year-over-year product availability and pricing changes from January through September 2021, leading up to the holiday season, as detailed in our 2021 Cyber Weekend Preliminary Insights blog. We reviewed popular holiday categories like apparel, electronics, and toys, to have a broad sense of notable trends seen consistently throughout various, applicable marketplaces. What we found was a consistent decline in product availability over the last six months compared to last year, alongside an increase in prices.

    Although retailers significantly improved stock availability in November and early December 2021, even digital commerce giants like Amazon and Target were challenged to maintain consistent product availability on their website as seen below. While small in magnitude, there is also a declining trend occurring again closer toward the end of our analysis period, post Cyber Weekend, across all websites included in our analysis.

    Inventory Availability 2021 Holidays
    Source: Commerce Intelligence – Product Availability insights for Home & Garden, Jewelry & Watches, Clothing & Shoes, Bed N Bath, Lighting & Ceiling Fans categories

    Greater Discounts, Higher Prices?

    With inflation at a thirty-nine year high, retailers and manufacturers have realized they can command higher prices without impacting demand as consumers have shown their willingness to pay the price, especially when threatened by product scarcity. Our assessment is that while some products and categories have responded drastically, manufacturers’ suggested retail prices (MSRPs) have increased nearly seven percent on average from January to December 2021. MSRP adjustments are not taken lightly either, as this is an indication increased prices will be part of a longer-term shift in product strategy.

    2021 MoM Retail Inflation Tracker
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com & Target.com each month in 2021 comparing price increases from January 2021 base

    Our 2021 pre-Cyber Weekend analysis reviewed MSRP changes for select categories (Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion) on Amazon and Target.com, and found around forty-eight percent of products on Amazon and thirty-five percent of products on Target.com have increased their MSRPs year-over-year, but kept pre-holiday discount percentages the same.

    Looking more specifically as to what year-over-year changes occurred on Black Friday in 2021, we observed MSRPs increasing across the board for all categories at various magnitudes. This indicates why 2021 discounts appeared to be greater than or equivalent to 2020 for many categories, when in reality consumers paid a higher price than they would have in 2020 for the same items.

    2021 Black Friday MSRP Increases
    Source: Commerce Intelligence – MSRP Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Black Friday November 27th, 2021, versus average MSRP pricing for the same SKU count from November 20-26th 2021

    On Amazon.com, categories like health & beauty have already increase MSRPs by a much greater percentage and magnitude versus Target.com leading up to and during Black Friday 2021, while other categories like furniture have increased MSRPs evenly on average across both retail websites. The below chart cites a few specific examples of year-over-year SKU-level MSRP, promotional price, and discount changes within found within the electronics, furniture, fashion, and health & beauty categories.

    Black Friday 2021 vs. 2020 SKU-level Price Changes
    Source: Commerce Intelligence – MSRP Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Black Friday November 27th, 2021, versus average MSRP pricing for the same SKUs on Black Friday November 26th, 2020.

    Fewer, but Deeper Discounts

    From October through early November 2021, fewer products were discounted compared to this same period in 2020, and the few that were saw much deeper discounts apart from the home improvement category. The most extreme example we saw in discounts offered was within furniture where only three percent of SKUs were on discount in 2021 compared to twenty-six percent in 2020. Interestingly, the magnitude of discount was also higher pre-Cyber Weekend 2021 versus 2020, but this trend was not exclusive to furniture and was also seen within electronics, health & beauty, and home improvement.

    Pre-Black Friday 2021 and 2020 SKUs on Discount and Magnitude
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com & Target.com Pre-Black Friday average selling price during November 20-26th 2021 versus average selling price from November 13-19th 2021 compared to Pre-Black Friday average selling price during November 19-25th 2020 versus average selling price from November 12-18th, 2020.

    Within the furniture category, the subcategories offering the greatest number of SKUs with price decreases on Black Friday 2021 were rugs by a wide margin, followed by cabinets, bed and bath, and entertainment units, but the magnitude of discounts offered were all under twenty percent.

    2021 Black Friday Furniture Category Price Decreases
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com and Target.com on Black Friday November 27th, 2021, versus average pricing for the same SKUs from Pre-Black Friday November 20-26th 2021 and Black Friday November 26th, 2020, versus average pricing for the same SKUs from Pre-Black Friday November 19th-25th 2020

    Accounting for this phenomenon could have been retailers’ attempts to clear inventory for SKUs which hadn’t sold even during the period of severe supply chain shortages. With more products selling at higher prices this year, retailers were also able to use fewer SKUs with greater discounts to attract buyer in hopes of filling their digital baskets with more full-priced goods, helping to protect margins heading in to Cyber Weekend. Scarcity threats also encouraged consumers to buy early, even when not on promotion, to ensure they would have gifts in time for the holidays.

    The same trends seen pre-Cyber Weekend 2021 were also seen on Black Friday with a year-over-year decrease in the percentage of SKUs offered on discount versus 2020, and steeper price reductions for the discounted products which can also be attributed to the increase in MSRPs.

    Black Friday 2021 and 2020 SKUs on Discount and Magnitude
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com and Target.com on Black Friday November 27th, 2021, versus average pricing for the same SKUs from Pre-Black Friday November 20-26th 2021 and Black Friday November 26th, 2020, versus average pricing for the same SKUs from Pre-Black Friday November 19th-25th 2020

    2021 Black Friday Price Increases?

    We all know Black Friday is all about price reductions, discounts and deals and so it’s rare to see actual price increases, yet for Black Friday 2021, trends ran counter to this. We observed price increases across all categories for around thirteen to nineteen percent of SKUs, with an average price increase of around fifteen percent in 2021 versus an average of only two percent in 2020.

    SKUs with Price Increases Black Friday 2021 and 2020
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com and Target.com on Black Friday November 27th, 2021, versus pricing for the same SKUs from Pre-Black Friday November 20-26th 2021 and Black Friday November 26th, 2020, versus average pricing for the same SKUs from Pre-Black Friday November 19th-25th 2020

    At an account level, we noticed a few interesting differences happening on Black Friday 2021 versus 2020 regarding category price changes. On Target.com, almost ninety percent of the bed and bath SKUs analyzed had a price change on Black Friday in 2021 versus 2020 with eighty-two percent presenting a higher price year-over-year versus only around seven percent showing a decrease, where on Amazon nearly forty-four percent of bed and bath SKUs showed an increase in price and around thirty-eight percent showed a decrease. Except for the health and beauty category on Target.com, more than half of the SKUs in each category saw a price increase on Black Friday versus a price decrease.

    2021 YoY Price Changes on Black Friday
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com and Target.com on Black Friday November 27th, 2021, versus average pricing for the same SKUs on Black Friday November 26th, 2020.

    The magnitude of year-over-year price changes seen on Black Friday 2021 was significant across all categories, but the magnitude of price increases found on Amazon.com within the health and beauty category outpaced the rest by far. We reviewed three hundred and sixty-five SKUs on Amazon.com within the health & beauty category and saw almost eighty-three percent of them had a price change with around thirty-one percent decreasing prices and around fifty-two percent increasing prices. This means that within the health & beauty category on Amazon.com, more than fifty percent of the SKUs tracked were sold at a one hundred and seventy-six percent higher price on average during Black Friday 2021 versus 2020.

    Magnitude of Black Friday 2021 Price Increases
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com and Target.com on Black Friday November 27th, 2021, versus average pricing for the same SKUs on Black Friday November 26th, 2020.

    The subcategories offering the greatest number of SKUs with price increases on Black Friday 2021 were cameras, followed by men’s fragrances, laptops, and desktops & accessories, but the magnitude of discounts offered were all under ten percent.

    2021 Subcategories with Price Increases during Black Friday
    Source: Commerce Intelligence – Pricing Insights for Bed & Bath, Electronics, Furniture, Healthy & Beauty, and Fashion categories on Amazon.com and Target.com on Black Friday November 27th, 2021, versus pricing for the same SKUs from Pre-Black Friday November 20-26th 2021 and Black Friday November 26th, 2020, versus average pricing for the same SKUs from Pre-Black Friday November 19th-25th 2020

    The Aftermath Post-2021 Cyber Weekend

    Extending this analysis beyond the holiday weekend, we analyzed price change activity from December third through the ninth across the top US retailers (chart below) and found that price decreases have been very minimal, comparatively speaking. Though there was a spike in number of price decreases from December 8th to the 9th, the percentage of SKUs with price decreases was still very low (less than three percent). We anticipate this trend will continue into 2022.

    SKUs with Price Decrease Post Cyber Weekend 2021
    Source: Commerce Intelligence – Pricing insights for Home & Garden, Jewelry & Watches, Clothing & Shoes, Bed N Bath, Lighting & Ceiling Fans categories

    A Sign of Things to Come

    A confluence of inflationary trends, product shortages and consumer liquidity have driven many marketplace changes to occur simultaneously. Government programs in the form of stimulus checks, have put extra money in consumers’ hands, and so they’ve been more willing to spend. That, coupled with the shock in the supply chain, has motivated people to buy far ahead of the 2021 holiday season. Hence, retailers have needed to rely much less on across-the-board discounts. Promotions have been more strategic – we’ve seen deeper discounts over fewer products, likely used to draw consumers in to buy certain items, and once they’re there, customers are buying everything else at a non-discount level. When these factors once again normalize, we could see a return to the “race to the bottom” that has occurred since the financial crisis of 2008-2009, but for once, retailers may be able to maintain some pricing power as the 2021 holiday shopping season played out.

    Even though performance was not as anticipated and holiday sales did not grow as rapidly as they did in 2020, Cyber Monday was still the greatest online shopping day in 2021. Through it all, retailers managed to keep their digital shelves stocked and orders filled in time for the holidays for the most part, running the risk of housing aged inventory if goods didn’t arrive in time. Despite predictions for steep promotions in January 2022, with supply chains still challenged and inflationary pressures still full steam ahead, we don’t anticipate much in the way of enhanced discounts to continue beyond the holidays.

    Access to these types of real-time digital marketplace insights can enable retailers and brands to make strategic decisions like how and when to address inflationary pressures, while also supporting many other day-to-day operations and help drive profitable growth in an intensifying competitive environment. Continue to follow us in the coming weeks for a detailed 2021 year-end review across more retailers and categories. Be sure to reach out to our Retail Analytics experts for access to more details regarding the above analysis.         

  • Importance of Image Recognition in the Retail Industry

    Importance of Image Recognition in the Retail Industry

    When it comes to classifying and analyzing images, humans can easily recognize distinct features of objects and associate them with individual definitions. However, visual recognition is a highly complex task for machines because it involves identifying multiple objects and finding object relationships. Image recognition has been a long-standing research problem in the computer vision field. But, the recent development in AI has improved the process of object detection, image identification, and image classification. The image recognition market is assumed to rise globally to a market size of $42.2 billion by 2022. Various industries are adopting image recognition technology to improve augmented reality applications, optimize medical imagery, boost driverless car technology, predict consumer behavior, and much more. 

    Although image recognition is a relatively new aspect of analysis, it is also making its way into eCommerce. Image recognition is helping retailers to expand consumer reach, offer insights into trends, and improve customers’ online shopping experience for the eCommerce industry. The Global Image Recognition in Retail Market is estimated to be USD 1.8 Bn in 2021 and is expected to reach USD 4.5 Bn by 2026, growing at a CAGR of 20%.

    Image Recognition
    Global Image Recognition in Retail Market

    In this blog, you’ll learn about image recognition technology and its importance in the retail industry. 

    What is Image Recognition?

    Image recognition, a subcategory of computer vision, is a technology that can identify objects, entities, or attributes in digital images or videos. However, computer vision is a broader term, including methods for gathering, processing, and analyzing data from the real world. Image recognition can be performed at varying degrees of accuracy, depending on the type of information required.

    Image recognition can perform the following tasks:

    Object Detection, Semantic Segmentation & Instance Segmentation
    Object Detection, Semantic Segmentation & Instance Segmentation
    • Classification: It identifies the “class,” i.e., the category to which an image belongs. A picture can have only one class.
    • Tagging: It’s a classification task but involves a higher degree of accuracy. Tagging can recognize several concepts or objects within an image, and there can be more than one tag assigned to a particular image.
    • Detection and localization: This step helps locate object(s) in an image. Once the system locates the object in question, localization helps to place a bounding box around it. 
    • Segmentation: This is also a detection task but involves a higher degree of precision. Segmentation locates element(s) to the nearest pixel in an image. 
    • Instance segmentation: It helps differentiate multiple objects belonging to the same class. 

    Image Recognition in eCommerce and how it works

    Nowadays, increasing competition and customer expectations are forcing online retailers to constantly monitor market dynamics wrt their pricing, promotion & product assortment in order to stay competitive. To get these insights, retailers need to match and compare their products against their competitors to see where the gaps are. That’s where product matching comes in. 

    Product matching refers to finding the same or similar products against a target universe of products from across the web, across multiple competing retailers. Product matching uses AI-based image recognition to determine product attributes, find patterns, and detect text, product price, shipping information, and so on. 

    Here’s how DataWeave’s AI-powered analytics platform uses image recognition & aggregates insights & data for retailers from across the web to provide a comprehensive view of the online competitive environment.

    Image recognition use-cases in the retail industry

    a. Attribute tagging

    Attribute Tagging
    Attribute Tagging

    Getting shoppers to your eCommerce platform is one thing and getting them to complete a purchase is a steeper hill to climb. If your platform can’t provide search results that match with customers’ requirements, they’ll get lost, grow frustrated, and drop off. Attribute tagging with image recognition allows eCommerce stores to automatically generate attributes for all products so customers can quickly find products they are looking for. 

    Tags allow users to filter products based on the categories they want to explore. Product tags include everything the customer might specifically search for — color, type, size, brand, use, design, fabric, discount, etc. For example, a dress could have tags like red, evening, midi, summer, long-sleeve, silk, summer sale, etc. When a user looks for midi dresses or long-sleeve dresses, products with these tags will show up. 

    b. Search by image

    Visual Search
    Visual Search

    Visual Search allows users to look for similar products using a reference image from their camera roll or downloaded from the internet. The visual search feature also enables eCommerce businesses to implement image-based search into their software applications. It maximizes the searchable potential of their visual data. 

    Meanwhile, Gartner predicts a 30% increase in digital commerce revenue by 2021 for companies who start supporting visual and voice search on their websites and apps. The benefits of visual search include more personalized, easy product recommendations and enhanced product discovery.

    c. Fashion trend analysis

    similarity matching
    Similarity Matching

    Tapping into trending product categories is a goldmine for any eCommerce business. Having insights into trending categories and products means less competition on search engines, fewer ads, and intelligent pricing. All of which can boost any retailer’s margins. Image recognition technology provides information about colors, styling techniques, fabric textures, prints, and more to spark consumer demand. It works by scanning social media images to pinpoint trending attributes and predict fashion trends. For instance, while scanning images, technology understands that it’s seeing a photo of a color-blocked sweatshirt because it recognizes the product has a hooded neck, full sleeves, blocks of different colors, and even the type of fabric. This technology can analyze millions of images, helping retailers analyze the volume of color-blocked sweatshirts. 

    We do this seamlessly at DataWeave. Our similarity matching solution helps retailers gather insights into attributes for products similar to the ones they’re carrying on their site. Similarity matching helps retailers gain visibility into their entire competitive landscape to keep their e-commerce strategy responsive to price & product assortment shifts among consumers and rivals

    d. Augmented reality

    According to Statista, the AR market is valued at $9.5 billion, with around 810 million active mobile users. Since shoppers want the full sensory product experience before shopping online, augmented reality (AR) can help them understand what they’re buying and how the product will work for them. There are AR applications for trying makeup, clothing, accessories, and even eyeglasses. IKEA was one of the pioneers in using AR for eCommerce retail. In 2017, IKEA launched the Place app, allowing shoppers to see how thousands of items will look in their homes, with 98% accuracy. 

    Image recognition helps AR applications anchor virtual content with the real world. For instance, Sephora has a Virtual Artist that allows users to try different makeup looks and even take pictures of an outfit they’re planning to wear to match the shade. Users can even check out full-face looks and learn how to do their makeup with virtual tutorials. 

    e. Counterfeit Detection

    Counterfeit Detection
    Counterfeit Detection

    Another application of image recognition that has proven to be very successful is counterfeit product detection. It has become increasingly difficult for brands and retailers to find and eliminate fake items on eCommerce sites. U.S. Customs seized over 13,500 counterfeit goods worth $30 Million in November 2021, indicating how brands and online marketplaces have struggled in the past to find an effective solution. 

    Essentially, image recognition technology allows eCommerce sites to detect products with fake logos and designs attempting to sell as legitimate brands by capturing discrepancies in images and content. The system flags and delists the products and sellers when a fake is detected.

    Here’s how DataWeave helped Classic Accessories, a leading manufacturer of high-quality covers, furnishings, and accessories automate their counterfeit detection process using our super Image Recognition capabilities. 

    f. User-generated content analysis

    Visual content plays a vital role in eCommerce sites, especially when it comes to product photos and videos. Today, branded visual content isn’t as effective as it’s one-dimensional. As a matter of fact, 93% of marketers agree that customers trust user-generated content more than content produced by brands. However, user-generated content that features product images or videos is way more exciting, realistic, and creative. It gives customers an appealing view of products being used in real life. 

    The most common form of UGC, i.e., reviews and ratings, have been the key for eCommerce brands as they are quantitative and qualitative metrics about a product/service quality, worth, value, reliability, etc. With image recognition, retailers can access insights into strengths and gaps in all product offerings by understanding what consumers are saying about them. 

    Here’s how DataWeave can help retailers and brands analyze consumer reviews & help them adapt to customer needs.

    Conclusion

    Because of its massive influence, image recognition technology is becoming widely adopted by eCommerce companies. It benefits both retailers and customers. Image recognition based on deep learning can provide retailers with helpful capacities like customer analytics, counterfeit detection, personalized searches, and more. Retailers can also use the data gathered from image recognition eCommerce technology to design effective marketing campaigns and improve their ROI.

    With super sharp image recognition capabilities, DataWeave offers 90% accuracy in matching eCommerce products, allowing us to provide comprehensive and precise insights into pricing and assortments. Sign up for a demo with our team to know more.

  • 6 Promotional Strategies for the Holiday Season

    6 Promotional Strategies for the Holiday Season

    For eCommerce companies, holidays are the busiest season of the year. Whether creating brand awareness with your marketing campaigns or freshening up your landing pages or finding new ways to segment & understand your customers, the list of tasks seems endless. It’s the time of the year when most people look forward to shopping for friends and family. 

    The holiday shopping season begins with Black Friday and Cyber Monday and leads to the December holidays, including Christmas and New Year. Consequently, proper planning and marketing are essential for a successful holiday season. 

    In fact, holiday sales during November and December are forecasted to be between $843.4B – $859B, up 10.5% over 2020, according to the National Retail Federation (NRF). For online stores specifically, sales are predicted to increase between 11% – 15% to a total of between $218.3B and $226.2B driven by online purchases.

    This guide will share eight promotional strategies retailers can use during the holiday season. We will also discuss how data analytics can help retailers improve their promotional strategies. 

    Using data analytics to guide promotional strategies

    Promotional Strategies
    Promotional Strategies

    Data is the foundation of every successful marketing campaign. Data analysis helps companies understand which graphics worked well and campaigns that generated the most revenue. Gathering data and running analysis helps companies improve their next marketing campaign. Retailers can also get deeper insights into campaigns/channels with the highest conversion rate or average order value (AOV).

    With data analytics, retailers can prioritize campaigns and channels that resonate the most with their customers this holiday season. But, it would be best to try more than one promotional strategy to ensure you double down on what works without placing all of your eggs in one Christmas-themed basket. 

    Here are four ways that data analytics can help guide promotional strategies:

    a. Customized alerts for listing pages

    Data analysis helps retailers determine if certain products are out of stock on their rival’s website and adjust their own pricing accordingly. It allows retailers to grab market share for trending items. For example, if you get an out-of-stock alert for a particular product at competitors’ stores, you can invest more in advertising that product on your online store. In addition, customized alerts keep retailers informed about their inventory status, allowing them to plan promotions and ads. They can see which products are becoming commoditized due to intense competition and which ones offer better revenue opportunities. 

    Learn how DataWeave can help retailers track their competitor’s stock and inventory status.

    b. Maximize conversions by tracking product trends

    Assortment Analytics
    Assortment Analytics

    Customers are always looking for products that are currently trending. With assortment analytics, eCommerce companies can get insights into hot trends, allowing them to stock in-demand categories and products. Integrating assortment analytics with AI-powered image analytics can also provide insights into attributes that are popular among customers. By filling gaps in their current assortments, retailers can improve conversion rates and increase revenue. 

    Here’s a case study on how DataWeave helped Douglas, a luxury beauty retailer in Germany boost sales by building an in-demand product assortment 

    c. Monitor competitor promotions

    Promotional Insights
    Promotional Insights

    With increased competition and consumer demand for deals, it has become important for retailers to monitor their competitor’s promotions. Monitoring promotions helps retailers to optimize their ad spend accordingly. AI-powered image analysis tools can capture important information from competitors’ ad banners and deliver insights into metrics that are working to deliver sales. 

    Here’s how DataWeave can help retailers make their marketing magnetic with competitive promotional insights! 

    d. Optimize margins with a data-driven pricing strategy 

    Pricing Intelligence
    Pricing Intelligence

    It has become challenging to price products in recent years since digital tools enable price transparency across channels. Although this trend is excellent for consumers, it makes competition fierce for retailers. A data-driven pricing strategy incorporates a variety of factors, including industry needs, competitor analysis, consumer demand, production costs, and profit margins. 

    With data-driven competitive pricing, retailers can keep pace with the changing eCommerce environment with real-time pricing updates. It also helps them optimize margins and quickly respond to changes in prices on rival stores. 

    Promotional Strategies for the Holiday Season

    a. Virtual Webrooms

    When customers want to see a product in-person, they go to a store showroom. It helps them make a purchase decision. However, with the Internet, eCommerce companies can bring this tactic online. The only difference between showrooming and webrooming is that the former takes in-person, whereas the latter happens digitally. Webrooming grew in popularity during the COVID-19 pandemic. Instead of spending weekends browsing stores, consumers took to the Internet for most of their product research.

    A webroom allows customers to explore products from every angle, providing them with the complete in-person showroom experience online. Webrooming is a powerful holiday marketing strategy, especially regarding expensive purchases. Customers prefer to understand how the product will look. However, building a webroom is extensive and requires retailers to hire developers and professional photographers.

    Webrooms allow retailers to share their collections, schedule virtual appointments, share 3D product images, set up virtual fitting rooms for clothing products, and accept purchase orders. For example, in 2015, Tommy Hilfiger launched its first digital showroom in Amsterdam to improve sustainability and minimize its carbon footprint. Through remote wholesale selling and digital product creation, a digital showroom helped Tommy Hilfiger transform the buying journey and retail value chain.

    b. Loyalty-rewarding sales and perks

    Loyalty Rewarding
    Customer Loyalty

    Consider building customer loyalty during your holiday promotions. First, encourage your holiday shoppers to become loyal customers by offering bonus rewards, contests, or giveaways when they sign up for your loyalty program. You can encourage them to purchase right away by providing instant discount coupons or points for a reward to redeem on their next purchase. For maximum impact, you should run this promotion throughout the holiday season. 

    Second, you should attract your current loyalty program members with discount codes. Offer free shipping or provide a one-day-only discount code to ensure your customers choose you during their last-minute purchases. With these rewards, you’ll attract customers who are window shopping and simultaneously bring your loyal customers back throughout the holiday season.

    c. Charitable Tie-Ins

    AmazonSmile
    AmazonSmile

    Research shows that customers are four times more likely to purchase from brands with a strong sense of purpose. With the festive season being the time of giving, working with a charity and giving back to your community is a great way to reach out to customers. 

    After a tough one and half years because of the pandemic, people want to give back and help those in need this holiday season. You can partner with a non-profit and run campaigns that allow customers to give back. It’s also great for sharing your brand mission with your customers. For instance, Amazon allows customers to shop from AmazonSmile, which donates 0.5% of their eligible Charity List purchases to a selected charity, at no extra cost to the customers. 

    Consider partnering with an organization within your industry. For example, you can pair up with a non-profit that collects and gives clothes to the needy if you sell clothes. You can involve customers by asking them to exchange old dresses for coupons or cash discounts. 

    d. Omni-channel customer experience

    Omni-channel marketing provides customers with a seamless, consistent, and cohesive experience over multiple marketing channels. Omnichannel marketing aims to provide a meaningful and cohesive experience that inspires your customers to make a purchase. Unlike multichannel marketing, this strategy puts the customer at the center of marketing campaigns and elevates the cross-channel customer experience. 

    Omnichannel shoppers spend 10% more money and purchase 15% more items than the original shoppers. eCommerce companies can use historical data to analyze successful channels and create a more transparent marketing strategy for the holiday season. Omnichannel analytics will provide a holistic picture of customer data that will help retailers to better meet the customer’s requirements and predict inventory. 

    e. Buy now, pay later (BNPL)

    Buy Now Pay Later
    Buy Now Pay Later (BNPL)

    Technically, buy now, pay later isn’t a promotional idea since your customers will still be paying the full price. However, BNPL allows them to delay their payments and not pay in full right away at checkout. Buy now, pay later needs to be on every eCommerce company’s holiday promotions plans. Various retailers, including Walmart, offer affordable monthly payments at the pace of 3 to 24 months with Affirm. Target also has a similar scheme with Sezzle and Affirm. Whereas Sephora and Macy’s offer 4 interest-free payments with Klarna.

    BNPL is especially popular with millennials and Gen Z shoppers and will factor into their 2021 holiday shopping plans. Research showed 62% growth in the use of buy now, pay later service in consumers aged 18 to 24. Giving customers a means to manage their budgets during holidays while still taking home their purchases will attract more customers. While the customer doesn’t pay the full price right away for their purchase, businesses still get the total worth of the item. In the eCommerce industry—nearly 50% of BNPL users say they use it while shopping online, and among them, 45% use the service frequently.

    f. Buy One, Get One

    The last promotional idea is a classic buy one, get one offer. Everyone likes a good BOGO promotional offer. In fact, 66% of shoppers from a survey preferred BOGO over other promotions. It’s a win-win promotional strategy for retailers and customers. With this offer, people shop and stock up on gifts for their friends and family, while retailers make a more significant profit than 50% off sales. People prefer to get 100% off on a product over 50% on two items. 

    BOGO sales are best to move inventory by giving shoppers a deal they can’t pass up. If you have stocked up extra items during Black Friday, you can move those last-minute gifts as end-of-year BOGO sales, making room for new merchandise in January.

    Conclusion

    In this post, you saw that there’s more to holiday marketing than a few social media posts. eCommerce companies can use these holiday promotional ideas to offer Loyalty-rewarding sales and perks, buy now pay later service, and an omnichannel customer experience. Regardless of which strategies you’re using, remember that historical data analytics and early planning will play a significant role in increasing your sales and revenue. 

    Proper planning backed by insights into key metrics will help your team develop a one-of-a-kind holiday marketing strategy to drive your holiday sales upward. From sharing gratitude to offering personalized experiences, retailers have various options for promoting business this holiday season.

    Learn how DataWeave can help make sense of your and your competitor’s pricing, promotional, and assortment data this holiday season. Sign up for a demo with our team to know more.

  • Are Your Digital Shelves Prepared for Green Monday?

    Are Your Digital Shelves Prepared for Green Monday?

    Traditionally, retailers have staged multiple promotions between Black Friday and before Christmas Day to keep consumers excited about holiday shopping, so it’s easy to see why one more promotional day might fall into relative obscurity. As if ‘Early Start’ offers to Black Friday and extended ‘Cyber Weekend’ promotions weren’t enough to plan for, eBay added another day into the mix called ‘Green Monday’, much to the benefit of consumers, as it furthers the window of opportunity to secure a bargain during the holiday season. 

    Green Monday falls on the second Monday of December and has historically been one of the greatest sales days of the year for eBay, often attracting last-minute shoppers or those searching for last-minute deals. However, because of the 2021 Global Shipping Crisis, there is speculation that Green Monday may be the last chance this year to have items delivered in time for Christmas. For this reason, we believe it could turn into quite a fruitful event for participating retailers if it encourages procrastinating shoppers that traditionally spend closer to December 25th to buy earlier in the season.

    This isn’t the first year retailers outside of eBay have offered Green Monday promotions, however. Our team has been actively monitoring activity on this day from 2017 through present, to not only assess which retailers participate in the event, but also to understand how the discounts may change surrounding the event. The categories monitored include Apparel (Clothing, Shoes & Jewelry), Bed and Bath, and Home and Garden, and we’ve identified products offered on discount by comparing each applicable product’s price on Green Monday versus the most commonly seen price for the product offered throughout the month of December.

    Better Promotions Than Boxing Day

    Taking a closer look at 2020 Green Monday discounts within the categories and retailers analyzed, apart from Wayfair.com, we see all offered more SKUs on discount on Green Monday versus the days leading up to and out of the event. Kohls.com led the pack with around 93% of SKUs offered on discount, followed by Macys.com with 95%, and Wayfair.com with 83%. Overall, the number of SKUs on discount on Green Monday were greater than the SKUs offered on discount on Boxing Day, which is traditionally known as a great day to bargain shop.

    Source: DataWeave Commerce Intelligence – Promotional Insights tracking Apparel, Bed & Bath, and Home & Garden category product’s online price on Green Monday 2020 in the US versus regular prices for the same products in the month of December each year.

    What’s in Store for Green Monday 2021?

    The insights we’ve tracked over the last four years have not indicated any signs to an end for Green Monday any time soon. As we see it, for consumers it is an extremely convenient time to order holiday gifts, and for retailers it is a good time to build brand trust and loyalty by fulfilling last minute orders at a great value, in time for the holidays.

    Our prediction for the categories analyzed is to expect to see more retailers participate in Green Monday 2021 to a greater degree (more SKUs on sale and enhanced promotions). For retailers in this analysis, we would anticipate HomeDepot.com to enhance the number of offers to match 2020 competitive activity, and for Wayfair.com to look at increasing the number of offers on Green Monday versus the period leading into the event.

    If you are interested in learning more about the details behind this analysis or our Promotional Insights solution, be sure to contact us. We can help you evaluate the effectiveness of your holiday promotional spend with access to near real-time marketplace insights on the brands, categories, and products your rivals promote, including discounts, campaign frequency and duration and more.

  • Manage Your Supply Chain Like a Pro

    Manage Your Supply Chain Like a Pro

    To make faster, seamless deliveries possible, brands need to tighten their supply chain. The pandemic has put a lot of stress on the global supply chain. The supply shock that began in China in February and the demand shock that followed as the global economy shut down uncovered weaknesses in production strategies and supply chains. Temporary trade restrictions and shortages of pharmaceuticals, critical medical supplies, and other products, further added to the problem. 

    As a consequence of all this, brands have to reduce or even eliminate their dependence on sources that are perceived as risky and rethink their use of lean manufacturing strategies that involve minimizing the amount of inventory held in their global supply chains. In the post-pandemic world, the supply chain will take center stage, and managing it efficiently with technical support is going to be what gives one brand an upper hand over the others.

    1. Micro fulfillment is emerging as the need of the hour

    Micro fulfillment
    Emerging Micro Fulfillment

    Retailers are now faced with unprecedented omnichannel fulfillment complexities. Not only do customers expect faster order fulfillment and delivery, but they’re also opting to ‘buy online and pick up in-store (BOPIS)’ or ‘click-and-collect’. Amazon has spent billions of dollars on building its shipping infrastructure, including its existing operating 175+ fulfillment centers across the world and investing nearly $1.5 Bn to build an air hub in the US. Walmart, on the other hand, is relying on its existing footprint across 5000+ US stores to help deliver online orders faster.

    All this is hinting towards micro-fulfillment emerging as a strategy retailers are using to make the fulfillment process more efficient and their supply chain more ready — from receiving an online order to packing it and offering last-mile delivery. This approach will certainly work towards imparting speed to localized, in-store pick-up and combine it with the efficiency of large, automated warehouses. Delivery speed and costs are more important than ever to retain customers and foster brand loyalty. In fact, this will become a big differentiator for grocery e-commerce as the number of people making online grocery purchases has increased drastically the world over and a recent report indicated that in the US, 46% of people use online delivery more now than before the COVID crisis, and 40% use online pickup more.

    2. Use big data to tie-in loose nodes

    The landscape of supply

    Supply chain management is held at the heart of every successful e-commerce company. Supply Chain efficiency always ensures that the right product reaches the right place at the right time. It ensures cost reduction and enhancement of cash utilization. That is why it is important to stay alert and tie-in all loose ends in the supply chain architecture. Big data can come in handy here and it is that quantitative method and structure that can be used to improve decision-making for all activities across the supply chain. While the role of big data is extremely exhaustive and full-pronged across the entire supply chain design, it is important to understand it in theory in a simplified way so that brands can incorporate it to make their backend operations seamless.

    Big data is all about real-time analytics and it primarily does two very important things in making supply chain management easy

    • It expands the dataset for analysis beyond the traditional internal data held on Enterprise Resource Planning (ERP) and supply chain management (SCM) systems. 
    • Big data apply powerful statistical methods to both new and existing data sources. This helps give structure to new insights. This in turn allows forecasting and helps improve supply chain decision-making capabilities for your brand, all the way from the improvement of front-line operations, to strategic choices such as the selection of the right supply chain operating models.

    3. Improve ROI by introducing automation to the mix

    Introducing automation
    Introducing Automation to Improve ROI

    Introducing automation will help take care of tasks usually done manually, such as placing orders, processing changes, data entry, and much more. This frees up time and cuts down on human errors leading to error-free, faster processes. Adidas for instance has been able to reduce 60% of its operational supply chain costs just by switching to end-to-end automation. The largest sportswear manufacturer used automation across 400 factories by bringing in standardized, reusable processes to deliver the best results in a cost-effective way across the supply chain, marketing, finance, retail, and eCommerce. On the supply chain part, with automation, the brand was able to globally attend to supply chain service desk management, vendor onboarding, PO change management, Contract form approval, product data verification, and other such tasks in real-time. This highly successful initiative helped the brand save a lot of time, it earlier lost in manually attending to internal processes and reduced the time to market for Adidas by two-thirds. Moreover, automating systems helps cut down slacks and in return allows the supply chain to stay agile and alert for any unforeseen situations. This readiness further boosts the framework towards growth. 

    4. Eye the future and introduce robotics

    Introduce Robotics
    Robotics is the next big thing in Future

    Autonomous technology is not the next big thing of the future but is the most important thing at present defining the face of the supply chain. Autonomous robots are expected to see strong growth over the next five years. In fact, according to the Boston Consulting Group (BCG), the global robotics market is estimated to reach USD 87 Billion by 2025. It is believed that more than half of this will be allocated for the retail market. In fact, it is not uncommon to find giant beetle-like robots moving around busily with vertical shelves stacked on them inside Amazon’s warehouse in southern New Jersey, US. Tesco for instance uses Radio Frequency Identification (RFID) robots who are used to scan inventories for entire stores in just an hour (as against seven hours for a store employee) with far fewer errors. 

    Even though every word of this sounds too futuristic to be believable, this is the reality for now and retailers are beginning to realize that innovation must set in holistically and extend far beyond just the warehouse or supply chain. Autonomous mobile robots (AMRs) are fast becoming commonplace in warehouses, helping warehouse workers to fulfill orders quickly and efficiently. There are a few different types of robots that companies are considering, and each has its own unique set of advantages. AMRs in totality enable workers to be more productive due to constant collaboration and promote agility, cutting down on slacks and errors. 

    A cohesive and well-defined supply chain where you can leave enough room for tweaks in the future owing to evolving trends will surely help you gain an edge over your competitors through the entire lifecycle of your product. Getting a grip over the supply chain is necessary now as, by 2025, many supply chains may shift from global flows of goods and services to national, regional, and local networks of buyers and suppliers. So, integrating the supply chain keeping an eye on the global and local is the real deal!

  • How Brands Boost Sales & Satisfaction on Walmart.com

    How Brands Boost Sales & Satisfaction on Walmart.com

    The explosive growth of online shopping has forced brands to re-examine their e-commerce processes to stay competitive and profitable. In particular, out-of-stocks are a common, costly retail challenge, as product shortages frustrate online shoppers – and even prompt them to leave brands.

    According to McKinsey & Company, forty-eight percent of consumers switched to a different brand in 2020 because those products were in stock. Among these consumers, seventy-three percent plan to keep using the new brands, linking product availability gaps to the erosion of sales and loyalty. Conversely, brands with effective inventory planning and replenishment can keep items in stock, drive sales and improve the customer experience.

    Retailers like Walmart, collaborating with these brands to meet customer demand, are still facing inventory challenges but, as noted in 2021 Q3 earnings, inventory was up almost twelve percent year-over-year as they worked to stay ahead of increased holiday demand. They have also adjusted in-store operations to accommodate ever-growing e-commerce demands, especially within grocery-centric categories, as digital grocery buyers now amount to more than half the U.S. population.

    Maximizing Conversions with Category Insights

    Walmart’s dot-com strategy is paying off in spades, considering they surpassed Amazon as the leading U.S. grocery e-commerce retailer in 2020 and grew another forty-one percent in Q3, 2021. Our team has been actively tracking digital shelf analytic KPIs on Walmart.com to identify inventory and promotional performance improvement opportunities at a category level to support brands in capitalizing on these digital growth opportunities.

    The latest analysis is summarized below, reviewing average category availability and discount trends occurring each week of the month, from May to August 2021, at a category level. A recent report found the 29th of each month to be the busiest day for online sales because consumers often get paid at the end of the month, which made DataWeave analysts wonder:

    • Which categories are maximizing their growth potential on Walmart.com and where are the greatest opportunities for improvement during periods of increased demand?
    • How do increased demand periods (like payday) impact category online availability?
    • Are category promotions offered at the right times throughout the month to best support demand?

    When Seasonal Demand for Groceries and Payday Merge

    Across all Walmart.com food categories tracked, Week 5 – where payday commonly falls for most consumers, had the lowest average product availability, while Week 4 had the highest average product availability for all categories except Deli and Fruits and Vegetables. These findings may inspire Walmart’s brand partners to rethink their inventory and assortment planning, replenishment and even pricing efforts to maintain a healthy stock closer toward the end of the month to match higher demand.

    The categories with the greatest difference in average availability during Week 5 versus the rest of the month were Snacks & Candy, Beverages and Alcohol, indicating consumers consistently made these types of purchases closest to payday, when income was highest throughout the month. Seasonality is a secondary factor that influenced demand for these items given events like Memorial Day, Fourth of July, Summer Break, and Back-to-School shopping all took place during our analysis. Additionally, most holidays overlapped payday, which also furthered Week 5 demand.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average availability percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    Coupling availability with discounts allows us to consider whether consumers buy more in Week 5 due to high discounts or increased purchasing power, or both. In reviewing the average category discounts offered within the same grocery-centric categories analyzed above, we found almost every grocery category showed a higher discount in Week 5 compared to the rest of the month, except for Bread & Bakery and Alcohol.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average discount percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    Regarding Alcohol, during Week 4, when average availability was the highest, the average discounts offered were the lowest. This can indicate inventory was primed for payday shoppers (and the holidays of course). Bread & Bakery offers the greatest average discounts when inventory levels are lowest on average, indicating Week 3 is a great time to stock up, while Week 4 might be a great time to buy the freshest inventory.

    The greatest average discounts in Week 5 were in Snacks & Candy, Pantry and Fruits & Vegetables. Deeper discounts for Snacks & Candy in Week 5 may have helped brands compete for consumers’ disposable income despite being a discretionary category. Pantry brands’ discounts may have reflected a need to compete for shoppers’ attention. During this period, consumers were out of the house more and less likely to use these grocery staples compared to earlier lockdown periods and cooler months.

    Making Specialty Categories and Health a Priority for Online Shoppers

    Interestingly, the only two categories where inventory was higher in Week 5 versus all other weeks each month were ‘Special Diets’ foods and ‘Summer Flavors’, although ‘Special Diets’ foods consistently maintained the lowest level of average availability each week across all food categories analyzed. This consistent lack of inventory could indicate a great opportunity for brands to increase inventory for dietary products sold on Walmart.com.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average availability percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    The average availability for ‘Summer Flavors’ foods verifies brands are maintaining a solid replenishment strategy for these seasonal items, and a high likelihood consumers will happily find what they need to plan their Summer gatherings on Walmart.com. One alarming factor we found was the change in average discounts offered during Week 5 versus Weeks 1 through 4, indicating promotions surrounding payday may be driving sales volume versus organic demand.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average discount percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    Digital Growth Opportunity in Meal Kits and Kids’ Meals

    Two categories primed for growth, according to Statista, are meal kits and kids’ food and beverages. Their research indicates retail sales for kids’ food has grown steadily year-over-year since 2013, and a recent report also indicates meal kit sales are expected to more than double 2017 sales in 2022, reaching $11.6 billion in the U.S., spurred by pandemic-induced demand. A concerning find in our research indicates both categories, ‘Easy Meal Solutions’ and ‘Kid Friendly Foods’ on Walmart.com, showed great volatility when it comes to in-stock availability. For example, in Week 1, ‘Easy Meal Solutions’ had an average availability nearly half the average of the rest of the month (around nineteen percent versus nearly thirty-eight percent), and in Week 5, payday week, ‘Kid Friendly Foods’ saw the biggest drop in average availability compared to Weeks 1 through 4 (over sixty-seven percent versus seventy-five percent) indicating supply may not be keeping up with the heightened demand.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average availability percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    The heightened average discounts offered during Week 5 for ‘Baby’ and ‘Pets’ items indicate two categories consumers will most likely stock up on during payday.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average discount percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    Back to School Stock-Outs

    U.S. retail sales unexpectedly increased in August, likely boosted by back-to-school shopping and child tax credit payments. Meanwhile, product shortages and other supply chain issues slowed 2021’s back-to-school sales, possibly affecting school supplies’ and clothing availability on Walmart.com. According to our analysis, the average product availability in Walmart.com’s school supplies category fell from over sixty-two percent during Weeks 1 through 4 to nearly forty-two percent in Week 5.

    Warmer weather, seasonal events, reduced lockdowns, and vaccination efforts led more Americans to resume in-person socializing, giving reason to update their spring and summer wardrobes. In July, Forbes shared that three-quarters of shoppers are purchasing apparel, accessories and shoes the most. On average, only around sixty-three percent of clothing items were available on Walmart.com during Weeks 1 through 4. However, in Week 5, that figure plummeted to just over thirty-eight percent, the most significant drop among all categories.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average availability percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    Demand for new fashion remained high throughout this period, seemingly fueled organically, as only moderate additional discounts took place in Week 5, and although the average discount on school supplies was only around twenty-seven percent during Weeks 1 through 4, it surged to just over forty-seven percent in Week 5. Generous additional discounts in Week 5 may have inspired online shoppers to shift spending from clothing to school supplies in late July and August ahead of students’ return to the classroom.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average discount percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    Prioritizing Product Availability with Digital Advertising Strategies

    Seventy-eight percent of B2C marketers increased their 2021 digital advertising spend to fuel online product discoverability (Share of Search), and sales and market share, but out-of-stock experiences simultaneously surged 172% this year from pre-pandemic levels. Paying for ads that drive traffic to your out-of-stock products can be as detrimental to your brand as a bad user experience. Our review of the ‘Featured Products’ sold on Walmart.com show consistent, low-levels of product availability each week throughout the months reviewed.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average availability percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    Additionally, the average discount offered on these products tended to be higher than most other categories reviewed, indicating brands participating in the featured product section of the website were not only investing in digital ads, but also doubling down with promotional activity as well.

    Source: DataWeave Digital Shelf Analytics for Brands – Category average discount percentages from May to August 2021 between Week 1 (the 1st to the 7th day of the month) and Week 5 (the 29th, 30th and 31st day of the month).

    How Brands can Replenish Their Digital Shelf

    It is well known just how important it is to have products available during the right time of day, week, month, or season to improve customer satisfaction rates, but with your e-commerce store open 24/7 and omnichannel fulfillment strategies in place, it drastically changes the way in which strategic execution is prioritized for a retailer to reduce basket abandonment and for brands to build loyalty.

    Our greatest takeaway from this analysis is realizing how crucial it is for brands to proactively track product availability and competitive pricing insights to stay ahead of the curve and achieve their digital growth goals. Early visibility to stock replenishment could help brands align with heightened cyclical and seasonal demand to avoid out-of-stocks and grow e-commerce sales.

    This is why more leading brands now rely on our Digital Shelf Analytics solutions, including Pricing and Availability insights, to keep eCommerce planning agile, to maximize online conversions, and ultimately maintain shopper satisfaction and loyalty.

  • Top 7 AI tools for your eCommerce business

    Top 7 AI tools for your eCommerce business

    The 2020 global health crisis sped up the adoption of omnichannel shopping and fulfillment. Consumers spent $791.70 billion online with U.S. merchants in 2020, a 32.4% rise compared to 2019. To keep up with this digital shift, offline businesses have substantially moved investments to online infrastructures for everything from e-commerce platforms, product recommendations, inventory management, and communications. AI tools for eCommerce have played a major role in helping businesses in the digital shift. 

    However, the benefits of setting up e-commerce stores are potentially outweighed by the increased costs. As markets transition to online retailers, they must learn to efficiently collect, secure, and analyze data coming in from multiple sources. Strategically approaching the data problem with artificial intelligence (AI) can help better serve customers, gain a competitive advantage, and drive loyalty.

    In this blog, you will learn about seven data and AI tools for eCommerce businesses:

    Seven data and AI tools for eCommerce businesses
    Seven Data and AI tools for eCommerce businesses

    1. Data Warehouse

    Data is the one advantage that eCommerce merchants and marketers have over brick and mortar retailers. When buyers are from the internet, eCommerce retailers can collect data and measure almost every aspect of their interactions. However, that advantage is worthless unless there is a system to make sense of the data they collect. Companies assume that they have a sound system in place. But, what they have is a network of silos. In such a system, data sticks to different platforms like Google Analytics, Shopify, or Klaviyo and can’t move to deliver valuable insights. Funneling all your data into a single location for your eCommerce stores is the right way to go. Data warehouses centralize and merge a plethora of data from various sources, helping organizations to derive valuable business insights and improve decision-making. 

    Data Warehouses support real-time analytics and ML operations quickly & are designed to enable and support business intelligence (BI) activities like performing queries and analysis on a colossal amount of data. Data could range from customer-related data, product or pricing data, or even competitor data. 

    However, the time needed to gather, clean, and upload the data to the warehouse is a time-consuming process. Here’s where DataWeave’s AI-Powered Data Aggregation & Analysis Platform can help! Get critical insights on your competitor’s pricing, assortment, and historical sale trends with a real-time dashboard. Build a winning eCommerce strategy with market intelligence without the need to store your data. 

    2. Data Lake

    Data Lake

    A data lake is a centralized repository that can store structured and unstructured data at any scale. Companies don’t have to provide a schema to the data before storing it, but they still can run different analytics and ML-related operations. However, it takes more time to refine the raw data and then analyze or create ML models for predictions. 

    An Aberdeen survey saw businesses implementing a Data Lake outperforming similar companies by 9% in organic revenue growth. The organizations that implemented Data Lake could perform various analytics over additional data from social media, click-streams, websites, etc. A Data Lake allows for the democratization of data and the versatility of storing multi-structured data from diverse sources, improving insights and business growth. 

    eCommerce businesses can collect competitors’ data in data lakes like their popular products, categories, landing pages, and ads. Analyzing competitors’ data helps retailers price their products correctly, helps with product matching, historical trend analysis, and much more. However, data lakes can also be used to store consumer data such as who they are, what they purchase, how much they spend on average, and how they interact with a company. Successful retailers leverage both competitor and consumer data to understand their consumers better, what brands to carry, how to price each product, and what categories to expand or contract. Retailers also store identity data such as a person’s name, contact information, gender, email address, and social media profiles. Other types of data stored are website visits, purchase patterns, email opens, usage rates, and behavioral data. 

    The major challenge with a data lake architecture is that it stores raw data with no oversight of the contents. Without elements like a defined mechanism to catalog and secure data, data cannot be found, or trusted resulting in a “data swamp.” Consequently, companies need teams of data engineers to clean data for data scientists or analysts to generate insights. This not only increases the turnaround time of gaining valuable information but also increases operational costs.

    However, you can rely on platforms like DataWeave that stores competitor pricing & assortment information at a centralized location. You can leverage intelligently designed dashboards to get real-time insights into the collected data and make data-driven decisions without the need for storing, cleaning, and transforming the data.

    3. Data Ingestion & ETL

    To churn out better insights, businesses need access to all data sources. An incomplete picture of data can cause spurious analytic conclusions, misleading reports and inhibit decision-making. As a result, to correlate data from multiple sources, data must be in a centralized location—a data warehouse or a data lake. However, extracting and storing information into these systems require data engineers who can implement techniques like data ingestion and ETL.

    While data ingestion focuses on getting data into data lakes, ETL focuses on transforming data into well-defined rigid structures optimized and storing it into a data warehouse for better analytics workflows. Both processes allow for the transportation of data from various sources to a storage medium that an organization can access, use, and analyze. The destination can be a data warehouse in the case of ETL and a data lake in case of data ingestion. Sources can be almost anything from in-house apps, websites, SaaS data, databases, spreadsheets, or anywhere on the internet.

    Data ingestion & ETL are the backbones of any analytics/AI architecture since these processes provide consistent and convenient data, respectively. 

    4. Programming languages

    Programming languages

    Programming languages are tools used by programmers to write instructions for computers to follow since they “think” in binary—strings of 1s and 0s. It serves as a bridge that allows humans to translate instructions into a language that computers can understand. Some common and highly used programming languages for building AI models are Python and R.  

    While Python is the most widely used language for training and testing models, R is mostly embraced for visualizations and statistical analysis. However, to productize the ML models, you would require Java programming language so that models can be integrated with your websites to provide recommendations.

    5. Libraries/AI frameworks

    An AI framework is a structure that acts as a starting point for companies or developers to add higher-level functionality and build advanced AI software. A framework serves as a foundation, ensuring that developers aren’t starting entirely from scratch.

    Using AI frameworks like TensorFlow, Theano, PyTorch, and more saves time and reduces the risk of errors while building complex deep learning models. Libraries and AI frameworks also assist in building a more secure and clean code. They future aid developers in simpler testing and debugging.

    Various open-source frameworks in the market also come with pre-trained models for specific use cases. Organizations can leverage off-the-shelf models and tweak with existing data to enhance the accuracy of the predictions.

    6. IDE & Notebooks tools

    IDE or Integrated Development Environment is a coding tool that allows developers to write and test their code more efficiently. However, notebooks are one of the most popular AI tools for organizations to execute analysis and other machine learning tasks. It offers more flexibility over IDEs in terms of exploratory analysis.

    All the features, including auto-complete, that IDEs or notebooks offer are beneficial for development as they make coding more comfortable. IDEs/Notebooks increase developers’ productivity by combining common software activities into a single application: building executables, editing code, and debugging.

    7. Analytics tools

    Competitive Pricing

    Data Analysis transforms raw data into valuable statistics, insights, and explanations to help companies make data-driven business decisions. Data analytics tools like PowerBI and Tableau have become the cornerstone of modern business for quickly analyzing structured and semi-structured data. 

    However, these platforms aren’t optimized specifically for the eCommerce industry. Consequently, you should embrace analytical tools particularly designed for eCommerce companies to make better decisions about product assortment, pricing, and promotions. With data analytics, companies can gain insights into the most popular and discoverable brands on their own and competitors’ platforms. Paired with attribute matching, competitive intelligence gives a deeper understanding of the latest trends and why certain products are popular with your customers. Some more meaningful metrics that retailers can track are discount gap, price gap, catalog strength, and product type gaps. 

    Competitive pricing is another benefit of data analytics with which retailers can identify gaps and keep up with actionable pricing insights. Retailers get to maximize profits and respond to demand by cashing in on insights into rivals’ pricing. With the right analytics tools, they can also track changes in pricing across crucial metrics such as matched products, recent price changes, highest price positions, stock status, and much more. 

    Analytics tools can also help eCommerce companies to capture information about competitors’ promotional banners through AI-powered image analysis. It can provide insights into how and where to spend promotional expenditure. 

    Conclusion

    This listicle discusses some of the AI and data tools commonly used by the eCommerce industry. Data analytics has become a popular method for retailers to understand their customers and boost productivity. Data analytics help companies improve customer experience, improve customer loyalty, generate insights, and advise on data-driven actions. Business intelligence tools can help companies monitor key performance indicators (KPIs), perform proper data analyses, and generate accurate reports. 

    Want to learn how DataWeave can help make sense of your and your competitor’s pricing, promotional, and assortment data? Sign up for a demo with our team to know more.

  • How Brands Can Outperform Rivals With Next-Gen Digital Shelf Analytics

    How Brands Can Outperform Rivals With Next-Gen Digital Shelf Analytics

    As eCommerce grows in complexity, brands need new ways to grow sales and market share. Right now, brands face urgent market pressures like out-of-stocks, an influx of new competition and rising inflation, all of which erode profitability. As online marketplaces mature, more brands need to make daily changes to their digital marketing strategies in response to these market pressures, shifts in demand, and competitive trends.

    eMarketer forecasts 2021 U.S. eCommerce will rise nearly 18% year-over-year (vs. 6.3% for brick-and-mortar), led by apparel and accessories, furniture, food and beverage, and health and personal care. The eCommerce industry is also undergoing fundamental changes with newer entities emerging and traditional business models evolving to adapt to the changed environment. For example, sales for delivery intermediaries such as Doordash, Instacart, Shipt, and Uber have gone from $8.8 billion in 2019 to an estimated $35.3 billion by the end of 2021. Similarly, many brands have established or are building out a Direct to Consumer (D2C) model so they can fully own and control their customer’s experiences.

    In response, DataWeave has launched the next generation of our Digital Shelf Analytics suite to help brands across retail categories directly address today’s costly market risks to drive eCommerce growth and gain a competitive advantage.

    “Our new enhancements help brands improve online search rank visibility and quantify the impact of digital investments – especially in time for the busy holiday season.”  
    ~ Karthik Bettadapura, CEO and co-founder, DataWeave

    The latest product enhancements provide brands access to tailored dashboard views that track KPI achievements and trigger actionable alerts to improve online search rank visibility, protect product availability and optimize share of search 24/7. Dataweave’s Digital Shelf Analytics platform works seamlessly across all forms of eCommerce platforms and models – marketplaces, D2C websites and delivery intermediaries.

    Dashboard for Multiple Functions

    While all brands share a common objective of increasing sales and market share, their internal teams are often challenged to communicate and collaborate, given differing needs for competitive and performance data across varying job functions. As a result, teams face pressure to quickly grasp market trends and identify what’s holding their brands back.

    In response, DataWeave now offers executive-level and customized scorecard views, tailored to each user’s job function, with the ability to measure and assess marketplace changes across a growing list of online retail channels for metrics that matter most to each user. This enhancement enables data democratization and internal alignment to support goal achievement, such as boosting share of category and content effectiveness. The KPIs show aggregated trends, plus granular reasons that help to explain why and where brands can improve.

    Brands gain versatile insights serving users from executives to analysts and brand and customer managers.

    Prioritized, Actionable Insights

    As brands digitize more of their eCommerce and digital marketing processes, they accumulate an abundance of data to analyze to uncover actionable insights. This deluge of data makes it a challenge for brands to know exactly where to begin, create a strategy and determine the right KPIs to set to measure goal accomplishment.

    DataWeave’s Digital Shelf Analytics tool enables brands to effectively build a competitive online growth strategy. To boost online discoverability (Share of Search), brands can define their own product taxonomies across billions of data points aggregated across thousands of retailer websites. They can also create customized KPIs that track progress toward goal accomplishment, with the added capability of seeing recommended courses of action to take via email alerts when brands need to adjust their eCommerce plans for agility.

    “Brands need an integrated view of how to improve their discoverability
    and share of search by considering all touchpoints in the digital commerce ecosystem.”
    ~ Karthik Bettadapura, CEO and co-founder, DataWeave

    Of vital importance, amid today’s global supply chain challenges, brands gain detailed analysis on product inventory and availability, as well as specific insights and alerts that prompt them to solve out-of-stocks faster, which Deloitte reports is a growing concern of consumers (75% are worried about out-of-stocks) this holiday season.

    User and system generated alerts provide clarity to actionable steps to improving eCommerce effectiveness.
    You also have visibility to store-level product availability, and are alerted to recurring out-of-stock experiences.

    Scalable Insights – From Bird’s Eye to Granular Views

    DataWeave’s Digital Shelf Analytics allows brands to achieve data accuracy at scale, including reliable insights from a top-down and bottom-up perspective. For example, you can see a granular view of one SKUs product content alongside availability, or you can monitor a group of SKUs, say your best selling ones, at a higher level view with the ability to drill down into more detail.

    Brands can access flexible insights, ranging from strategic overviews to finer details explaining performance results.

    Many brands struggle with an inability to scale from a hyper-local eCommerce strategy to a global strategy. Most tools available on the market solve for one or the other, addressing opportunities at either a store-level basis or top-down basis – but not both.

    According to research by Boston Consulting Group and Google, advanced analytics and AI can drive more than 10% of sales growth for consumer packaged goods (CPG) companies, of which 5% comes directly from marketing. With DataWeave’s advanced analytics, AI and scalable insights, brands can set and follow global strategies while executing changes at a hyper-local level, using root-cause analysis to drill deeper into problems to find out why they are occurring.

    As more brands embrace eCommerce and many retailers localize their online assortment strategies, the need for analytical flexibility and granular visibility to insights becomes increasingly important. Google reports that search terms “near me” and “where to buy” have increased by more than 200% among mobile users in the last few years, as consumers seek to buy online locally.

    e-Retailers are now fine-tuning merchandising and promotional strategies at a hyper-local level based on differences seen in consumer’s localized search preferences, and DataWeave’s Digital Shelf Analytics solution provides brands visibility to retailer execution changes in near real-time.

    Competitive Benchmarking

    Brand leaders cannot make sound decisions without considering external factors in the competitive landscape, including rival brands’ pricing, promotion, content, availability, ratings and reviews, and retailer assortment. Dataweave’s Digital Shelf Analytics solution allows you to monitor share of search, search rankings and compare content (assessing attributes like number of images, presence of video, image resolution, etc.) across all competitors, which helps brands make more informed marketing decisions.

    Brands are also provided visibility into competitive insights at a granular level, allowing them to make actionable changes to their strategies to stay ahead of competitors’ moves. A new module called ‘Sales and Share’ now enables brands to benchmark sales performance alongside rivals’ and measure market share changes over time to evaluate and improve competitive positioning.

    Monitor competitive activity, spot emerging threats and immediately see how your performance compares to all rivals’, targeting ways to outmaneuver the competition.

    Sales & Market Share Estimates Correlated with Digital Shelf KPIs

    In a brick-and-mortar world, brands often use point of sale (POS) based measurement solutions from third party providers, such as Nielsen, to estimate market share. In the digital world, it is extremely difficult to get such estimates given the number of ways online orders are fulfilled by retailers and obtained by consumers. Dataweave’s Digital Shelf Analytics solution now provides sales and market share estimates via customer defined taxonomy, for large retailers like Amazon. Competitive sales and market share estimates can also be obtained at a SKU level so brands can easily benchmark their performance results.

    Additionally, sales and market share data can also be correlated with digital shelf KPIs. This gives an easy way for brands to check the effect of changes made to attributes, such as content and/or product availability, and how the changes impact sales and market share. Similarly, brands can see how modified search efforts, both organic and sponsored, correspond to changes in sales and market share estimates.

    Take Your Digital Shelf Growth to the Next Level

    The importance of accessing flexible, actionable insights and responding in real-time is growing exponentially as online is poised to account for an increasing proportion of brands’ total sales. With 24/7 digital shelf accessibility among consumers comes 24/7 visibility and the responsibility for brands to address sales and digital marketing opportunities in real-time to attract and serve online shoppers around the clock.

    Brands are turning to data analytics to address these new business opportunities, enhance customer satisfaction and loyalty, drive growth and gain a competitive advantage. Companies that adopt data-driven marketing strategies are six times more likely to be profitable year-over-year, and DataWeave is here to help your organization adopt these practices. To capitalize on the global online shopping boom, brands must invest in a digital shelf analytics solution now to effectively build their growth strategies and track measurable KPIs.

    DataWeave’s next-gen Digital Shelf Analytics enhancements now further a brand’s ability to monitor, analyze, and determine systems that enable faster and smarter decision-making and sales performance optimization. The results delight consumers by helping them find products they’re searching for, which boosts brand trust.

    Connect with us to learn how we can scale with your brand’s analytical needs. No project or region is too big or small, and we can start where you want and scale up to help you stay agile and competitive.

  • Top 4 ways to optimize content to drive e-commerce sales

    Top 4 ways to optimize content to drive e-commerce sales

    Content is the reigning king for e-commerce & plays a big role in driving sales and conversions. And, consumer-centric content that drives traffic is vital for e-commerce sales. Unlike offline retail where the sales staff on the ground is always available to answer customer queries, online that is not the case. When shopping online, customers rely on audio & visual product content to give them the information they need in order to make purchase decisions. Understanding that your product speaks to your customers directly on online channels is critical – so optimizing your product content to represent your brand in the best light is very important.

    Here are the Top 4 ways to optimize content & drive ROI.

    1. Focus on your customer & set a brand tone

    Who is your customer? And what type of product is your brand selling? The golden rule to getting the right content for your brand is to answer these two questions right. For instance, if you’re selling furniture and focusing on a family audience then using flowery language will not help your cause. You need to share factual, product-specific content, calling out furniture specs from color, fabric, size, and so on.

    Flower Glossary Categories

    Take for instance ProFlowers – a US-based flower retailer who created an entire Florapedia® – an in-depth flower guide. This content helped their customers learn more about the various flowers & discover new flowers they never knew of when making purchase decisions. To drive e-commerce sales, ProFlowers set the brand tone using educational content.
    On the other hand, if you are selling clothing or lingerie, you need to be extremely specific about the details of each product. Let’s look at reputed outdoor clothing brand Jack Wolfskin – they use high-quality images for content optimization and showcase real instances and moods in which the clothing can be worn or what they can be paired with. This is a good way to allow customers to picture themselves owning the item, as well as research their unique qualities.

    Clothing brand Jack Wolfskin
    Educational, visual-heavy, or fun & quirky – pick your content style based on your brand tone.

    2. Use videos as a powerful content optimization tool

    Videos empower content and hook your customers in. In a report, Cisco had earlier projected that by the year 2022, videos will be responsible for 82% of all consumer internet traffic. For e-commerce, video content can not only deliver a message but is easily shareable across all platforms. Videos not only possess the power to captivate people for extended amounts of time, but according to research, if a video is embedded on your website, you’re 53 times more likely to rank on the first page of Google. 

    Videos work as a descriptive medium to give more details about your product. Further, explanatory videos relieve consumer fears regarding the quality of the product by allowing viewers to visually experience its usages and benefits. MAC for instance uses a host of make-up tutorials and other video content on their website.

    videos as a powerful content optimization tool

    Videos bring brand storytelling to life and keep visitors informed. In the case of the videos created by MAC, they are not only informative and engaging, but they also help the brand answer common shopper questions with live examples. Customers who land upon the MAC website can watch videos relevant to the products they want to shop for, understand the product details and then decide if the product is for them. Thus, brands using videos can create a better customer experience by giving the visitors an immersive brand exposure online, just like they could have got offline. 

    3. Focus on making your product page consumer-centric

    A product page can be highly discoverable if it aligns with the best practices & standard e-commerce algorithms put in place by popular marketplaces and e-commerce channels. This is because the organic product ranking algorithms vary across channels and are composed of direct and indirect factors used to match a consumer’s popular search queries to products they are most likely to purchase. For better content optimization that ensures visibility, start by mapping platform-specific content standards. Then follow the SEO trends and tweak your product titles and description, to give your brand content a boost.

    LOVE Hair product
    Love Hair Product

    Take for instance the LOVE Hair product pages – the product titles are crafted using product features and benefits like revitalizing, nourishing, volumizing. Consumers searching for shampoos normally type in these attributes to look for shampoos that may suit their requirements – so using attributes as a hook in the product title is a great idea to make the product more discoverable against that keyword or attribute. 

    Next, keeping these standards as a backbone, fine-tune the product details you are putting out on the page. Your product features are the reasons why your consumer will buy your brand as compared to your competitors, so your descriptions should be crisp, easy to read, highlighting all the product features & facts that help them make that purchase decision. Let’s look at the Fitbit product page…

    Fitbit product page
    Fitbit Product Page

    4. Optimize content based on devices

    With mobile commerce reaching the tipping point in the e-commerce sales funnel, you cannot ignore attending to content optimization for hand-held devices. Many times, buyers on the go use mobile devices to conduct their research and your success lies in being able to entice them with a perfectly optimized e-commerce page even on their mobile device. Here are a few tips to keep in mind:

    • Keep their reading experience in mind. Use shorter titles, and bite-sized product information so key points are upfront and visible on a tinier screen 
    • Be concise with your content presentation
    • Video content should not autoplay on mobile. The less invasive your content, the better
    • Keep video & image file sizes small so that page load time is quick
    Optimize content based on devices
    E-Commerce Product Page

    A perfectly balanced e-commerce product page is even more vital in the new normal, given that COVID has accelerated e-commerce, globally. So, whether you are selling furniture, books, clothes, or health juices, with the right focus on product content, you can convert shoppers into customers more easily and increase your sales & revenue. Feel free to take inspiration from some of the examples above to apply some of these strategies to your online store.

    And if you need to get your brand discovered with content optimization, here’s how DataWeave can help! 

    Building the right product page with the right content is not enough. You will also need to keep rehashing your product pages with reviews, offers, and other such relevant nodes to deliver the right punch. After all, delivering the right customer experience starts with a product page done right. 

    Want to see first-hand how DataWeave can help brands with content optimization? Sign up for a demo with our Digital Shelf experts to know more. 

  • Win Search. Win the Digital Shelf this Holiday Season!

    Win Search. Win the Digital Shelf this Holiday Season!

    With the holiday shopping frenzy right around the corner, brands need to do everything they can to win their customer’s share of wallets. ‘Tis the season shoppers have longer shopping lists and will likely buy products they’ve never purchased before for gift giving. This makes it even more critical for brands to make sure they make it easy for shoppers to find their product at the time right time, with the right deals and discounts.
    Watch the webinar with Karthik Bettadapura – CEO, Co-Founder at DataWeave & Vladimir Sushko– E-Retail Director at Anheuser-Busch InBev & learn about the key levers brands need to pull to get their Digital Shelf ready for the Holiday Season

    Let’s start with Product Search…

    Search Optimization

    Organic levers you can pull for Search Optimization

    Key Highlights:

    • Product content is not a one-time fix. It’s seasonal. Seasons change and so does your product. Your content needs to reflect these dynamic changes. 
    • Fact – Search rankings drop when product availability starts dipping.
      Lesser known fact – even after stock replenishing, your search ranking does not bounce back immediately. The opportunity cost of dwindling product stock is high. 
    • Being optimized for the right keyword is good. Being optimized for the right keyword, with a higher ranking than your competitor is great! 
    • Ratings & Reviews have a large correlation with search ranking and impact on sales.

    We then asked the audience what factors they thought had the biggest impact on search rankings… 

    Search Ranking

    Listen to the experts answer questions that have been on everyone’s mind this Holiday Season! 

    Win Search Wn the Digital Shelf
    • Vladimir: How do you approach Search at Ab InBev? 
    • Vladimir: Favourites have an impact, but is this something you can influence? If yes, how?
    • Vladimir: When it comes to growing your online sales via marketplaces what’s the one lever you pull most aggressively?
    • Karthik: Optimizing Share of Search on Marketplaces v/s traditional online retailers 
    • Vladimir: What organic efforts do you use to improve your share of search?
    • Vladimir: When it comes to sponsored search do you use an always-on strategy or are ads spent strategically? 
    • Karthik: Sponsored or Organic? What’s your advice to brands? 
    • Vladimir: Are you tracking your competitor’s Digital Shelf? 
    • Karthik: Which competitor KPIs do you recommend brands should track?
    Bonus Content

    Vladimir: What’s your strategy to make sure you have a high share of search during Christmas – the busiest shopping season. 

    Karthik: What’s your advice for brands for the festive season?

    Click here to register for the On-Demand Webinar

    Do you know if your brand is prepped and ready to make an impact during the biggest holiday season of the year? Or simply just wondering if your Digital Shelf is optimized with the right price, discounts, reviews, and keywords? Our team can DataWeave can help! Reach out to our Digital Shelf experts to learn more.

  • 2021 Cyber Weekend Preliminary Insights

    2021 Cyber Weekend Preliminary Insights

    The exponential growth of eCommerce has forever changed holiday shopping as we know it. What was once led by the launch of Cyber Monday in 2005, has since expanded to ‘Cyber Five’ in 2018, now spans beyond an eight-week period, and is collectively the busiest digital shopping period of the year. Most retail websites have launched a ‘Thanksgiving Comes Early’ sales event for a mosaic of products, causing one to wonder how this ‘early start’ to holiday shopping will impact the traditional promotional cadence consumers have grown to expect to see launch closer to the holidays. Given today’s environmental challenges, threats of scarcity are also encouraging consumers to buy early, which could also impact traffic on the shopping days that have traditionally seen the highest sales volume from digital shoppers.

    In the current environment, the onus will be on consumers to keep a watch for their categories of interest and buy them as and when they appear on sale in their favorite store, because there is no guarantee of sustained availability. Of course, they might return and buy at a different store if a better deal comes up, but there’s a time cost for the dollars saved. More broadly, there has been enough noise made about deals and discounts to keep consumer interest and curiosity going.

    The early promotional start and heightened demand has influenced our team to get a jump start on our 2021 Black Friday analysis to look deeper at trends seen pre-Black Friday 2021 versus 2020. With this assessment, we can track how promotional prices and product availability rates may have changed throughout the event leading in to 2021 Cyber Five, and compare it to last year’s activity to understand how 2021 holiday sales may be impacted.

    We reviewed popular holiday categories like apparel, electronics, and toys (for kids and pets), to have a broad sense of notable trends seen consistently throughout various, applicable marketplaces. What we found is a consistent decline in product availability over the last six months and as compared to last year, alongside an increase in prices.

    We first analyzed availability changes for popular categories on Amazon, noted in the chart below, to understand how inventory may have changed throughout the year, and also compared to 2020. With the exception of batteries and solar power goods and books and maps, there appears to be consistency in greater product availability in 2021 versus 2020, but a slow decline in availability throughout 2021, leading into the holiday season.

    Source: DataWeave Commerce Intelligence – Product Availability in-stock percentage from July 2020 through September 2021 for a sample size of 1000+ products on Amazon.com

    When it came to our pricing analysis, we reviewed select categories on Amazon and Target.com, and found around fifty percent of products on both websites to have seen a price increase year-over-year, while only thirty-seven percent and sixteen percent of products saw a price decrease on Amazon and Target.com, respectively. We also see an increase in the manufacturer’s retail price (MRP) in 2021 versus 2020 for a very high proportion of products (forty-eight percent of products on Amazon and thirty-five percent of products on Target.com), but the discount percentages have remained the same.

    Source: DataWeave Commerce Intelligence – Pricing Intelligence: MRP and promotional pricing for 1000+ products on Amazon and Target.com were analyzed from November 13th – 15th, 2021 versus Pre-Black Friday November 24th & 25th 2020

    *Please reach out to our Retail Analytics experts for access to sub-category details available within the above analysis conducted on Amazon and Target.com.

    This indicates 2021 discounts may appear to be greater than or equivalent to 2020, but in reality, consumers will end up paying higher prices than they would have for the same items in 2020. The remainder of this article highlights our key findings found within each key category reviewed – Electronics, Apparel and Toys.

    Electronics Category Analysis

    The television category showcases a great example of how pricing fluctuations impact holiday promotional cadences. Based on our analysis, we found the average television price to have increased around seven percent from April to October 2021, as seen below and as noted within our analysis conducted with NerdWallet.

    Source: DataWeave Commerce Intelligence – Pricing Intelligence: The change in average price captured for televisions sold on Amazon from May 2021 through October 2021.

    In fact, on Amazon and Target.com, we see around eighty-four percent of the SKUs listed show both an MRP and promotional price increase in 2021 versus 2020 during pre-Black Friday times. One specific example found on Amazon is noted below for Samsung TV model QN65LS03TAFXZA, a 65 inch QLED TV that was priced at $1697 during this analysis at a fifteen percent discount from MRP, but was priced last year at $1497 without a discount from MRP. In essence, even though the TV offers a greater discount this year, it is actually more expensive than it was in 2020 at this same time of year.

    Source: DataWeave Commerce Intelligence – Pricing Intelligence: MRP and promotional pricing analysis on Amazon.com comparing prices from November 13th – 15th, 2021 versus Pre-Black Friday November 24th & 25th 2020

    Unlike TVs, the price of laptops has experienced a decrease over time based on our analysis conducted during the same timeframe, indicating these are a great buy for consumers this holiday season versus promotional offers seen in 2020.

    Source: DataWeave Commerce Intelligence – Pricing Intelligence: The month-over-month change in average price captured for televisions sold on Amazon from April 2021 through September 2021.

    Overall, our prediction is that within the electronics category, promotions during Cyber Five may be equivalent to last year’s offers, however, supply will be limited and the total spend versus last year will be greater to the consumer outside of Doorbuster deals offered on select models.

    Apparel Category Analysis

    The Luxury market is seeing a Roaring 20s-like feeling this season given the Covid-induced changes in work and lifestyle and higher disposable income. Therefore, our prediction is that prices for these goods are likely to remain flat, or offer very little discounts this season both due to supply constraints as well as higher demand. For example, our analysis on shoe pricing changes shows relative stability from April to October 2021.

    Source: DataWeave Commerce Intelligence – Pricing Intelligence: The change in average price captured for shoes sold on Amazon from May 2021 through October 2021.

    Given heightened demand and the Global shipping crisis, we anticipate luxury apparel categories to face out-of-stock challenges this holiday season, and therefore we also anticipate seeing less promotional activity for these items as well during Cyber Five 2021. To dive deeper into the severity of the impact, we looked at availability for clothing, accessories, and footwear categories from August 2020 until present to verify our thesis.

    Focusing only on clothing, accessories, and footwear, these categories followed the same downward trending pattern regarding product availability decreases this year with a decline from June (seventy-six percent versus eighty-six percent in May 2021) to September 2021 (the lowest rate seen at sixty-eight percent availability), followed by a partial recovery in October and November (achieving seventy-seven percent availability).

    Source: DataWeave’s Commerce Intelligence – Product Availability: 10k SKUs tracked across 11 retailers US websites (Farfetch, Brownsfashion, NetAPorter, EndClothing, 24s, Selfridges, Ssense, Harrods, Luisaviaroma, MyTheresa, MrPorter) tracked daily stock status in apparel categories; Availability is calculated as percent of instances when product is in stock against all instances tracked.

    Not all recoveries were the same however, and given this, we predict accessories to have the lowest availability rate and greatest risk of facing out of stocks heading into Cyber Five. From May through November 2021, accessories availability continued to decline significantly from month to month, beginning at eighty-three percent in May and ending at seventy-four percent in November. Given this continued decline and with Black Friday right around the corner, we don’t anticipate inventory levels to increase enough to meet the increased holiday demand.

    Source: DataWeave’s Commerce Intelligence – Product Availability: 10k SKUs tracked across 11 retailers US websites (Farfetch, Brownsfashion, NetAPorter, EndClothing, 24s, Selfridges, Ssense, Harrods, Luisaviaroma, MyTheresa, MrPorter) tracked daily stock status in apparel categories; Availability is calculated as percent of instances when product is in stock against all instances tracked.

    Toys & Games Category Analysis

    As noted by DigitalCommerce360, we also anticipate toys to be one of the greatest impacted categories this holiday season given the continued decline in overall availability for these items on Amazon.com, as one great example. Within our category analysis, we saw a steady decline in availability from March 2021 through June (eighty percent to sixty-one percent), followed by a period of stability from June through August (approximately sixty percent), followed by another decline from September through October, finally reaching the lowest availability of fifty-six percent (down twenty-four percent from March 2021).

    Source: DataWeave’s Commerce Intelligence – Product Availability – hundreds of Toys & Games SKUs tracked on Amazon.com on a weekly basis from March 2021-October 2021

    The biggest sub-category within the toys department on Amazon, Sports and Outdoor Play, followed the same trend as Toys and Games overall through June 2021, also reaching its lowest availability of fifty-six percent. Instead of continuing along that pattern, Sports and Outdoor Play started on a recovery path, ending at a relatively high availability level of sixty-seven percent in October, which is only five percent lower than its highest availability (seventy-two percent in March 2021). Games and Accessories, the second largest sub-category in Toys and Games, had a continuous decline starting with eighty-nine percent in March 2021, reaching its lowest availability of fifty-four percent in October.

    Source: DataWeave’s Commerce Intelligence – Product Availability – hundreds of Toys & Games SKUs tracked on Amazon.com on a weekly basis from March 2021-October 2021

    The sub-category Tricycles, Scooters and Wagons interestingly had its highest availability from July to September 2021 (around eighty percent), unlike other sub-categories which as a whole, had their lowest availability during the same timeframe. From September through October, there was a significant decline (fourteen percent), reaching its lowest availability of sixty-seven percent. The sub-category Babies & Toddlers started on a continuous decline from its highest availability of eighty percent in April to its lowest availability of fifty-six percent in October.

    Source: DataWeave’s Commerce Intelligence – Product Availability – hundreds of Toys & Games SKUs tracked on Amazon.com on a weekly basis from March 2021-October 2021

    *Please reach out to our Retail Analytics experts for access to sub-category details available within the above analysis on the Toys and Games category on Amazon.com.

    Pet Toys Category Analysis

    When it comes to in demand holiday toys, you can’t forget about the needs for gifts for our furry friends and family. We also tracked sub-categories such as dog, cat, and bird toys, following the same methodology as tracked within Toys and Games to track pet toy availability changes.

    Source: DataWeave’s Commerce Intelligence – Product Availability – hundreds of Pet Toys SKUs tracked on Amazon.com on a weekly basis from March 2021-October 2021

    Dog toys, the biggest sub-category out of the three pet toys analyzed, had high availability – ninety percent in March 2021, but started to decline reaching a low of sixty-five percent in October. There was a period of stability from April to August (averaging seventy-seven percent), followed by a significant decline of over thirteen percent in from September to October. Cat toys, the second largest sub-category, also had its highest availability in March (eighty-nine percent) followed by a steady decline to sixty-six percent in June, a recovery from July to August (achieving seventy-three percent), followed by another decline during September and October, reaching its lowest availability of sixty-three percent (down twenty-six percent from eighty-one percent in March). Interestingly, dog toys which has a product count eight times greater than cat toys, had higher availability than cat toys during each of the months considered during the analysis.

    Source: DataWeave’s Commerce Intelligence – Product Availability – hundreds of Pet Toys SKUs tracked on Amazon.com on a weekly basis from March 2021-October 2021

    In Conclusion

    If we consider discounts and availability to be a good indicator of sales for the 2021 holiday season, with the Global shipping crisis looming over this year’s event, we expect retailers to have trouble keeping their inventory well stocked, which might affect growth rates. That being said, while discounts may be muted and popular items may come on very limited sales given constraints, we believe digital sales on Black Friday will see the highest year-over-year growth to date, given a number of supporting factors: scarcity threats increasing demand and the reason to buy, and consumers waiting to see if holiday offers surpass those see in the early start promotions, followed by the sudden rush to buy on Black Friday so as not to risk a given product being out of stock beyond this time period.

    We also anticipate seeing a continued decline in product availability day-to-day as we progress throughout Cyber Five 2021. Given the analysis conducted on 2020 trends, (we tracked nearly a one percent decline in availability on Black Friday 2020 vs. Thanksgiving Day, followed by a two percent decline on Cyber Monday), our data indicates products went out-of-stock at a faster rate then also.

    Ultimately only the digital-savvy retailers and brands will thrive during these opportune times, while others will continue to be in catch-up mode. Access to real-time marketplace insights can enable a first-to-market strategy, while having access to historical patterns can also help react faster to commonly seen future market factors, such as another pandemic or Global shipping crisis. These types of insights also support day-to-day operations, enabling retailers and brands to accelerate eCommerce growth, determine systems to distinguish their online strategies, discover efficiencies and drive profitable growth in an intensifying competitive environment.

    Continue to follow us in the coming weeks to see the insights we track through Cyber Five 2021, and be sure to reach out to our Retail Analytics experts for access to more details regarding the above analysis.

  • Top 10 Retail Analytics that You Must Know

    Top 10 Retail Analytics that You Must Know

    Customers expect personalization. Unless they have a seamless experience on your online channels, they’ll leave for a different retailer. Retail analytics can solve these problems for merchants looking to increase customer satisfaction and sales. It provides insights into inventory, sales, customers, and other essential aspects crucial for decision-making. Retail analytics also encompasses several granular fields to create a broad picture of a retail business’s health and sales, along with improvement areas.

    Big data analytics in the retail market
    Big data analytics in the retail market

    Big data analytics in the retail market is expected to reach USD 13.26 billion by the end of 2026, registering a CAGR of 21.20% during the forecast period (2021-2026). The growth of analytics in retail depicts how it can help companies run businesses more efficiently, make data-backed choices, and deliver improved customer service.

    In this blog, we’ll discuss the top 10 analytics that retailers are using to gain a competitive advantage in accurately evaluating business & market performance.

    Top 10 of Retail Analytics You Must Know
    Top 10 of Retail Analytics You Must Know

    1. Assortment

    Assortment planning allows retailers to choose the right breadth (product categories) and depth (product variation within each category) for their retail or online stores. Assortment management has grown beyond simple performance metrics like total sales or rotation numbers. Instead, retail analytics offers a comprehensive analysis of product merchandise and an estimated number of units at the push of a button. Retailers that effectively apply assortment analytics can enjoy increased gross margins and prevent significant losses from overstocks sold at discounted prices or out-of-stock inventory leading their customers to buy from competitors. 

    It also helps retailers gain insights into the trendy and discoverable brands and products on all e-commerce websites across the globe. They can boost sales by making sure they have an in-demand product assortment. They can also track pricing information and attributes common across popular products to drive their pricing and promotion strategies.

    2. Inventory Management

    An inadequately maintained inventory is every retailer’s worst nightmare. It represents a poor indicator of inadequate demand for a product and leads to a loss in sales. Data can help companies answer issues like what to store and what to discard. It’s beneficial to discard or increase offers on products that are not generating sales and keep replenished stocks of popular items. 

    Worldwide Inventory Distribution

    In 2020, the estimated value for out-of-stock items ($1.14 trillion) was double that of overstock items ($626 billion). A similar trend was especially prominent in grocery stores, where out-of-stock items were worth five times more than overstock items.

    Unavailability of high-selling products can lead to reduced sales, ultimately generating incorrect data for future forecasting and producing skewed demand and supply insights. Retailers can now use analytics to identify which products are in demand, which are moving slowly, and which ones contribute to dead stock. They can know in real-time if a high-demand product is unavailable at a specific location and take action to increase the stock. Retailers can use this historical data to predict what to stock, at what place, time, and cost to maintain and optimize revenue. It helps satisfy consumer needs, prevents loss of sales, reduces inventory cost, and streamlines the complete supply chain.

    3. Competitive Intelligence

    Market intelligence & Competitive Insights
    Market intelligence & Competitive Insights

    The ability to accurately predict trends after the global pandemic and with an unknown economic future is becoming the cornerstone for successful retailers. Smart retailers know how important it is to Pandemic-Proof their retail strategy with Market Intelligence & Competitive Insights 

    With 90% of Fortune 500 companies using competitive intelligence, it’s an essential tool to gain an advantage over industry competitors. Competitive Intelligence allows you to gather and analyze information about your competitors and understand the market–providing valuable insights that you can apply to your own business. A more strategic competitor analysis will explain brand affinities and provide insights on what to keep in stock and when to start promotions. Customer movement data will also give you access to where your customers are shopping.

    4. Fraud Detection

    Fraud Detection
    Fraud Detection

    Retailers have been in a constant struggle with fraud detection and prevention since time immemorial. Fraudulent products lead to substantial financial losses and damage the reputation of both brands and retailers. Every $1 of fraud now costs U.S. retail and eCommerce merchants $3.60, a 15% growth since the pre-Covid study in 2019, which was $3.13. Retail Analytics acts as a guardian against fraudsters by constantly monitoring, identifying, and flagging fraud products and sellers. 

    5. Campaign Management

    Some of the challenges of the retail industry are that it’s seasonal, promotion-based, highly competitive, and fast-moving. In today’s competitive marketplace, consumers compare prices and expect personalized shopping experiences. Campaign management allows marketing teams to plan, track, and analyze marketing strategies for promoting products and attracting audiences. Retail analytics can help businesses predict consumer behavior, improve decision-making across the company, and determine the ROI of their marketing efforts. 

    According to Invesp, 64% of marketing executives “strongly agree” that data-driven marketing is crucial in the economy. Retail analytics can help businesses analyze their data to learn about their customers with target precision. With predictive analysis, retailers can design campaigns that encourage consumers to interact with the brand, move down the sales funnel, and ultimately convert.

    6. Behavioral Analytics

    Retail firms often look to improve customer conversion rates, personalize marketing campaigns to increase revenue, predict and avoid customer churn, and lower customer acquisition costs. Data-driven insights on customer shopping behaviors can help companies tackle these challenges. However, several interaction points like social media, mobile, e-commerce sites, stores, and more, cause a substantial increase in the complexity and diversity of data to accumulate and analyze. 

    Insider Intelligence forecasts that m-eCommerce volume will rise at 25.5% (CAGR) until 2024, hitting $488 billion in sales, or 44% of all e-commerce transactions. 

    Data can provide valuable insights, for example, recognizing your high-value customers, their motives behind the purchase, their buying patterns, behaviors, and which are the best channels to market to them and when. Having these detailed insights increases the probability of customer acquisition and perhaps drives their loyalty towards you. 

    7. Pricing

    competitive pricing in retail
    Competitive pricing in retail

    Market trends fluctuate at an unprecedented pace, and pricing has become as competitive as it’s ever been. The only way to keep up with competitive pricing in retail is to use retail analytics that enables retailers to drive more revenue & margin by pricing products competitively. 

    A report from Inside Big Data found companies experience anywhere from 0.5% up to 17.1% in margin loss purely because of pricing errors. Pricing analytics provides companies with the tools and methods to perceive better, interpret and predict pricing that matches consumer behavior. Appropriate pricing power comes from understanding what your consumers want, which offers they respond to, how and where they shop, and how much they will pay for your products. 

    In 2021, the price optimization segment is anticipated to own the largest share of the overall retail analytics market. Retailers can identify gaps and set alerts to track changes across crucial SKUs or products with pricing analytics. Knowing your customer’s price perception will increase sales and also allow you to design promotions that’ll attract customers. Pricing analytics also accounts for factors like demographics, weather forecasting, inventory levels, real-time sales data, product movement, purchase history, and much more to arrive at an excellent price.  

    8. Sales and Demand Forecasting

    Sales and demand forecasting allow retailers to plan for levels of granularity—monthly, weekly, daily, or even hourly—and use the insights in their marketing campaigns and business decisions. The benefits of a granular forecast are apparent since retailers don’t have to bank on historical data of previous clients and customers to predict revenues. Retailers can plan their strategies and promotions that suit their customer’s demands. 

    With sales and demand forecasting, retailers can also consider the most recent, historical, and real-time data to predict potential future revenue. Sales and demand analytics can predict buying patterns and market trends based on socioeconomic and demographic conditions. 

    9. Customer Service and Experience

    With the development of eCommerce, more and more customers prefer to browse and interact with the product before purchasing online. They look for better deals and discounts across stores and platforms. 3 out of 5 consumers say retail’s investment in technology is improving their online and in-store shopping experiences. To enhance merchandising and marketing strategies, retailers can gather data on customer buying journeys to understand their in-store and online experiences. 

    Retailers can run test campaigns to know the impact on sales and use historical data to predict consumers’ needs based on their demographics, buying patterns, and interests. Retail analytics help retailers to bring more efficiency in promotions and drive impulsive purchases and cross-selling.

    10. Promotion

    Analyze competitors' promotions
    Analyze Competitors’ Promotions

    Promotions are potent sales drivers and need to be cleverly targeted towards specific customers with precise deals to generate outstanding sales. Retail analytics allows companies to study their customers and competitors to a vastly elevated level. 

    To be an industry leader, retail companies not only have to understand their customers, but they must also analyze competitors’ promotions to improve their marketing strategies. Analyzing your competitor’s promotional banners, ads, and marketing campaigns are no more associated with imitation. 

    With data analytics and AI, retailers can watch their competitors’ commercialization strategies. It can uncover vital information about their target audience, sales volume fluctuations, popular seasonal product types, product attributes of popular items, and significant industry trends.  Knowing exactly which products and brands are popular among your competitor’s campaigns can help retailers improve their promotional strategies. 

    Conclusion

    The benefits of retail analytics are spread across various verticals, from merchandising, assortment, inventory management, and marketing to reducing losses. The need for analytics has become even more apparent considering the growing eCommerce platforms, changing customer buying journeys, and the complexity of the industry. Understanding which products sell best among which customers will help retailers to deliver an optimized shopping experience.

    Want to drive profitable growth by making smarter pricing, promotions, and product merchandising decisions using real-time retail insights? DataWeave’s AI-powered Competitive Intelligence can help! Reach out to our Retail Analytics experts to know more.

  • How Artificial Intelligence is giving the Indian Beauty Industry a Facelift

    How Artificial Intelligence is giving the Indian Beauty Industry a Facelift

    With the help of artificial intelligence and machine learning, beauty and cosmetics companies are exploring new possibilities. According to a report by Avendus, the global beauty and personal care market are expected to touch US$725 billion by 2025 and the young Indian market is expected to grow to $28 billion by then. This segment is a space of opportunity and today we have more than 80 Indian brands in this domain. 

    D2C beauty brand logos
    D2C beauty brand logos

    While technology in this space plays a very important role, Artificial Intelligence (AI) amongst everything else is giving the beauty industry a makeover. This is because, AI can create an impact on all stages of the beauty value chain — from research & development to supply chain management to product selection, marketing, and more! Resonating this thought, Chaitanya Nallan, CEO & Co-Founder, SkinKraft Laboratories mentions “As a digital-first brand, we sell across multiple e-commerce platforms as well as through our own website. Thus, it is very important that we track and maintain inventory across all channels in real-time to avoid stock-outs and loss of sales. We use AI for this. We have built an in-house data tracking dashboard that pulls in inventory information from all warehouses and maps them against sales to give us an accurate estimate of days of inventory across all SKUs and across all platforms. This information directly feeds into our procurement dashboard and also helps the marketing team to create the right sales strategy.”

    Stock availability is crucial to driving sales. If you need help tracking your online inventory – DataWeave can help give you a near real-time view of your product stock status across marketplaces. 

    With AI being a powerful technology wand, here is how it can drive the future of beauty brands within the D2C segment in India.

    Making Virtual Product trials a reality

    virtual product trial
    Virtual Product Trial

    Augmented Reality (AR) is a prevalent term and many companies are already using it on an everyday basis. More commonly, the Snapchat and Instagram filters we use are all powered by AR. In a similar vein, virtual images can be laid over actual images in real-time using AI. And keeping this concept handy, beauty brands are bringing to the front the AR-powered ‘virtual mirrors’ that let consumers try on cosmetic products in real-time. Modiface by L’Oréal is a perfect example of VR-mirrors, which has pioneered the AR-powered makeup try-ons in the market. These virtual mirrors use AI algorithms to detect the user’s face through a camera by focal points and map the face. Then using AR, images of makeup are adjusted according to the terms obtained and overlaid over the features on the face giving consumers a virtual feel of what they’d look like wearing the product. 

    Virtual try on
    Virtual Try-on

    Much recently, Indian brand Lakme has made ‘virtual try on’ possible by creating a smart mirror on its official website that allows customers to watch their reflection, try on different shades, and customize those shades according to their preferences. Shade matching until a few years back was an entirely on-ground phenomenon and customers visiting a local cosmetics store were able to choose and match the shade of compact, eye shadow, and lipstick against their true skin tone. Today AI can allow you to narrow down on products based on a virtual shade card, put them against your skin in real-time. 

    Make it Truly Personalised

    Every customer is unique, and one size does not fit all. Everyone has a personalized beauty regime they follow & understanding this could be the key to success for beauty brands. For this reason, the future of beauty lies in harnessing AI and AR solutions to tailor the beauty shopping experience to match the needs of the individual consumer. This not only enhances digital engagement but also increases purchasing confidence which in turn helps brands drive conversion and brand loyalty.  

    Pre-pandemic, offline beauty advisors played a consultative role when customers were making purchase decisions. A lot of this has moved online – take for instance Olay. It launched an online “Skin Advisor” app based on a deep-learning algorithm that analyses a consumer’s skin using a simple selfie! Armed with information on their skin type, customers can make an informed, personalized purchase that’s right for their specific skin type. 

    Skin Advisor App
    Skin Advisor App

    Understanding customer preferences and using data from their past purchases also help with personalized marketing in a big way. “Data-driven personalization gives brands insight into what their customers are interested in. We integrate this data into our marketing campaigns and deliver specific, personalized, and relevant content. This way, we make sure to target the right audience with the right messaging. This, in turn, helps us increase engagement and retain customers. Moreover, this combined data, allows us to get repeat sales through upselling and cross-selling. Further, knowing customers beyond just simple demographics helps us improve our targeting and helps us predict future behaviour. We’d like to know, for instance, if a customer clicked on our advertisement, liked, or commented on our social media product displays, signed up to our email list, etc. These analytics reveal a customer’s interest. Combine it with demographics – and you get a sense of what the customer is interested in,” Dhruv Madhok, Co-Founder, ARATA highlights. 

    Boost Product Development

    Social listening
    Social listening

    AI algorithms can be used to study and analyse customer feedback. The algorithm works towards interpreting customer comments, reviews, and feedback on a brand’s website, social media channels, and other online platforms. Artificial Intelligence can also decode and analyse questionnaires and feedback forms that the customers may have responded to online or offline. 

    The beauty and personal care industry is largely driven by usage and customer preferences, so gauging how customers feel about key products can help businesses create & develop products that customers will most likely prefer to buy. For instance, reputed beauty brand Avon recently mentioned that it developed the True 5-in-1 Lash Genius Mascara based on actual consumer feedback! They used machine learning & artificial intelligence to read, filter, process & rank thousands of online consumer comments to determine the top features they crave in a mascara. Using this customer gathered intelligence, they developed a unique product that consumers we’re “asking for”!

    True 5-in-1 Lash Genius Mascara by beauty brand Avon
    True 5-in-1 Lash Genius Mascara by beauty brand Avon

    Need help listening to what your consumers are saying about your brand online? Read more about DataWeave’s AI Powered Sentiment Analysis solution.

    More and more brands are listening to customer responses closely to give way to new products, bring in tweaks to their existing basket, and innovate further. “Our ORM team is leading the knowledge accumulation as far as social listening is concerned. They are not just responsible for responding to customer queries, they are also instrumental in highlighting key insights based on user behaviour being observed,” Chaitanya of SkinKraft Laboratories further asserts. 

    Bombay Shaving Company too with its data-centric culture leverages customer responses for decision making & product development. “In-home personal care and hygiene exploded during the pandemic. We used data analytics to explore different dimensions of in-home experience-driven needs (new usage occasions, need for convenience and DIY, etc.). We listened to our customers & were able to introduce our women’s brand, with innovative hair removal products in a big way during this period. Which today contributes to a significant percentage of our business,” Shantanu Deshpande, Founder & CEO, Bombay Shaving Company mentions.

    Given the scope and scale of the beauty and personal care industry that is major ‘usage’ driven, Artificial Intelligence with its diverse potential can bring a paradigm shift in the industry. AI can help not only with virtual trials, personalization, listening in to customers’ feedback but also with monitoring a brand’s Digital Shelf. Brands can amplify their online sales by tracking Digital Shelf KPIs like share of search & product visibility, pricing & discounting, product content, availability & assortment. Reach out to our Digital Shelf experts to learn more.

  • Gold, Gift Hampers & Gadgets – brands that sparkled this Diwali!

    Gold, Gift Hampers & Gadgets – brands that sparkled this Diwali!

    The festival of lights symbolized the victory of light over darkness, good over evil & knowledge over ignorance. Over the years, Diwali has become all that and more. It has single-handedly become the biggest shopping season in India! Splurging on a new Smart TV or Fridge, or a furniture upgrade at home has become customary during Diwali. Not to forget buying gold and gifts for all your loved ones! 

    As more and more people are doing their Diwali shopping online, we decided to look at the data, see what people were browsing and buying. And more importantly, which brands spruced up their Digital Shelf & put their best foot forward this Diwali Season. 

    Methodology

    • We tracked the first 250 products on Amazon & Flipkart against specific keyword searches & product categories. 
    • Share of Search (SoS): The percentage of products that appeared on the search results page on Amazon or Flipkart belonging to a brand, against a specific keyword or category. 
    • Dates of Crawl during the Flipkart Big Billion Day / Amazon Great Indian Festival.
      – Pre-sale period: 1st October 2021
      – Sale Period: 3rd to 10th October 2021
      – Post Sale Period: 11th – 18th October 2021

    India’s E-Commerce Gold Rush

    YouGov reported that almost three in ten urban Indians (28%) are planning to spend on gold in the next 3 months. Seven in ten (69%) of these prospective gold buyers agreed with the statement, “Diwali is the best time to buy gold”, highlighting their inclination to spend during the festive season. Also, the same survey showed that Tanishq was the most trusted gold brand. With Kalyan Jewellers, Malabar Gold & Diamonds and PC Jewellers also making it to the top 5 list.

    E-Commerce Gold Rush

    While traditionally Gold was mostly sold offline, that trend has fast changed. We tracked brands that had the highest Share of Search against the keyword “Gold Coin” on both Amazon & Flipkart to see if Tanishq, Malabar Gold, PC Jewellers – the big trusted names in jewellery were making their mark online. 

    Search Insights for Gold Coin
    Search Insights for Gold Coin
    • On Amazon, MMTC-PAMP (a joint venture between Switzerland-based PAMP SA & MMTC Ltd, a Government of India undertaking) and Kundan had the highest visibility for the keyword “Gold Coin” at 10%, followed by Malabar Gold at 9%. (Refer to above graph of Search Visibility on Amazon)
    • MMTC-PAMP used the help of Sponsored ads to get this visibility. They sponsored 9 products during the sale, while ACPL, the largest supplier of silver in India sponsored 26 products and New Delhi-based PC Jewellers sponsored 12 products. (Refer to above graph of Sponsored Products on Amazon)

    As recently as 2 weeks ago, MMTC-PAMP launched their e-commerce portal following in the footsteps of other jewellery brands. According to a report by the World Gold Council, the jewellery industry went through a massive slowdown amid the pandemic and prepping their e-commerce & digital strategies are likely going to be the only way forward.

    • On Flipkart, PC Jewellers, Malabar Gold & Kundan occupied the top 3 spots on the search results page. While PC Jewellers sponsored 12 products on Amazon, on Flipkart they sponsored zero. Malabar Gold on the other hand sponsored a whopping 25 products on Flipkart! Interestingly Malabar Gold sponsored no products on Amazon for the keyword Gold Coin. (Refer to above graph of Sponsored Products on Flipkart)

    Unboxing the love – Branded Diwali Gift Hampers

    Branded-Diwali-Gift-Hampers
    Branded-Diwali-Gift-Hampers

    Now let’s talk about Diwali Gifts. How often have you thought of buying someone a Diwali gift but had absolutely no idea what to get them? You’re not alone! A lot of consumers would simply run a search for “Diwali Gift Hampers” or Diwali Gifts” in the hope to stumble across a great gifting idea and make an instant purchase! Smart brands who know this make sure their products have organic or sponsored visibility against these keywords

    On Amazon, Tied Ribbons, a D2C gift and Décor company had the highest number of Sponsored products (15) against the keyword Diwali Gift followed by the iconic Brand Archies with (14) products.
    Flipkart had a whole bunch of smaller brands and sellers optimizing their products for this keyword. Some bigger, more known brands like Chaayos, Cadbury, D2C Tea brand Vahdam did have visibility for the keywords “Diwali Gift Hampers/ Diwali Gifts” but they were way down on the list, at the bottom of the search results page, or on Page 2.

    Was this a missed opportunity for them?

    Give your home a festive upgrade!

    Diwali is a perfect time to upgrade or buy new electrical appliances for your home. Great prices, new product launches, and an unmatched festive feeling make it even more ideal to make new purchases. If you’re eyeing smart innovative electrical appliances for your home this year and decided to go make your purchase during the Flipkart Big Billion Day or Amazon Great Indian Festival, let’s take a look at which brands made sure they showed up right on top in your online search. 

    We tracked search visibility for 5 keywords in the home appliance space – Smart TV, Washing Machine, Microwave, Air Conditioner & Refrigerators to see which brands had the highest share of search

    Brands with the highest Share of Search on Amazon
    Brands with the Highest Share of Search on Amazon
    • On Amazon, both Samsung & LG had high visibility across all products except Air Conditioners!
    • For ACs, Voltas had the highest share of search even though they sponsored 0 products! And that’s definitely noteworthy. So what really gave them the edge and put them in this winning position?

    We took a look at their product reviews to draw an analysis. Voltas ACs had close to 10k reviews! The highest in the AC category. Ratings & Reviews play a key role in helping brands drive their Digital Shelf experience. Customers trust user-generated content more than information brands share with them. Also, Amazon’s A9 algorithm prioritizes products with better reviews & shows them higher up in search – a low-cost & organic way for brands to get to the top without spending money on Sponsored ads!

    Most loved AC brand
    Most loved Air Conditioner brand
    • When it comes to washing machines, Lloyd & White Westinghouse (trademark by Electrolux) sponsored the maximum number of products in the category, this gave them the highest Sponsored SoS (13%) on the first page. 
    • While their sponsored visibility was high, their overall SoS was low which is why they didn’t organically feature in the top 5. Sponsoring products is a great but expensive way to artificially boost product visibility during sale periods. Brands need to go the Voltas route by optimizing their reviews & rating or content, to organically gain and sustain product visibility.

    … & here are the brands that made it to the top on Flipkart.

    Brands with the highest Share of Search-on-FLIPKART
    Brands with the Highest Share of Search-on-FLIPKART

    Gift-worthy gizmos!

    Buy the latest gadgets and pamper yourself this Diwali or gift them to your loved ones! You could be looking to upgrade your laptop, or buying a fancy DSLR or Smartwatch, buying it online may be your best bet. Discounts have dwindled over the years but you may still get the most lucrative discounts online. Let’s look at the discounts offered on Amazon & Flipkart for some gift-worthy gizmos like Laptops, Cameras, Smart Watches & Headphones this festive season. 

    The platform that offered the highest number of products in their catalog at a discount

    Flipkart had the higher number of gizmos on Discount this Diwali

    On Amazon, during the sale, the headphones category offered a 75% of products on discount as compared to the pre-sales period. That number was just around 51% for cameras. Far more number of products were discounted on Flipkart – 87% for headphones & laptops. And cameras 77%. So if you were looking to shop for gadgets around Diwali, Flipkart would’ve been a better bet. 

    Let’s look at which platform offered the highest percentage of discounts on products. 

    Discounts were higher across all 4 product categories!
    Discounts were higher across all 4 product categories!

    Apart from more products being discounted on Flipkart, Flipkart also offered higher discounts across these 4 categories. Discounts were higher across all 4 product categories!  

    Do you know if your brand is prepped and ready to make an impact on a Big Festival Sale Day? Or simply just wondering if your Digital Shelf is optimized with the right price, discounts, reviews and keywords? Our team can DataWeave can help! Reach out to our Digital Shelf experts to learn more.

  • Discounts continue to fizzle out on Amazon-Flipkart as e-commerce gathers steam

    Discounts continue to fizzle out on Amazon-Flipkart as e-commerce gathers steam

    Around 30 percent of electronic products across Amazon and 19 percent across Flipkart continued to be sold without any discount during October which is ironically seen as the festive month where the two companies make tall claims about deals and discounts offered around Indian festivals.

    Out of the 70-80 percent products where discounts were available, Flipkart surprisingly turned out to be more generous than Amazon during the period under review.

    As per the data exclusively shared with Moneycontrol by digital commerce analytics platform DataWeave, Flipkart on an average offered 26.3 percent discounts across the categories mentioned as compared to Amazon which had just 10.6 percent discounts.

    What makes it more interesting is that while Amazon was officially running its flagship sale The Great Indian Festival for the entire month, Flipkart had concluded its The Big Billion Days on October 10th itself.

    However, it looks like the latter was in no mood to let the competition have it all.

    The pattern is slightly different from the week-long data which was reported by Moneycontrol last month. During the first week of the festive sale, both the two companies offered no additional discounts across 30 percent of the products across the electronics category which houses products like refrigerators, air-conditioners, and laptops.

    While Amazon continues to stick to the trend, Flipkart seems to have become a little aggressive there.

    On a product level, across air conditioners, while Flipkart offered discounts across 84 percent of the products, Amazon offered it only across 73.1 percent of products. Laptops saw at least 87 percent of products on Flipkart having discounts while on Amazon it was across 76.3 percent.

    Smart TV interestingly had a different pattern. While Amazon had 72.1 percent of the products at a discounted price, Flipkart had just 63.7 percent of smart TV’s on discount.

    Interestingly, on Amazon and Flipkart at least 2.5 percent and 3.1 percent of electronic products also had a price hike during the period under review respectively.

    This is a far cry from discounts in the 60-70 percent range that the two companies advertise across electronics and appliances categories on their platforms during the sale period to lure customers.

    “Sellers decide the price of their products on Amazon. Our investment in technology and infrastructure has allowed them to save costs and consistently offer great prices to customers. Our partnership with banks, sellers, and ecosystem partners allow us to add further value through exchange offers, no-cost EMI, instant bank discounts among others, ” said an Amazon spokesperson.

    Flipkart did not respond to queries.

    Bengaluru-based Dataweave counts Japanese ad-tech firm FreakOut Group and domestic venture capital firm Blume Ventures among its investors. The data was shared exclusively with Moneycontrol.

    The price comparisons were made with rates displayed on October 1, the last business-as-usual day before the sale started and the month-long sale period beginning October 3.

    For this analysis, DataWeave crawled pages of the electronics category, which houses products, including air-conditioners, cameras, headphones, laptops, microwave ovens, refrigerators, smart televisions, smartwatches and washing machines. The firm scanned 2,285 products on Amazon and 3,131 on Flipkart.

    According to experts,…Continue reading the article here
    This article was originally published on Moneycontrol on November 3, 2021

  • Prioritizing Brand Protection Before the Holiday Rush

    Prioritizing Brand Protection Before the Holiday Rush

    Counterfeits pose a dangerous threat to any retail brand. Since every single sale is a pivotal branding opportunity, especially for young, burgeoning eCommerce brands, an online marketplace flooded with counterfeits can be particularly dangerous. One in five customers will boycott a brand after mistakenly purchasing a counterfeit product, and that’s not the kind of ratio that any retailer –– from the smallest Direct-to-Consumer (DTC) site to the behemoths like Amazon –– can afford to ignore.

    In the age of online reviews, it’s especially dangerous to have counterfeits floating around. Customers that have a bad experience with a counterfeit can take to the internet to disparage your brand without ever actually interacting with your company or trying your product. That’s why consistent and thorough content audits are paramount to ensuring your brand’s authentic products are highly discoverable, and brand protection and governance processes are in place to safeguard brand integrity across all applicable eCommerce websites.

    The Holiday Counterfeit Boom

    The holidays are a time when customers search for gifts for their friends and family, which means exploring brands outside of their usual fare. Many consumers will be exposed to your brand’s Digital Shelf for the first time over the holiday season, creating an opportunity for brand growth. But if you don’t have eCommerce brand protection initiatives in place, the holidays can be detrimental to brand positioning, customer trust, and your bottom line.

    As consumers boost their online spending and web traffic increases over the holidays, so does the likelihood of them purchasing counterfeit goods online. eMarketer predicts that retail eCommerce sales will comprise almost 20 percent of total holiday retail sales this year. As such, there will also be a surge in counterfeit inventory. So, this is an ideal time to invest in a brand protection solution to help you stay ahead of unauthorized sellers entering the marketplace.

    Brand Integrity Helps Suppliers Save

    Implementing a solution to mitigate the risks of counterfeit products should be at the top of every retailer’s “To-Do” list this year. However, for many retailers, this means manually reviewing numerous websites and third-party marketplaces for violations. Not only is manually reviewing content, images, and seller authenticity a time-consuming process, but it also leaves a lot of room for human error – making it possible for counterfeits to slip through the cracks and into the hands of unsuspecting customers. Not to mention your time should be spent fulfilling orders and increasing customer satisfaction during the high-traffic holiday season, not distracted by monitoring counterfeits.

    Fortunately, that’s not the only way to identify counterfeits and protect your brand online. An effective content auditing tool can help you monitor, detect, and determine systems to identify and act on identified violations, saving time and labor hours normally spent on manual auditing processes. Content audit software also often contains helpful features to help you run your business more strategically by monitoring online hygiene factors like product titles and description. It works across all online channels by highlighting content gaps, which can then be remedied to improve product visibility and conversions. Through online content optimization, you can save money (in unnecessary labor costs), improve your Share of Search, and increase sales and share, with a modest up-front investment.

    Brand Value Protection Boosts Consumer Confidence

    Brand image protection doesn’t just protect retailers, it also protects customers from unintentionally buying dangerous counterfeit goods. Counterfeiting has skyrocketed during the pandemic. The International Chamber of Commerce reports that, by 2022, counterfeit goods will be a $4.2 trillion industry, and global damage from counterfeit goods is projected to exceed $323 billion. Studies show one in four customers has unknowingly purchased a counterfeit item online.

    As counterfeits increase in number, so does the risk of counterfeit consumption by unwitting consumers. Counterfeit goods are as dangerous as they are ubiquitous. Customs and Border Patrol has found ingredients such as cadmium, arsenic, lead, and cyanide inside of counterfeit cosmetics. Consumers are aware of these risks. So, as a retailer, you need to be able to reassure customers that they can trust the authenticity of the goods they are purchasing at your online store.

    A counterfeit detection tool can help you identify fakes and image replicas across multiple online marketplaces, so you can get fake products delisted. Automated counterfeit solutions can increase customer satisfaction in their purchasing experience, since they know they’re getting an authentic product right off the bat. This type of online brand protection creates increased brand loyalty over time, as well as more positive first-time product interactions.

    Making a Measurable Impact: A Counterfeit Detection Case Study

    Classic Accessories is a leading manufacturer of high-quality furnishings and accessories. The company’s investment in a counterfeit detection tool paid off in spades for their organization. After noticing a surge in counterfeit versions of their goods being sold via online, global marketplaces, they decided they needed to change their manual counterfeit and image violation detection process to an automated one to proactively respond to concerned activity in a timely manner.

    Their goal was to achieve streamlined, actionable insights across all retail websites to account for varied violation submission processes, and to reduce the timespan in which insights were generated, ultimately eliminating the need to conduct daily, manual audits. They partnered with DataWeave, who built out a fully customized program to automate Classic Accessories’ content inventory management process, and identified SKU-level violations by matching names and images in diverse online marketplaces.

    During the first three months of onboarding, Classic Accessories was able to detect more than 25,000 violations, submitting notices to each marketplace, and even achieved a 100% removal rate across all Amazon sources. Additionally, they also achieved their goal of saving time (22 hours per week) in automation processes, translating to a $68,000 savings opportunity in labor costs.

    Closing Thoughts

    Prioritizing your online brand protection strategy is imperative to growing your online presence and achieving customer satisfaction and brand loyalty. Fortunately, there are options like DataWeave’s brand protection tool available to help curate your online content, provide consistency across online channels, and improve consumer confidence by addressing and removing counterfeit violations. Implementing the right solution can help find counterfeit products in real-time to keep your brand safe –– and your reputation intact –– throughout the 2021 holiday season. The right brand protection software will provide both Brand Protection and Content Audits, so your brand is optimized from every possible angle for truly competitive results.

  • Amazon-Flipkart sops war in festive sales fizzles out, shows data

    Amazon-Flipkart sops war in festive sales fizzles out, shows data

    Discounts may have been scaled down as the e-commerce market matures and the government looks out for alleged malpractices.

    Radhika Subramanium made umpteen trips to the shiny black Bosch mixer-grinder on her phone in the last few weeks. She put it in her shopping cart and waited for the festive season sale to begin, hoping to get a good deal. At the end of the day, who doesn’t want to save a few extra bucks?

    But, on October 3, the big day when e-commerce giants Amazon and Flipkart locked horns and launched The Great Indian Festival and Big Billion Days, Subramaniam was sorely disappointed. Her cart barely showed any discount. She bought the appliance anyway because it was needed, but her excitement was gone.

    It was largely the same story for Vaibhav Jaiswal. His Boat headphones didn’t even fetch a Rs 200 discount.

    Revati Krishna, in fact, checked out with zero discount on the sit-and-bounce ball she had picked up for her nephew.

    Subramanium, Jaiswal and Krishna are among hundreds of Indians who realised that e-commerce sales no longer offer the lucrative discounts they used to, except for select products such as mobile phones.

    On average, 30 percent of the products sold across the electronics category which houses products like refrigerators, air-conditioners and laptops on Amazon and Flipkart had no discount during their week-long festive sale season, according to a study by a data analytics company.

    Higher prices

    Interestingly, 8-11 percent of the products across categories such as washing machines, microwave ovens and laptops even showed higher prices during the sale across the two platforms.

    The price comparisons were made with rates displayed on October 1, the last business-as-usual day before the sale started.

    The data was compiled by Bengaluru-based digital commerce analytics platform DataWeave, which counts Japanese ad-tech firm FreakOut Group and domestic venture capital firm Blume Ventures among its investors. The data was shared exclusively with Moneycontrol.

    The discounts were lean even on lower-priced products. Amazon dangled a 6.4 percent discount on air-conditioners priced at Rs 33,500-34,000 during the sale, while Flipkart offered barely a 5 percent discount, according to the data.

    This is a far cry from discounts in the 60-70 percent range that used to be advertised across electronics and appliances categories on online marketplaces.

    For this analysis, DataWeave trawled the first five pages of the electronics category, which houses products, including air-conditioners, cameras, headphones, laptops, microwave ovens, refrigerators, smart televisions, smartwatches, and washing machines. The firm scanned 1,184 products.

    Gone are the days when discounts were offered for habit-forming. According to experts, with the markets maturing, companies no longer fancy hoarding deal hunters.

    “As people have got used to buying online, the companies have decided to focus on convenience rather than price,” said Harish HV, managing partner at ECube Investment Advisors. “You won’t even find a significant difference between the price of a product across the two marketplaces Amazon and Flipkart, which have a clear duopoly. It will go on like this unless a big new entrant starts disrupting prices again.”

    According to Harish Bijoor, … Continue reading the article here
    This article was originally published on Moneycontrol on October 27, 2021

  • 6 ways Reviews & Ratings can Skyrocket your eCommerce sales

    6 ways Reviews & Ratings can Skyrocket your eCommerce sales

    As per recent research conducted by Deloitte, approximately 81% of consumers use reviews to make purchase decisions. Reviews work like social testimonials. They are credible recommendations, as a vote of confidence from an existing customer. And when satisfied customers express themselves through the right words, automatically your product gets a boost.

    In case you’re thinking, ‘who has time to read through each and every review?’ Put a pause to your thought, because more than 70% of people regularly or occasionally read online reviews, and 19% of US shoppers trust online reviews as much as a personal recommendation. Online reviews matter and for brands that are selling online, this is becoming a big deciding ground, contributing to sales.

    Let’s go a little deeper and take a look at why good Ratings and Reviews are important for your eCommerce sales.

    1. Use your customer’s voice as a marketing tool!

    Reviews have emerged as a new and effective product promotional tool that never fails to attract the right audience. Even standalone, reviews or word-of-mouth from real users have always been the hook for consumers, so using reviews in your marketing amps up the impact. And the best part is, that it is absolutely free and user-generated!

    Here’s how Fabletics in the UK is using reviews for marketing – they’ve brought these customer testimonials right onto their website homepage! These attention-grabbing reviews showcase the voice of their existing customers and serve as the main influence for future customers that visit their website and want to know more about their brand offerings.

    Fabletics
    Fabletics website

    Using reviews in Search ads is another really impactful way to amplify your customer’s voice and confidence in your brand. Here’s a sample of how we at DataWeave could use our fantastic G2 reviews to build out a Search ad.  

    G2 Review
    G2 Review

    2. Use Reviews & Ratings to influence buying decisions

    Suja Website
    Product page from Suja website

    Display your reviews upfront. Help consumers make their purchase decision easier. Take for instance Suja, a cold-pressed juice brand. Suja converts user ratings and reviews into scores for each of their organic drinks and displays it right below the product, so at one glance users know which products have high reviews and which don’t. This further eases purchase decisions and every customer can decide on the variant right at the product page and then add it to the cart if it meets their expectations.  

    3. Positive reviews impact your brand’s conversion rate

    Improved star rating

    Experts say that 50 or more reviews per product can mean a 4.6% increase in conversion rates. McKinsey has attempted to quantify the relationship between reviews and conversion rates by analyzing reviews and ratings across the 70 highest-selling categories on a major online platform. After tracking hundreds of thousands of individual SKUs over a two-year time span, they found out that the correlation between star ratings and product sales was positive in 55 of the 70 categories they examined. In fact, a jump in rating was also seen to add to the conversion rates growing. Loyalty drives ratings and that, in turn, leads to positive conversions.

    Negative or fewer ratings can directly impact sales. We at DataWeave can help Brands adapt to consumer feedback by tracking their reviews and rating.

    4. Use honest & transparent reviews to build trust, including negative reviews.

    Product Review

    Take for instance this detailed review for a Lancôme mascara on Ulta Beauty. It not only gives the user a ready guide to the product they are eyeing but also makes the brand come out very transparent and believable, courtesy of the cons & negative reviews on display. This helps build a relationship of trust with customers across the board. Various studies have been conducted where consumers said when looking at reviews of businesses, they would trust the company less if there were no negative reviews on display. And they said the probability of every single customer having a four or five-star experience just isn’t believable – this would cause suspicion and has a strong potential of turning them away from making a purchase. Consumers clearly want the real story about a brand or business and not just a rosy picture.

    5 Ratings and reviews can boost SEO

    Ratings and reviews to structure
    Use ratings and reviews to structure the entire listing

    Online reviews are estimated to make up 10% of the criteria Google algorithms use when displaying search results. Every brand understands the importance of putting SEO-optimized content online via blogs & an array of other content marketing activities. Reviews can contribute to that cause too! User-generated content like reviews can work as a ready stream of optimized content, which Google can crawl to rank products higher in search. What is interesting is that buyers when posting a review for products are bound to mention the brand name and use certain words to describe their experience, which subconsciously in most cases become the right keywords! This actually then turns into organically generated authentic, keyword-optimized content. In fact, brands can collect and use rich snippets of reviews on their website or use it for marketing purposes to further optimize listings on Google. Take for Instance Face Theory, they use ratings and reviews to structure the entire listing for their own e-commerce website. This helps them rank higher in search on Google and even on Amazon.

    #6 Understand Customer Sentiment via reviews

    Consumers use reviews to make purchase decisions. On the flip side, what’s interesting is that brands can also gauge their consumers through reviews or feedbacks they submit. This feedback helps brands align with the ground reality of how consumers really feel about their products. And by synthesizing & breaking down reviews across channels, brands can work towards bringing more innovation and personalization for their customer, just the way they want.

    Understand Customer Sentiment via reviews
    Understand Customer Sentiment via reviews

    Take, for instance, Starbucks, a leading international coffee chain introduced MyStarbucksIdea in 2008. This was an instant hit and Starbucks customers within just the first five years of operation, shared over 150,000 ideas and recommendations to the brand, and the company put hundreds of them to use. This is a real case of a brand becoming an advocate to customer sentiments to drive its innovations directly from the core of ideas and reviews submitted by discerning customers.

    In today’s scenario, brands do not need elaborate programs like MyStarbucksIdea, they can simply ask customers for their ideas, thoughts, and suggestions via online reviews across numerous platforms! The only task from there is on is collecting and analyzing these reviews to glean insights.

    explosion of product reviews

    The new normal has led to an explosion of product reviews as more and more people shop online. In the US alone reviews were 40 – 80% higher during the core months of the pandemic in 2020 as compared to 2019.

    Reviews matter, and even more so now. Brands need to build it as part of their actionable strategies and incentivize consumers to rate and review products with each purchase.

    Need help tracking your online ratings? Or decoding customer sentiment from reviews they’ve left for your products? Sign up for a demo with our team to know how DataWeave can help!  

  • Online Halloween Shopping Is Here to Stay – Winning Share of Search

    Online Halloween Shopping Is Here to Stay – Winning Share of Search

    Lessons from Kroger, Albertson’s, and Safeway’s Optimized Online Positioning   

    As consumers continue their migration to online shopping through and after the pandemic, Halloween shopping is no exception. 

    If that’s the new paradigm, what clues should retailers and brands be looking for to enhance their sales? With Halloween around the corner, the analyst team at DataWeave wanted to see how successfully grocers are partnering with brands to prepare for the influx of online Halloween shoppers. We tracked insights from September 14 to 24, 2021, using data from Kroger, Albertson’s, and Safeway websites to understand the preparedness of each retailer, their partnered brands, and how their online strategies compare with one another.

    There are hundreds of ways for a consumer to search for a brand’s products online and of critical importance, almost 50 percent of traffic across the top 1000 retailers come through search. At the same time, consumers are becoming less brand conscious. This is a significant development, and there are significant ramifications to consumers searching for products using generic category specific keywords without including brand names in the search.  Consequently, we can’t sufficiently stress how understanding online channel experiences is critical to successful outcomes. Retailers and brands alike need an integrated view of how to improve their discoverability and share of search by considering all touchpoints in the digital commerce ecosystem.

    The Importance of Product Descriptions, Assortment, Sizes, Price Points

    With 75 percent of people never scrolling past the first page of a website when searching for the goods they desire, getting products to page one is imperative to a brand’s success. While in-store, festive displays will help drive traffic and availability awareness, the ‘digital shelf’ is a totally different locus of opportunity. Here, brands rely on proper product descriptions, the right assortment, sizes, and competitive price points to stand out among the crowd and modify their positioning, given each retailer’s consumer base and assorted competitive brands.

    Optimizing the Digital Shelf and leading Share of Search for page one across all retail websites isn’t achievable overnight, but it is never too early or too late to start, given the 24/7 visibility your products have online. When it comes to Halloween candies, confectionery brands must consider many factors when differentiating their online positioning, such as finding the ‘sweet spot’ for pricing, size, and variety within each product offered, and knowing the right and wrong times to drive promotions. Additional elements to consider when introducing seasonal candies include cannibalization of non-holiday inventory, which can increase spoilage for aged inventory, or if holiday items are successful, could cause an abundance of markdown items to be sold before replacement inventory can be ordered.

    To better understand what retailers are doing—or should be doing—to optimize their Halloween holiday sales, we turned to our DataWeave Digital Shelf Analytics data to answer these questions:

    • Which brands and products are dominating “Share of Search” page one results across all three retailer websites?
    • How do discounts and promotions vary among candy brands and retailers?
    • How does each retailer use Halloween-specific and ‘variety’ labeling within the product descriptor to differentiate their holiday season assortment?
    • What sizes of candy packages is each retailer offering, and how does this play out in online positioning?

    Winning Candy Brands

    Which Halloween candies are people searching for—and presumably buying? Our data shows that Hershey’s branded candies achieved the greatest page one ‘Share of Search’ results across all three retailers’ websites—Albertson’s, Kroger and Safeway. This was unsurprising, given their total SKU count as well as the brand loyalty Hershey’s steadily maintains throughout the year. There is a high likelihood of consumers buying what they see on page one, so in our analysis, Hershey’s has the best chance of ‘winning’ this holiday season within all three of these retail channels. 

    That said, looking more specifically at how candy items are labeled and bundled adds another layer of insight to how candy brands are performing at each of these retailers.

    Historically speaking, Snickers is almost always within the top five confectionery brands sold during the Halloween season, but with the migration of more consumers shopping online, Mars may be leaving opportunity on the table this year. Our data shows that Snickers had the lowest Share of Search percentage on page one results on Safeway.com and Albertson’s.com for brands carrying 8 or more SKUs each, indicating they will most likely not make the first page results—and therefore may end up as a clearance item after Halloween if relying on online promotional efforts to achieve sales goals.

    Source: DataWeave’s Digital Shelf Analytics Solution: Data aggregated from 9/14/21-9/24/21 for Albertson’s.com and Kroger.com, and 9/17-9/24 for Safeway.com; Analysis was conducted reviewing product information for items falling within the ‘Halloween Candy’ listing category

    What Size Candy Packages Are Retailers Carrying/Betting On?

    For example, Albertsons.com and Safeway.com’s assortment includes 124 SKUs and 108 SKUs respectively with most of those items falling within the 5 to 16-ounce (averaging 25 percent) and 32 to 64-ounce (averaging 29 percent) sizes, Kroger.com is betting on a ‘smaller is better’ strategy, with a majority (63 percent) of their candies sold in the 5 to 16-ounce package size. 

    The average Hershey candies available through all three retailers happen to be much greater in size and price point, on average, than other top ranked items, and while these larger items appear to mostly be variety packs, a majority are not labeled as ‘Halloween’ candy.

    Source: DataWeave’s Digital Shelf Analytics Solution: Data aggregated from 9/14/21-9/24/21 for Albertson’s.com and Kroger.com, and 9/17-9/24 for Safeway.com; Analysis was conducted reviewing product information for items falling within the ‘Halloween Candy’ listing category

    How Important Is Halloween-Specific Branding?

    Our data shows that Kroger.com included the name ‘Halloween’ within the product description for most (around 80 percent) of the candies sized 16 ounces or smaller, and overall have labeled more than two-thirds of their total candy items sold as ‘Halloween.’ This indicates they are staged well for the peak of the seasonal demand and anticipate their shoppers to buy smaller unit sizes, comparatively speaking.

    Source: DataWeave’s Digital Shelf Analytics Solution: Data aggregated from 9/14/21-9/24/21 for Albertson’s.com and Kroger.com, and 9/17-9/24 for Safeway.com; Analysis was conducted reviewing product information for items falling within the ‘Halloween Candy’ listing category

    Taking a closer look at all items positioned as ‘Halloween’ across the three retailer websites, Hershey’s brand Reese’s is set for success at Kroger.com for total Share of Search percentage, considering they carry eight Reese’s, non-variety SKUs. Competing in the audience of others leading with variety packs indicates the weight the Reese’s brand carries and also indicates they will also have a great likelihood of success for increased sales this Halloween season. 

    Mars M&M’s brand came out on top at Safeway.com and Albertsons.com within the ‘Halloween’ labeled SKUs, but a majority (around 70 percent) of these are variety packs that leads with the M&M’s brand versus an M&M’s only bag.

    Source: DataWeave’s Digital Shelf Analytics Solution: Data aggregated from 9/14/21-9/24/21 for Albertson’s.com and Kroger.com, and 9/17-9/24 for Safeway.com; Analysis was conducted reviewing product information for items falling within the ‘Halloween Candy’ listing category

    How Much (Less) Are People Paying for Halloween Candy?

    To determine whether candy promotions are increasing Share of Search, DataWeave measured the average promotional discount these retailers and top candy brands are offering online. When looking only at brands offering discounts on 100% of the SKUs they carry within each retailer, Brach’s brand is performing best on Albertson’s.com, and Hershey products are positioned at the top for Kroger.com and Safeway.com. 

    Source: DataWeave’s Digital Shelf Analytics Solution: Data aggregated from 9/14/21-9/24/21 for Albertson’s.com and Kroger.com, and 9/17-9/24 for Safeway.com; Analysis was conducted reviewing product information for items falling within the ‘Halloween Candy’ listing category

    Do Consumers Search For ‘Variety’ Candy Bags, or One-Product-Only Bags?

    DataWeave tagged the word ‘variety’ and found that across all three retailers’ websites, non-variety candy bags take up a greater overall Share of Search than ‘variety’ bags. Either this isn’t an important search word or retailers could try adding ‘variety’ to product descriptions to increase Share of Search.

    Source: DataWeave’s Digital Shelf Analytics Solution: Data aggregated from 9/14/21-9/24/21 for Albertson’s.com and Kroger.com, and 9/17-9/24 for Safeway.com; Analysis was conducted reviewing product information for items falling within the ‘Halloween Candy’ listing category

    Time to Make a Change

    Getting products to page one on retailers’ websites can improve sales by as much as 50 percent, but determining the right levers to pull to get there is no easy feat. Based on our preliminary analysis of Halloween insights, our advice to confectionery brands this Halloween season is to invest now to increase visibility to the fast-changing market, to get orders right and on time, establish effective pricing and promotional plans, and get the right candies in stock, to the right locations. Retailers able to get an end-to-end view of the online competitive landscape will be able to make calculated marketing decisions that stand to help generate growth and profitability.

    We are now within the prime Halloween shopping season, given that 55 percent of candy sales usually happen in the last two weeks of October (According to Timothy LeBel, President of U.S. Sales for Mars Wrigley). With online sales still growing as consumers have shifted their comfort level in buying more online, retailers should be looking for ways to optimize their product positioning, increase their Share of Search, to improve the likelihood of consumers ordering their brand’s candy to ply those Trick-or-Treaters knocking on their doors.

    About DataWeave

    DataWeave is a leading provider of advanced sales optimization solutions for e-commerce businesses, consumer brands and marketplaces. The AI-driven proprietary technology and language-agnostic platform aggregates consumable and actionable Competitive Intelligence across 500+ billion data points globally, in 25+ languages, with insights to performance for more than 400,000 brands across 1,500+ websites tracked across 20+ verticals, to ensure online performance is always optimized.

  • 4 Hacks to improve your online Product Visibility

    4 Hacks to improve your online Product Visibility

    With online shopping becoming increasingly important for brands, the concept of ‘product visibility’ within this ecosystem has emerged as the most noteworthy path to generate sales & win the Digital Shelf. Research shows that on Amazon, the first 3 products garner 64% of business generated. And post-pandemic, more and more people are now shopping online, which means your ‘digital product visibility’ becomes as critical as your in-store product visibility. What’s more, this digital shopper loves to start their search for products directly at leading marketplaces like Amazon, eBay, and the likes. As per the Shopper-First Retail report released by Salesforce almost 87% of shoppers begin product searches online. So, this is the window that brands have and this is where they need to hold their customer’s attention. But the primary question here is how to appear high up on your customer’s search?

    Imagine the pages of an e-commerce marketplace as Digital Shelves and correlate that with the offline space. Will the customer sieve through a rack-full of products to reach for your brand, lying at the back of the shelf? No, they won’t. If they have to buy a personal care item, they will choose the brand that is visible to them at the front of the rack. In a similar vein, when they search for a product online on popular marketplaces, they will quickly click “add to cart” for the ones that come up top in the search. 

    Algorithms of popular e-commerce marketplaces are usually well-kept secrets, but here are 4 hacks brands can consider to increase product visibility on their Digital Shelf.

    1. Optimize what you say about your products

    Content Quality
    Work on the product listing content

    To ensure that your products are visible, you will have to work on the product listing content judiciously. And it’s all about using the right keywords. Here, you will have to tighten the strength of your content to ensure that both your listing text and titles are accurate, and include natural language search keywords that consumers normally use when searching for products. Ignore, jargon or business-heavy words, and think what a real consumer may use to search for a smartwatch – for instance. ‘Bluetooth watch’ or ‘Smart Watch’ or ‘Camera Watch’ etc. The product title below has it all covered.  So no matter which of the 3 keywords a customer is searching for, this watch will come up in their search results.

    Title enables Product Visibility
    Listing Text and Title enables Product Visibility

    This aside, the title should highlight as much as possible about the product and the description should be pointed and readily related to the search one can use to look for it. For instance, in the below image Puracy, has not only used the word shampoo in its title, which normally the consumers will use to search, but has given all the major highlights as a part of the title. The consumer at a glance would get the whole picture inclusive of the quality, fragrance, quantity and the dispenser type.

    Product Features mentioned in Title
    Product features mentioned in Title ensures greater Product Visibility

    Search engines take consumer’s natural language preferences into consideration, so a bad or incomplete product description or title will never help customers see your brand easily on the marketplaces listing. Here’s a listing, which does not work at all.

    Bad or incomplete product description
    Bad or incomplete product description is bad for Product Searchability

    Let’s look at the above example closely. If the customer is a diehard fan of Calvin Klein and is searching for a Calvin Klein sweater, then this product will definitely show up in their search results, but what if he was looking to buy full sleeve polos or wanted a full sleeve sweater, or a navy blue sweater – even though this product fits the bill completely for all the searches, but it may not show up in his search results only because the right content/ keywords have not been used to describe the product. And that is why it is important to use common keywords in your product content that consumers normally use when searching for your product.

    In fact, according to a recent Forrester survey 45% of online shoppers do not complete a purchase if they cannot find what they are looking for, and insufficient product information adds to the cause. If you want to audit your current e-commerce content, DataWeave can help!

    2. Improve product ranking through the right reviews

    Reviews and Ratings
    Good Reviews and Ratings boost product page rankings

    Marketplace search engines prioritize products with good reviews and ratings and show them higher up in search. This prompts product visibility and assures your brand of organic discoverability. So, it is important to fetch as many honest reviews and ratings for your products, in order to gain marketplace visibility.

    Research shows that 88% of consumers trust online reviews as much as personal recommendations, and 72% of consumers are inspired to trust a brand based on the positive reviews it receives. Moreover, millennials, trust user-generated content 50% more than other media. Even though bad reviews are part and parcel of any business, a brand’s focus should be on ‘honest’ reviews. Real user-based reviews have the power to generate customer trust. When customers begin to trust your product and in your brand, they are more willing to add that product to their cart and finalize their purchase. Good product reviews will certainly make your Digital Shelf a lot more attractive & boost your product sales. Learn how DataWeave can helps brands monitor & stay on top of their Reviews & Ratings

    3. Give importance to pricing and attain the sweet spot with product ranking

    Pricing leads to Performance
    The right Product Pricing leads to higher rankings in Searches

    Intelligent pricing, which is not too low or too high should be your weapon to make your brand gain ample visibility among its competitors. Moreover, if the cost of your products is ominously dissimilar from other products it is competing with, it is bound to impact your position in search results. To achieve great results, either you can consider your competitors and analyse the pricing to reach a perfect mid-ground or choose a dynamic pricing strategy. This strategy will allow your products to cost less than the competition, marginally. 

    Amazon is pretty sophisticated in this department and reprices top-selling items 3 or 4 times per day and the same can be repriced up to 12 times daily. Following in line, McKinsey reports that multichannel leaders are also changing the prices on 10 to 20 percent for their online assortment daily.At DataWeave, we can help brands track prices on a daily or even every few hours during sale season, when prices are the most sensitive. Learn more here.

    4. Invest in paid advertising to improve your listing

    Paid Ads - Boost Sales
    Paid ads on Online Retail sites can boost product visibility and Sales

    Investing money in paid promotion at e-commerce marketplaces will help you gain visibility and push your products on top of the first page of your category listing. Today, e-commerce platforms allow you to pay for promoted listings that are displayed near organic search results. In fact, a paid Pay Per Click (PPC) campaign will allow you to build up your sales volume and brand awareness, which will in turn assure your brand of long-term organic search placement. 

    The idea of sponsored ads is getting well-received all across and Amazon’s accelerating ad revenue growth is a living proof of this. In the fourth quarter of 2020, Amazon’s ad revenue reached $7.95 billion, up 66% over the previous year. 

    The e-commerce marketplace is expanding and in 2020, retail e-commerce sales worldwide amounted to 4.28 trillion US dollars and e-retail revenues are projected to grow to 5.4 trillion US dollars in 2022. To be able to make the most of this growing market, make sure your brand is winning the Digital Shelf, starting by winning the appropriate ‘Share of Search’. Want to learn how DataWeave can help you win the Digital Shelf? Sign up for a demo with our team to know more.

  • How an American QSR (Quick Service Restaurants) improved its Business ROI Food Apps

    How an American QSR (Quick Service Restaurants) improved its Business ROI Food Apps

    Traditionally, Quick Service Restaurants (QSRs) such as McDonald’s or Burger King, have been strategically operating on a brick and mortar model. However, according to some studies, an average QSR generates as much as 75% of its sales from online orders.

    With the advent of delivery apps such as Uber Eats and Doordash, a significant portion of QSRs’ business has moved to these platforms. The war to top rank on one of these platforms is an even greater feat. With each brand competing for the top listing, it’s much less about the dollars you pay and much more about optimizing your investments.

    The relationship between QSR chains and food delivery apps has its advantages and disadvantages. One of the critical grouses QSRs have against food apps is the incremental marketing spend required to participate on the platform and the inability to measure the impact of their investment. What makes matters worse is the limitation in metrics even available to measure the impact – neither the food apps provide them, nor does anyone else.

    At DataWeave, we have made it our mission to enable QSRs to not only define measurable metrics to achieve a positive ROI for food app marketing investments, but we also equip QSRs with the tools to track their competitive performance at granular, zip code-based level so that localized strategies can be modified as needed. Below is an example of a 1000+ store chain QSR we partnered with to optimize a pre-existing investment made with a large food aggregator app. Within months of engagement with us, they were able to achieve a 3X increase in sales without adding any additional marketing dollars.

    Below are the pain points we identified and solved together:

    1. No Defined Metric

    Problem – No leading metric to track marketing performance

    One of the first issues we realized was that sales was not a good metric for tracking marketing performance as it’s a lagging metric and doesn’t capture the issues that help grow or suppress sales.

    Most of the sales are driven by rank in the cuisine category and searches for branded keywords. But, the QSR chain had no way to track these ranks.

    In fact, 70%+ sales go to the first five restaurants for the category and keyword

    Comparing ranking on food delivery platforms
    Comparing ranking on food delivery platforms across different categories and times

    Solution – Establish ranking as a clear marketing metric

    By aggregating data across different food app platforms comprehensively, i.e. across locations, at different times of the day, we established the ranking of the QSR chain in critical categories and for priority keywords, identifying where they under or over-performed relative to the competition. As we did this daily- this became a straightforward metric that helped establish the performance of their marketing campaign.

    2. Geographical & Categorical Challenges

    Problem: Identifying poor-performing stores and zip codes

    We realized  it was not a simple exercise to identify well performing stores on food apps since sales depend on many factors such as competition, population of the area, local cuisine preference, etc.

    Solution: Zip Code Ranking and Attributes

    We tracked the ranking of each store within each Zip Code for keywords and created a list of poor-performing stores. We also extracted attributes such as estimated time of arrival (ETAs), Delivery Fee, Ratings, Reviews, etc., for each of these poor performing stores, to identify the reasons for the poor ranking. 

    Analysing key metrics at a store level
    Analysing key metrics at a store level – identifying worst & best performing stores

    E.g., We realized 356 of the stores were not populating on first page results, primarily because of poor ratings and High ETAs. After the focused initiative, 278 of these stores started showing on the first page and increased sales by 23%. 

    3. Sensitivity Analysis Deficiency

    Problem: Not clear about the contribution of Rating, ETAs, Fees, etc. on the Ranking

    The exact ranking algorithms of these food apps are not publicly shared – so the QSR chain wasn’t clear which variable of rating, ETAs, fees, ad spend, or availability contributed more or less to the overall ranking. 

    Solution: Sensitivity analysis for measuring contribution 

    Comprehensive data for multiple zip codes in various timestamps was analyzed to determine which variable contributes most significantly to the rankings and when. We also conducted A/B testing – simultaneously testing two different variables, such as reducing ETAs at one store and improving ad spend at another, calculating which led to greater rank and sales impact.

    For example, we realized reducing publicized ETA’s (even by decreasing the delivery radius) contributed much more to improve the rankings than changes to ratings.

    4. An Unknown Competitive Landscape

    Problem: Tracking competitor performance

    For example, we found the QSR chain performed well in key urban centers, but the competition was doing even better, but there wasn’t a good way to track and compare the performance of the competitors.

    Solution:

    We started tracking the QSR chain and the competition for each of the metrics and started comparing performance.

    Analysing competitive performance
    Analysing competitive performance on key metrics such as ETA, Availability etc

    We quickly realized ranking started quickly improving as we gained a slight edge in each metric against the competitors. For example, 5 minutes less ETA adds to higher ranking.

    In six months of this exercise with the QSR chain, we improved the average ranking from 24 to 11 for the QSR chain, getting them featured on the first page.

    5. Blind Advertising Investment Opportunities

    Problem: 

    The QSR chain was not clear on which banners (Popular near you, National Favorites, etc.)  to choose to invest in, and had to depend on the recommendations of the food platforms entirely. 

    They weren’t even provided a clear view of which position made the banner visible and at what rank among those banners was their promo visible. They were at times the 7th promo in the 6th banner, which has almost zero probability of being discovered by the user – this happened despite paying heavily for the banners.

    Solution: 

    We aggregated data for all banners populated within each zip code and found out the ranking and in which position the QSR chain was visible.

    Analysing right banners
    Identifying and analysing right banners for advertising spends

    The QSR chain invested in 630 zip code-based banners with guaranteed visibility, but our assessment indicated the banners were only visible in 301 zip codes. After selecting suitable banners for promotions, we improved visibility to 533 zip codes within enhancing the budget.  

    We are now using the same strategy for refining discounts, offers, promotions, and coupons. 

    6. Lack of Campaign Performance Monitoring

    Problem: Unsure of the long-term impact of marketing spend

    In general, increasing marketing spend does give a temporary boost to sales, but the QSR chain’s question was, how can we measure the long-term impact i.e., ranking keywords and the targeted zip codes.

    Solution: 

    We created a simple widget for every marketing campaign which showed the rank for the keywords for selected zip codes before the campaign, during the campaign, and post the campaign, clearly establishing the midterm impact of the campaign. This constant monitoring allowed the QSR to also quickly pivot on their strategy on account of national holidays etc, and act accordingly.

    7. Non-Existent ROI Measurement

    Problem: Establishing the impact of ranking on sales

    Though the QSR chain could track sales that were coming via the food app channel, they had no way of knowing incremental organic volume driven by marketing efforts. 

    One missing variable here was how much of extra sales could be attributed to improvement of QSR ranking? 

    Solution: 

    By combining the sales data with aggregated insights over time, we established for the QSR chain how much increase in sales they could anticipate from an increase in ranking, also knowing which changed variables led to the percentage of change increase.

    So, in essence, we were able to tell the QSR chain that for each store how much sales would increase by improving ETAs, rating, ad visibility, availability, etc., enabling precise ROI calculations for each intervention they make for their stores.

    Increasing sales by 3x within six months was only the beginning, and the journey of driving marketing efficiency using competitive and channel data has only just begun. 

    DataWeave for QSRs

    DataWeave has been working with global QSR chains, helping them drive their growth on aggregator platforms by enabling them to monitor their key metrics, diagnose improvement areas, recommend action, and measure interventions’ impact. DataWeave’s strategy eliminates the dependence on food apps for accurate data. We aggregate food app data and websites to help you with analysis and the justification of marketing spend and drive 10-15% growth.

    DataWeave’s strategy eliminates the dependence on food apps for accurate data. We aggregate food app data and websites to help you with analysis and the justification of marketing spend and drive 10-15% growth.

    If you want to know learn how your brand can leverage Dataweave’s data insights and improve sales, then click here to sign up for a demo

  • Structured and Unstructured data – Benefits of Big Data

    Structured and Unstructured data – Benefits of Big Data

    The big buzzword of the decade has got to be data. When the untapped potentials of great data were first discovered, experts started calling it the new oil, implying that it is now the most precious resource. And then when the usage of data became more mainstream, where corporations started mining and getting access to piles of data, people started calling it the new soil, insinuating that if all this data isn’t regularly nurtured and optimally used, it would be rendered useless. 

    But amidst all this hype, all the clutter, and all the buzz around this four-letter word, data is just a bunch of numbers and statistics collected for reference and analysis. Basically, it is just what you, your company, your government, or your country make of it. So how can retailers make the most of it? 

    Before assessing the use cases, it is paramount to understand the different types of data retailers have access to today. Broadly, it is structured and unstructured. Log files, excel spreadsheets with point-of-sale figures, hierarchies, and inventory data are rich sources of structured data; and information that is derived from in-store sensors, customer reviews, social media posts and hashtags, and even conversations between the store staff and customers serve as unstructured data. While the former sits on well-organized databases for retailers to access, giving them operational robustness, unstructured data gathered from social media and personal interactions helps retailers achieve unprecedented value and gain a competitive advantage. However, the very nature of unstructured data makes the process of obtaining, analyzing and making sense of it rather difficult.

    Structuring vs Unstructured
    Structuring vs Unstructured

    In fact, according to a survey by Deloitte, only 18% of organizations reported being able to take advantage of such data. However, harnessing this data isn’t rocket science (not anymore, at least) as there are a number of tools at a retailer’s disposal today that makes this process convenient and efficient. At DataWeave, we help retailers and brands make sense of unstructured data. Read more about our tech here. 

    Unstructured data is also qualitative, rather than being quantitative, which in turn makes its use cases more effective, giving businesses a competitive edge. How? Glad you asked!

    Customer Behaviour Analytics

    What motivates a customer to buy more, or spend more time in a store or online? What is the best time to reach them and where (in an omnichannel world) would they like to be reached? Million-dollar questions, right? Big data gives you insights into this and more, which will then help improve customer acquisition and loyalty. 

    UK-based home retailer Argos uses data to find out exactly how consumers felt about them. After having embarked on an ambitious project of opening 53 new digital stores a few years back, Argos invested in tools that helped them analyze data received from various social media sites based on the demographics and location to assess the performance of each store and identify rooms for improvement. This helped them understand which stores were perceived more favorably and in which areas, quickly identify issues in-store, action feedback, and find resolutions to increase customer satisfaction.

    Want to know customer sentiment against your product? Our Sentiment Analysis solution can help! Access in-depth insights sourced from customer opinions with our constantly evolving algorithm.

    DataWeave Sentiment Analysis
    DataWeave Sentiment Analysis

    Personalization and hyper-personalization

    The fact that customers are interacting with retailers on multiple platforms today gives retailers access to a wealth of information about their individual customers that could help them tailor their products, offerings, services and communication to these individuals. According to a study conducted by BCG and commissioned by Google, customers increasingly prefer a shopping experience that’s easy and fast and that helps them make purchase decisions.

    Target’s popular pregnancy prediction score based on purchase and purchase volume of about 25 different products in-store, such as unscented lotion, large amounts of calcium, magnesium, and zinc, serves as a great example of how they use this information to then target advertising (e.g sending a booklet of coupons related for baby products) to this cohort of their customers. This algorithm got the international limelight when Target started sending such coupons to the irate father of a teenager who had no idea that his daughter was pregnant. Basically, the retailer knew about the man’s daughter’s pregnancy even before he did!

    Operations and supply chain

    Amazon Go
    Amazon Go

    A healthy mix of structured and unstructured data is key today in achieving operational excellence. Faster product life cycles and ever-complex operations cause organizations to use big data in retail analytics to understand supply chains and product distribution to reduce costs. Combining that with CRM, ERPs, and other log file data can help in real-time delivery management, improved order picking, and overall supply chain efficiency to reduce costs. 

    Amazon Go, the checkout-free convenience store by Amazon uses AI-powered cameras, computer vision, and sensors to facilitate grab-and-go systems. Now, the store wholly relies on structured and unstructured data in order to function.  The sophisticated automated system makes ordering and restocking highly efficient, given that the cameras can track inventory in real-time. The system knows how many picks-per-hour each stocker is completing and exactly when items go out of stock. 

    The fact that data enables prediction and forecasts can help cater to a prospective rise in demand by managing the supply chain in advance. For example, if a pharmaceutical company analyzed social media content and determined that people in specific geographical areas were discussing cold and flu symptoms, that could give them a heads-up that demand for products to treat those conditions is on the rise.

    Price and cost optimization

    Machine learning algorithms are not only designed to learn, but over time they get better at finding the optimal price points for retailers. Retailers can use machine learning models to set prices against sales targets. According to an IBM study, 73 percent of companies surveyed plan to optimize their pricing and promotions through smart automation before the end of 2021.

    Automation achievers outshine peers in profitability and revenue growth
    Automation achievers outshine peers in profitability and revenue growth

    Walmart has shrewdly utilized powerful proprietary algorithms to make their offers nearly impossible to beat over the last few years. It still reigns in offering the best price match policy for their customers. This strategy has helped it gain a lot of trust, good publicity, and enabled retention of customers. But how do you optimize what you charge without pricing yourself out? That is where data comes into play. You need real-time monitoring across thousands of stock-keeping units (SKUs) to identify key value categories and items. With proper data analytics in your pocket, you can ask and answer the following important questions: Which items’ prices matter most? Which items have the biggest pull on price perception?  What pricing strategies are competitors adopting, and how can you match them? And which items can you afford to reduce in price to win loyalty and boost that very perception?

    Learn more about how DataWeave can help retailers make smarter pricing decisions. 

    Seamless shopping journey
    Seamless shopping journey

    Every company uses data to achieve its own personal goals and objectives, but what makes one retailer better than the other is how they use both structured and unstructured data to provide a seamless experience and shopping journey to customers in a way that is effortless, non-intrusive, and innovative. So use your structured data and also find a way, use the tools, and leverage the power of technology to structure your unstructured big data. In today’s competitive retail landscape where retailers – both online and offline – are leveraging cutting edge technologies to deliver close-to-perfect products and services, and innovative concepts, it is only the ability to harness all forms of structured and unstructured data that will result in achieving your ever-evolving customer engagement and experience goals. 

    Want to learn how DataWeave can help make sense of your unstructured data? Sign up for a demo with our team to know more. 

  • Seven tricks to win food wars on food aggregators apps

    Seven tricks to win food wars on food aggregators apps

    Food aggregators have emerged as a critical channel for Quick Service Restaurant (QSR) chains to grow their business – especially post-pandemic. Quick Service Restaurants, QSRs, as we call them, are capitalizing on the opportunity too. For many chains, as high as 50% of their revenue now comes via aggregator channels.

    However, most QSR chains are only beginning to leverage data and analytics to drive business on the food aggregator apps.

    Currently, QSRs spend vast amounts on marketing on Food apps but are always unsure of the return on their investment. Aggregators share some data, but they have an inherent motive to entice QSRs to buy more advertisements. They cannot share competitive insights as well. Moreover, as QSRs work with several platforms at once, it gets difficult to collate and analyze data from all these platforms together. These issues make leveraging data for QSR chains difficult. At Dataweave, we have collated some insights from our recent experience of working with global QSR chains helping them improve their sales on different food applications using data:

    1. Availability

    Availability of QSR and Availability Trends
    (L) Availability of QSR outlets across aggregator platforms at state, city, and outlet levels. (R) Availability trends at Lunch and Dinner slots across platforms. Such trends can highlight problem areas that need to be addressed.

    The easiest and most impactful fix is to ensure that all your outlets are available on the app at the peak slots, typically lunch and dinner. Availability increase of ~2% at peak times results in order volume increase by ~5%-7%.

    The reasons for unavailability range from lack of riders, overwhelming orders at the outlet, or just plain technical glitches. Tracking this metric and actively engaging with your stores and aggregator platforms to resolve any issues should be a daily priority.

     2. Monitoring Keyword Ranks

    High correlation between ranking and sales
    Illustrative chart showing a high correlation between ranking and sales

    If you are a Pizza chain but don’t show up among the first five ranks when your target customer is searching for Pizza, the chances of a sale are lower.

    What helps is to track the ranking for your brand, and your competitor brands, in different category listings across different keywords.

    Your ranking may differ a lot by region, markets, and Zip codes depending on consumer tastes, competitors, and your brand presence, and it’s helpful to track it granularly. 

    No surprises here – but rank is strongly correlated with your order volumes!

    3. Tracking competitors

    QSR chain rank
    Illustrative chart showing the rank of key QSR chains on the home page and various categories

    One of the tricks to rapidly gain in ranking is to monitor competitors in your category and ensure that you are doing better on each attribute – ranking, rating, ETAs (estimated time of arrival), fees, discounts, etc.

    A slight edge across your outlets translates to rapid gain in ranking and order volumes.

    4. Choosing suitable banners for promotions

    Position of banners
    Position of various banners at various zip codes. Important to choose banners that rank higher.

    Choosing banners is an essential strategy to gain visibility – but it’s vital to know two factors: 

    • At what rank does the banner you are choosing show up on the App/Website.
    • At what position does your brand show up in the banner?

    If you are on a 5th rank on the 4th banner, your marketing spend is probably going down the drain.


    5. A/B Testing

    Before starting an effective marketing campaign, it helps to do A/B testing by running two different banners in the same city one week apart to see which yields more impact.

    A/B testing can also be a tool to choose banners, discounts, offers, signature images, etc.

    6. Sensitivity analysis

    Delivery time impact
    Illustrative chart showing that ETAs are highly correlated with sales, whereas ratings do not have much impact.
    • What has more impact on sales – Ratings or ETAs? 
    • What will be the likely impact on sales of the marketing campaign in New York vs. Denver? 
    • What is the likely impact of competitors’ ad blitz on your sales?

    Data can answer these and many more questions, and this sensitivity analysis should be part of the QSR chain’s decision-making

    7. Monitoring campaign performance

    QSR chains spend millions of dollars of ad budget running campaigns on aggregator platforms combining banner ads, discounts, offers, etc.

    It’s a great idea to measure QSRs rank on these aggregator’s platforms before, during, and post the campaign in focus Zip Codes for priority keywords to see if the gain in ranking is temporary or lasts for a while.

    The ultimate factors for QSRs to win will remain the quality of food and consistency of the brand’s messaging. Leveraging the power of data can help understand the aggregator platform’s characteristics, competitor’s strengths, weaknesses, & strategy, and consumer behavior trends.

    Also, data can help better direct ad dollars and the eCommerce teams’ focus on the right initiatives to drive maximum sales and growth.

    DataWeave for QSRs

    DataWeave has been working with global QSR chains, helping them drive their growth on aggregator platforms by enabling them to monitor their key metrics, diagnose improvement areas, recommend action, and measure interventions’ impact. 

    DataWeave’s strategy eliminates the dependence on food apps for accurate data. We directly crawl food aggregators apps and websites and help you with data and analysis to solve the aforementioned issues and drive 10-15% growth.

  • Amazon Prime Day Secrets all Brands need to know.

    Amazon Prime Day Secrets all Brands need to know.

    Prime Day or not, brands need to make sure their Digital Shelf is well stocked, highly discoverable in crowded marketplaces, have the right offers and discounts to stay competitive, all while making sure their products have glowing reviews, ratings and optimized content. While this is a year-round effort, brands go the extra mile on Prime Day to make sure they’re putting their best foot forward.

    Methodology
    To understand how brands adapted their digital shelf for Prime Day, we examined data insights across Amazon in 6 markets and compared the following brand KPIs:

    • Share of voice (SOV): The percentage of a brands products that appear in the search results page for relevant keywords on Amazon.
    • Availability: The percentage of products in stock on Amazon for Prime Day.
    • Additional discounts: The reduction in the listing price of a product during Prime Day compared to before or after the event to see how brands adapted their pricing strategies to stand out from rivals

    Winning brands made sure their products were ‘highly’ discoverable

    With all the global lockdowns, home entertainment hit a new high. So we looked at the word “TV” to see which brand had the highest share against this keyword during the Prime Day event.

    • In the US – Samsung won hands down with close to 15% SOV. LG came in at a not so close 2nd with 9% SOV.
    • In the UK – Samsung won again with a whooping 16.7% SOV with Sharp at # 2 at 12%.

    Now let’s look at some key European markets

    • On Amazon Italy we saw a similar trend – Samsung & LG, neck to neck at 22% & 19% respectively.
    • Amazon Germany was no different – Samsung had the highest SOV at 15% and Philips far behind at 7%.

    Samsung has such a strong association with the keyword TV. This means, when customers are searching for TVs on Amazon in these regions – the brand that has the largest selection up on display for them to choose from is Samsung! That’s definitely going to have a positive impact on sales, don’t you think?

    Do you know which keywords you should be tracking for your brand? And do you know your Brand’s SOV against those keywords?

    … & finally, an outlier!

    • In Amazon France, LG took the lead for a change – with 15% SOV. But we have Samsung not far behind at 13%.

    Kudos to team Samsung!

    Winning Brands kept a close eye on product availability

    Poor product availability leads to lost sales. But not on Amazon Prime Day! Bigger brands that sell over 500 products created artificial scarcity by listing a chunk of products out of stock before the sale. And restocked aggressively during the sale.

    In contrast, the smaller brands that sold fewer than 100 products didn’t dare make such bold moves and stayed stocked up even pre-event to avoid even a single day of lost sales.

    Let’s look at some data from the US

    • The average availability for bigger brands selling 500+ products before the sale was 41% and then went up dramatically to 81.4% the day of the sale when they aggressively restocked.

    Similar trend in the UAE

    • Availability pre-sale was 26.2% and during the sale shot up to 87.6%!

    Various other markets displayed similar patterns. And this was only possible because these brands were able to track their availability with precision and plan their stock levels accordingly.

    How are you tracking your availability across marketplaces? Do you know when your products are out of stock and are in immediate need of replenishment?

    Winning Brands made strategic pricing and discounting decisions

    Discounts matter. Period. And brands that use discounts strategically, win.

    Let’s look at Airpods on Amazon in the US.

    • During the event, Apple had the highest SOV for the keyword Airpod at 7.5% followed by SkullCandy, an American audio accessory manufacturer at 5.6%. 
    • Here’s the interesting part – during the sale Apple offered just 3.4% additional discounts while SkullCandy offered 32.1% additional discount to try and win sales from Apple. And looks like it worked! Apples SOV dropped from 13.5% before the event to 7.5% during the event and SkullCandy’s SOV improved 

    Now let’s look at the same data cut in the UAE – a market where Apple products have a fair penetration, but not as high as in the US. They needed a more aggressive discounting strategy in this market.

    • In the US, during the sale, Apple offered additional discounts on just 30% of products. However, in the UAE that number rose to 90% – a clear strategy to make their product pricing more attractive to customers to win sales

    Discounts and markdowns aren’t always the answer to improving sales, but when used strategically can drive significant impact to your bottom line.

    Are you tracking your competitor pricing? Do you know if they’re keeping tabs on your pricing strategy to get ahead of you?

    Winning Brands made it to the Amazon Best Seller list

    Amazon Best Sellers are products that have the highest sales on Amazon. Products with a higher Amazon Best Seller Rank have higher sales.

    • In the US, Nintendo had the highest share in the Electronics Best Seller category during the sale at 18.6%. Before the sale their share stood at 22.5% – so they lost ground a little ground with a 27.2% drop in their Best Seller share. While they gave additional discounts of 17%, only 27% of their catalogue was discounted.
    • But here’s a brand that knocked it out of the park! The Razer had an SOV of just 1.18% before the sale and during Prime Day it shot up to 6%! A clear indication that sales for the Razer spiked exponentially during Prime Day. Could this be because Razer offered 100% of their catalogue on an additional discount of 31%? It’s a bold move that could have paid off and contributed to super high sales. 

    Now let’s look at France – the Fashion Capital of the World and which brand came out on top in the Fashion Best Seller Category

    • Footwear brand Havaianas had the highest SOV on Prime Day (13.48%) Not too surprising because before the sale they were at 14.09%
    • Now let’s look at the Best Seller Rank – Lacoste secured BSR #1 at the event. Pat on the back for them because before the sale they were at Rank 46! And post-sale they dropped to #6. Definitely a combination of techniques involved here that got them from #46 to #1 at super speed!

    What techniques have you tried to boost sales for your products on Amazon?

    Brands that do not optimize their Digital Shelf risk losing out on their share of basket. If you’ve been thinking about how to optimize your Brands Digital Shelf, then get in touch & learn how DataWeave can help!

  • Similarity matching keeps retailers competitive: Know your rivals

    Similarity matching keeps retailers competitive: Know your rivals

    Soaring e-commerce growth has made retail more crowded, complex and competitive. Now retailers face an urgent need to keep an eye on more rivals with potential substitute products to maximize their own e-commerce growth.

    Consider these recent figures, which illustrate online shoppers’ abundance of product choices:
     

    • 24% year-over-year increase in direct-to-consumer (DTC) brands in the U.S. alone was estimated for 2020 as more brands bypass retailers1
    • 55% of shoppers have purchased private label in the past year and many retailers are investing more in their own brands2
    • 110% average increase in small retailers’ 2020 online holiday sales, as more players launched new e-commerce shops during the pandemic3
    • 39% of U.S. consumers have changed brands, with the level of brand switching doubling in 2020 compared to 2019, especially among Gen Z and Millennial consumers, as loyalty declines4

    These statistics prove that in 2021 retailers need to navigate more online players and products. Now retailers need a new approach to stay on top of market trends to keep their e-commerce strategies competitive, profitable and attractive to discerning online shoppers. 


    Retailers reduce the risk of substitutes with similarity matching

    In response to online crowding, more leading retailers are turning to similarity matching. Similarity matching is a type of retail analytics that scour global e-commerce sites to find products that exactly match a specific item as well as products that closely match it. Similarity matching insights have grown in strategic significance because they increase retailers’ visibility into potential substitute products, so they can respond to all rivals’ moves with greater agility and efficiency to stay competitive.


    In terms of e-commerce applications, similarity matching helps retailers gather insights on potential substitute products so they can adjust their pricing and assortment strategies accordingly. Retailers can align their pricing with rivals’ pricing moves for similar items to protect their margins and maximize profitability. They can also make informed assortment decisions, including which product mix of bestsellers, unique items and private labels could optimize their online sales performance.

    Online shoppers search for products differently across different categories

    Consumer behavior plays a role, as online search habits differ across product categories, which influences the type of similarity matching retailers need. For example, categories like fashion, toys, home and kitchen work best with similarity matching based on text and images. In these highly-visual categories, consumers can quickly determine whether a product fits the design and aesthetic they are looking for. As a result, e-commerce product titles, descriptions and product images play a big role in consumers’ purchase decisions.

    By contrast, consumer electronics and furniture are categories in which consumers tend to seek specific product attributes, such as a certain level of resolution for their high-definition TV or a couch with particular dimensions so it fits their living room. For these types of products, consumer purchases are driven by product specifications, so similarity matching takes into account their specific needs as well as a degree of tolerance for exact or near-similar attributes across online competitors.

    Expect intense e-commerce rivalry in 2021

    As more consumers shop online, they are increasingly informed by online product comparison information. A wide variety of product choices means consumers can substitute similar goods with ease, especially if a particular item is out-of-stock. Perceived product differentiation, price sensitivity and private labels can also influence consumers’ purchase decisions.

    Across categories, e-commerce growth is outpacing total retail growth. When competition is this fierce, there is an increased risk that numerous and aggressive players will drive down profit margins. Leading retailers are now seizing opportunities to earn consumer loyalty. Using similarity matching helps retailers by offering in-demand products that consumers will actually buy and deliver exceptional online experiences to prevent shoppers from switching to rivals and their comparable products.

    Similarity matching lets you stay competitive

    As e-commerce traffic and rivalry increase, similarity matching helps retailers stand out and serve online shoppers more effectively.

    Retailers gain visibility into their entire competitive landscape to keep their e-commerce strategy responsive to shifts among consumers and rivals. By knowing the full scope of potential substitute products available online, retailers can keep their pricing and assortment strategies in line with rivals’ to reduce their risk of losing sales to rivals, and boost their top line, profitability and cost savings.

    The data insights give retailers the flexibility they need to align with online shoppers’ different needs across categories. As a result, retailers can use similarity matching to boost agility and gain a competitive advantage by adapting to online shoppers’ needs, winning their sales and fueling e-commerce growth.DataWeave’s similarity matching capability lets clients

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    2 Ochwat, Dan. Shopper study: Private brands purchased because they’re preferred. Store Brands. February 24, 2021
    3 Miranda, Leticia. Small businesses who pivoted to e-commerce saw record sales during Black Friday weekend. December 1, 2020.
    4 Charm, Tamara, Harrison Gillis, Anne Grimmelt, Grace Hua, Kelsey Robinson and Ramiro Sanchez Caballero. Survey: US consumer sentiment during the coronavirus crisis. McKinsey & Company. March 24, 2021.