The DataWeave Blog

Category: North America

  • 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 almost 14%. This is largely attributable to the numerous tariffs currently imposed on Chinese goods.
    • Mexico: Prices for products from Mexico have risen by 11%.
    • United States: Interestingly, even U.S.-sourced products show a 10% increase.
    Tariff related 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.

  • Beyond Basic Price Monitoring: Advanced Applications of Competitive Intelligence

    Beyond Basic Price Monitoring: Advanced Applications of Competitive Intelligence

    It’s up to senior leadership, whether you’re a Chief Strategy Officer, Pricing Executive, or Commercial Director, to think big picture about your company’s competitive intelligence strategy. For more junior team members, it’s easy to get caught in the “this is how we’ve always done it” mindset and continue to go through the motions of price monitoring.

    You don’t have that luxury—it’s up to you to find and implement new ways to move beyond basic price monitoring and usher your company into an era of achieving actionable insights through competitive intelligence. There is much more to gain from competitive data than simple price monitoring.

    How can retailers leverage clean, competitive data to uncover strategic insights beyond basic price comparisons? This article will help you shift your mindset from tactical monitoring to strategic insight generation. We’ll see how sophisticated analysis of clean and refined competitive data can reveal competitor strategies, regional and geographic opportunities, and overall market trends.

    It’s time to shift away from standard reporting, which should be left for your pricing owners and end users, and towards gaining competitive intelligence to shape your holistic company pricing strategy. With the right tools, you can make this shift a reality.

    Regional Price Intelligence

    One significant opportunity you should take advantage of is a greater understanding of regional price intelligence. Understanding the nuances that shape how products, categories, and other retailers’ prices according to geographical differences can set your company up to win customer trust and dollars at checkout.

    Understanding geographic and regional pricing strategies

    Geographic price intelligence helps leaders leverage market opportunities based on where sales are happening. Variations in how products and categories are priced across regions often reflect competitor tactics, local demand, and cost structures.

    Let’s consider an example that impacts a broad geography, such as the entire continental United States – egg prices. Eggs are a staple grocery item and are frequently a loss leader in stores. This means they are products priced below their cost specifically to draw customers into stores.

    However, Avian Flu outbreaks affecting millions of birds have become more common recently. These outbreaks drive the cost of eggs higher as flocks must be culled to prevent the spread of the disease. This means that retailers must act to maintain acceptable margins or losses without frightening away customers or losing their trust.

    Avian Flu has been especially bad in Iowa and California. Retailers in these regions face tough decisions during outbreaks. They need to figure out how to balance the high prices required to cover the supply shortages with maintaining consumer trust that this staple product will not be perceived as ‘overpriced.’ Customers expect retailers to be fair even when supply chain issues make it challenging to keep prices stable.

    Another example impacting the broader USA is credit card defaults. Credit card defaults are reaching levels unseen since the financial crisis of 2008. $46 billion worth of credit card balances were written off in the first nine months of 2024 alone. This unprecedented figure highlights the fact that many Americans are struggling financially. Higher-income earners continue to do ok, but lower-income families are feeling the pressure more than ever.

    Understanding the differences between the geographies you sell in can help you construct your pricing strategies better. This is especially true as consumers brace themselves for more anticipated economic hardship.

    Retailers must set realistic financial targets without overpricing their catalogs. Otherwise, they risk losing customers who would otherwise have bought their products. Competitive intelligence can help retailers understand how economic disparities impact core consumer bases.

    Pricing leaders can leverage insights around geographic variations in supply, demand, and competitor pricing to help in situations like these. With how important eggs are, changes to their price can spill over into other categories. And with credit card defaults affecting hundreds of thousands of Americans, having a way to dive into these topics can help shape overarching strategies.

    Customer perception is a recurring theme in competitive intelligence. It’s not only about the actual value your brand offers but the perceived value based on historical context, current events, and competition.

    Leveraging Regional Price Differences for Strategic Advantage

    On the topic of customer perception, there are strategic ways to use customer perception to your advantage. One of these is detecting cross-market arbitrage opportunities using competitive intelligence and actioning them.

    But what is cross-market arbitrage? It’s the practice of exploiting the differences in price across different markets or regions. As a retailer, you can use cross-market arbitrage to your advantage by finding disparities in market conditions and strategically pricing your products to entice customers or offer more value. These opportunities can be in demand, supply, or competitive pricing. Acting quickly in markets where frequent disruptions happen can drive your business forward.

    DataWeave’s advanced competitive intelligence tools can analyze regional market trends to help you respond to real-time local demand fluctuations or cost pressures.

    Local Market Dynamics

    Pricing isn’t a one-size-fits-all operation. Where and what you’re pricing truly matters. Pricing teams should take price zones into account when constructing pricing strategies. This is because pricing isn’t equivalent across locations; it’s localized. Understanding this fact is critical for category-specific considerations at the macro and micro levels.

    This map shows a retailer’s regional price differentials on a breakfast basket. With the ability to access and refine your data, you can better construct maps like this one to track local market dynamics. Determine where you need to differentiate prices based on locality, understand the strategic stance of your competitors, and plan if you start to see changes in competitive price zones.

    Map shows a retailer's regional price differentials on a breakfast basket

    Competitor Strategy Detection

    As a retailer, you should continuously monitor your competitors, whether they’re succeeding or stagnating. One example of a major retailer that is seeing growth even during this challenging economic time is Costco. Costco is an interesting case because they do not have stores in every major city or even in every state.

    Costco has its brand strategy down, and it is tied to the pricing strategy. Costco has committed to its customers to provide quality items at competitive prices, and they’ve delivered even in a volatile economy. Costco has managed to maintain competitive prices on core merchandise and make strategic pricing adjustments on items that matter most to members. Their private label brand, Kirkland Signature, highlights their value-first approach. They continue to lead with price reductions like:

    • Organic Peanut Butter: $11.49 → $9.99
    • Chicken Stock: $9.99 → $8.99
    • Sauvignon Blanc: $7.49 → $6.99

    Costco has figured out how to balance premium offerings for cost-conscious consumers with standardly priced items filling the shopper’s basket. This demonstrates that they have a pricing strategy that relies on competitive intelligence and market trends.

    With the correct data and tools, any retailer can conduct research to discover more about their competitors and gain usable insights into their implemented pricing strategies. Once established, this can act as an early warning signal so you can take action.

    For example, understanding whether a retailer operates with a stable Everyday Low Price (EDLP) strategy or a more dynamic High/Low pricing approach is crucial when building and maintaining the integrity of your pricing strategy.

    Data should be able to show you things like:

    • When holiday price decreases start to accelerate
    • How quickly a retailer responds to cost increases (especially at the category or item level)
    • The cadence of seasonal campaigns and their impact on pricing behavior

    When we move beyond the numbers, these patterns tell a story about how to win in today’s competitive retail landscape. After all, pricing isn’t just a standard reporting tactic. In its truest form, it’s a strategy rooted in understanding the bigger picture of your consumers, competition, and the economy.

    Actionable Intelligence Framework

    With a practical system to turn insights into action, your company’s pricing strategy is much more likely to drive actual results. Merely collecting data and churning out out-of-date reports won’t cut it. Instead, begin to identify patterns and insights for accurate competitive intelligence. Use this simple framework to start setting up a comprehensive competitive intelligence process.

    • Setting up monitoring systems: Leverage technology to monitor and aggregate data on your competition, market trends, and consumer behavior. Ensure the system chosen can clean and refine the data along the way so it’s ready to be analyzed.
    • Creating action triggers: Define clear thresholds and triggers based on key insights. These can be things like price changes of a certain amount, competitor moves, assortment changes, or regional and geographic trends. These triggers should prompt specific, pre-planned actions for your team to capitalize on opportunities.
    • Response protocol development: Change management is easier with a plan. Work on building out and training your teams on protocols for specific triggers. When something arises, they know the protocol to take advantage of the opportunity or mitigate the challenge effectively.
    • Performance measurement: Measure the impact of your team’s protocol-based actions with the help of pre-determined KPIs and then hone your approach to competitive intelligence based on the results.

    Competitive Intelligence at Your Fingertips

    Shifting from a latent standard reporting and price monitoring mindset to a growth mindset centered around competitive intelligence doesn’t need to be a struggle. The key is to lean on the tools that will accelerate your company’s journey to finding the right insights and putting action behind them quickly.

    Start by conducting a competitive intelligence maturity assessment to evaluate your organization’s current state and identify areas for improvement. Then, create a capability development roadmap for your company to track efficacy and progress toward your goal.

    Want to talk to the experts in competitive pricing intelligence? Click here to speak with the DataWeave team!

  • 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!

  • 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.

  • 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!

  • 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 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!

  • 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!

  • 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)

  • How DataWeave Enhances Transparency in Competitive Pricing Intelligence for Retailers

    How DataWeave Enhances Transparency in Competitive Pricing Intelligence for Retailers

    Retailers heavily depend on pricing intelligence solutions to consistently achieve and uphold their desired competitive pricing positions in the market. The effectiveness of these solutions, however, hinges on the quality of the underlying data, along with the coverage of product matches across websites.

    As a retailer, gaining complete confidence in your pricing intelligence system requires a focus on the trinity of data quality:

    • Accuracy: Accurate product matching ensures that the right set of competitor product(s) are correctly grouped together along with yours. It ensures that decisions taken by pricing managers to drive competitive pricing and the desired price image are based on reliable apples-to-apples product comparisons.
    • Freshness: Timely data is paramount in navigating the dynamic market landscape. Up-to-date SKU data from competitors enables retailers to promptly adjust pricing strategies in response to market shifts, competitor promotions, or changes in customer demand.
    • Product matching coverage: Comprehensive product matching coverage ensures that products are thoroughly matched with similar or identical competitor products. This involves accurately matching variations in size, weight, color, and other attributes. A higher coverage ensures that retailers seize all available opportunities for price improvement at any given time, directly impacting revenues and margins.

    However, the reality is that untimely data and incomplete product matches have been persistent challenges for pricing teams, compromising their pricing actions. Inaccurate or incomplete data can lead to suboptimal decisions, missed opportunities, and reduced competitiveness in the market.

    What’s worse than poor-quality data? Poor-quality data masquerading as accurate data.

    In many instances, retailers face a significant challenge in obtaining comprehensive visibility into crucial data quality parameters. If they suspect the data quality of their provider is not up to the mark, they are often compelled to manually request reports from their provider to investigate further. This lack of transparency not only hampers their pricing operations but also impedes the troubleshooting process and decision-making, slowing down crucial aspects of their business.

    We’ve heard about this problem from dozens of our retail customers for a while. Now, we’ve solved it.

    DataWeave’s Data Statistics and SKU Management Capability Enhances Data Transparency

    DataWeave’s Data Statistics Dashboard, offered as part of our Pricing Intelligence solution, enables pricing teams to gain unparalleled visibility into their product matches, SKU data freshness, and accuracy.

    It enables retailers to autonomously assess and manage SKU data quality and product matches independently—a crucial aspect of ensuring the best outcomes in the dynamic landscape of eCommerce.

    Beyond providing transparency and visibility into data quality and product matches, the dashboard facilitates proactive data quality management. Users can flag incorrect matches and address various data quality issues, ensuring a proactive approach to maintaining the highest standards.

    Retailers can benefit in several ways with this dashboard, as listed below.

    View Product Match Rates Across Websites

    The dashboard helps retailers track match rates to gauge their health. High product match rates signify that pricing teams can move forward in their pricing actions with confidence. Low match rates would be a cause for further investigation, to better understand the underlying challenges, perhaps within a specific category or competitor website.

    Our dashboard presents both summary statistics on matches and data crawls as well as detailed snapshots and trend charts, providing users with a holistic and detailed perspective of their product matches.

    Additionally, the dashboard provides category-wise snapshots of reference products and their matching counterparts across various retailers, allowing users to focus on areas with lower match rates, investigate underlying reasons, and develop strategies for speedy resolution.

    Track Data Freshness Easily

    The dashboard enables pricing teams to monitor the timeliness of pricing data and assess its recency. In the dynamic realm of eCommerce, having up-to-date data is essential for making impactful pricing decisions. The dashboard’s presentation of freshness rates ensures that pricing teams are armed with the latest product details and pricing information across competitors.

    Within the dashboard, users can readily observe the count of products updated with the most recent pricing data. This feature provides insights into any temporary data capture failures that may have led to a decrease in data freshness. Armed with this information, users can adapt their pricing decisions accordingly, taking into consideration these temporary gaps in fresh data. This proactive approach ensures that pricing strategies remain agile and responsive to fluctuations in data quality.

    Proactively Manage Product Matches

    The dashboard provides users with proactive control over managing product matches within their current bundles via the ‘Data Management’ panel. This functionality empowers users to verify, add, flag, or delete product matches, offering a hands-on approach to refining the matching process. Despite the deployment of robust matching algorithms that achieve industry-leading match rates, occasional instances may arise where specific matches are overlooked or misclassified. In such cases, users play a pivotal role in fine-tuning the matching process to ensure accuracy.

    The interface’s flexibility extends to accommodating product variants and enables users to manage product matches based on store location. Additionally, the platform facilitates bulk match uploads, streamlining the process for users to efficiently handle large volumes of matching data. This versatility ensures that users have the tools they need to navigate and customize the matching process according to the nuances of their specific product landscape.

    Gain Unparalleled Visibility into your Data Quality

    With DataWeave’s Pricing Intelligence, users gain the capability to delve deep into their product data, scrutinize match rates, assess data freshness, and independently manage their product matches. This approach is instrumental in fostering informed and effective decisions, optimizing inventory management, and securing a competitive edge in the dynamic world of online retail.

    To learn more, reach out to us today!

  • 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!

  • 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!

  • 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!

  • 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

    _____________

    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!

  • 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. 

  • 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.

  • 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.

  • 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.

  • 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!

  • 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.         

  • 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.