The DataWeave Blog

Category: Product Content

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

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

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

From Cost Shock to Chronic Uncertainty

Tariffs are no longer just one-off headlines; they’ve become an unpredictable, ongoing variable in the global marketplace. The true challenge isn’t always the duty rate itself, but the constant whiplash of not knowing if, when, or how much that duty will change. This pervasive uncertainty is having a tangible impact:
- Market Uncertainty: Tariff talk alone disrupts planning and fuels market instability.
- Operational cost inflation: Shifting trade rules raise expenses across sourcing, freight, and distribution.
- Compromised SKU-level Margin: The profitability of individual products is under constant threat.
- Shrinkflation: Brands shrink product quantities to mask rising costs, risking consumer trust.
Unpredictable Competitive Response: Delaying price moves while watching competitors can erode margins as much as tariffs.

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

The Tariff Math No One Can Afford to Get Wrong

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

Step 1: Harmonized System (HS) Code
- What it is: A six- to ten-digit classifier that drills down to product sub-types.
- Why it matters: A single digit change can shift an item into a higher-tariff bracket.
Step 2: Country of Origin
- What it is: The nation in which the imported item was made.
- Why it matters: Mis-tagging the origin can lead to mis-pricing and inaccurate margin calculations.
Step 3: Trade-Agreement Overlay
- What it is: Differentiation between the World Trade Organization (WTO) baseline tariffs and special trade agreements (e.g., USMCAUnited States-Mexico-Canada Agreement).
- Why it matters: The same HS code can result in significantly different duties, up to a 10% swing, depending on the originating country (see the example below).
This isn’t just about paying the correct duty; it’s about safeguarding your bottom line in a global marketplace where every digit and every designation carries substantial weight.

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

Hard Numbers: Where Prices Are Already Climbing

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

The intricate dance of HS codes, country of origin, and trade agreements directly translates into the prices consumers see. And the data doesn’t lie. Below, we delve into the hard numbers: where prices are already climbing, as illuminated by DataWeave’s latest digital shelf monitoring, showing significant import-driven price inflation by source country.
- China: Products sourced from China are up 5%. This is largely attributable to the numerous tariffs currently imposed on Chinese goods.
- Mexico: Prices for products from Mexico have risen by 3%.
- United States: Interestingly, even U.S.-sourced products show a 3% increase.
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.
June 13, 2025
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.

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.

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.

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.

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.

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.

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!
November 14, 2024
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.

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.

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.

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.

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.

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.

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.

November 8, 2024
DataWeave’s AI Evolution: Delivering Greater Value Faster in the Age of AI and LLMs
In retail, competition is fierce, and in its ever-evolving landscape, consumer expectations are higher than ever.

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

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

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

In this first piece, we’ll offer a snapshot of how DataWeave aggregates and analyzes billions of publicly available data points to help businesses stay agile, informed, and ahead of the curve. These fall into four broad categories:
- Product Matching
- Attribute Tagging
- Content Analysis
- Promo Banner Analysis
- Other Specialized Use Cases
Product Matching

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

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

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

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

Here’s how it works:

Text Preprocessing

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

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

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

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

Embeddings

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

Classification

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

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

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

Including tags for synonyms, variants, and long-tail keywords (e.g., “denim” and “jeans”) improves the matching process by recognizing different terms used for similar products. Metadata tags categorize similar items according to SKU numbers, manufacturer details, and other identifiers.

Altogether, these capabilities provide high-quality product matches and valuable metadata for retailers to classify their products and compare their product assortment to competitors.

User-Generated Content (UGC) Analysis

Customer reviews and ratings are rich sources of information, enabling brands to gauge consumer sentiment and identify shortcomings regarding product quality or service delivery. However, while informative, reviews constitute unstructured “noisy” data that is actionable only if parsed correctly.

Here’s where DataWeave’s UGC analysis capability steps in.
- Feature Extractor: Automatically pulls specific product attributes mentioned in the review (e.g., “battery life,” “design” and “comfort”)
- Feature Opinion Pair: Pairs each product attribute with a corresponding sentiment from the review (e.g., “battery life” is “excellent,” “design” is “modern,” and “comfort” is “poor”)
- Calculate Sentiment: Calculates an overall sentiment score for each product attribute
The final output combines the information extracted from each of these features, which looks something like this:
- Battery life is excellent
- Design is modern
- Not satisfied with the comfort
The algorithm also recognizes spammy reviews and distinguishes subjective reviews (i.e., those fueled by emotion) from objective ones.

Promo Banner Analysis

Our image processing tool can interpret promotional banners and extract information regarding product highlights, discounts, and special offers. This provides insights into pricing strategies and promotional tactics used by other online stores.

For example, if a competitor offers a 20% discount on a popular product, you can match or exceed this discount to attract more customers.

The banner reader identifies successful promotional trends and patterns from competitors, such as the timing of discounts, frequently promoted product categories or brands, and the duration of sales events. Ecommerce stores can use this information to optimize their promotion strategies, ensuring they launch compelling and timely offers.

Other Specialized Use Cases

While these generalized AI tools are highly useful in various industries, we’ve created other category—and attribute-specific capabilities for specialty goods (e.g., those requiring certifications or approval by federal agencies) and food items. These use cases help our customers adhere to compliance requirements.

Certification Mark Detector

This detector lets retailers match items based on official certification marks. These marks represent compliance with industry standards, safety regulations, and quality benchmarks.

Example:
- USDA Organic: Certification for organic food production and handling
- ISO 9001: Quality Management System Certification
By detecting these certification marks, the system can accurately match products with their certified counterparts. By identifying which competitor products are certified, retailers can identify products that may benefit from certification.

Nutrition Fact Table Reader

Product attributes alone are insufficient for comparing food items. Differences in nutrition content can influence product category (e.g., “health food” versus regular food items), price point, and consumer choice. DataWeave’s nutrition fact table reader scans nutrition information on packaging, capturing details such as calorie count, macronutrient distribution (proteins, fats, carbohydrates), vitamins, and minerals.

The solution ensures items with similar nutritional profiles are correctly identified and grouped based on specific dietary requirements or preferences. This helps with price comparisons and enables eCommerce stores to maintain a reliable database of product information and build trust among health-conscious consumers.

Building Next-Generation Competitive and Market Intelligence

Moving forward, breakthroughs in generative AI and LLMs have fueled substantial innovation, which has enabled us to introduce powerful new capabilities for our customers.

These include:
- Building Enhanced Products, Solutions, and Capabilities: Generative AI and LLMs can significantly elevate the performance of existing solutions by improving the accuracy, relevance, and depth of insights. By leveraging these advanced AI technologies, DataWeave can enhance its product offerings, such as pricing intelligence, product matching, and sentiment analysis. These tools will become more intuitive, allowing for real-time updates and deeper contextual understanding. Additionally, AI can help create entirely new solutions tailored to specific use cases, such as automating competitive analysis or identifying emerging market trends. This positions DataWeave to remain at the forefront of innovation, offering cutting-edge solutions that meet the evolving needs of retailers and brands.
- Reducing Turnaround Time (TAT) to Go-to-Market Faster: Generative AI and LLMs streamline data processing and analysis workflows, enabling faster decision-making. By automating tasks like data aggregation, sentiment analysis, and report generation, AI dramatically reduces the time required to derive actionable insights. This efficiency means that businesses can respond to market changes more swiftly, adjusting pricing or promotional strategies in near real-time. Faster insights translate into reduced turnaround times for product development, testing, and launch cycles, allowing DataWeave to bring new solutions to market quickly and give clients a competitive advantage.
- Improving Data Quality to Achieve Higher Performance Metrics: AI-driven technologies are exceptionally skilled at cleaning, organizing, and structuring large datasets. Generative AI and LLMs can refine the data input process, reducing errors and ensuring more accurate, high-quality data across all touchpoints. Improved data quality enhances the precision of insights drawn from it, leading to higher performance metrics like better product matching, more accurate price comparisons, and more effective consumer sentiment analysis. With higher-quality data, businesses can make smarter, more informed decisions, resulting in improved revenue, market share, and customer satisfaction.
- Augmenting Human Bandwidth with AI to Enhance Productivity: Generative AI and LLMs serve as powerful tools that augment human capabilities by automating routine, time-consuming tasks such as data entry, classification, and preliminary analysis. This allows human teams to focus on more strategic, high-value activities like interpreting insights, building relationships with clients, and developing new business strategies. By offloading these repetitive tasks to AI, human productivity is significantly enhanced. Employees can achieve more in less time, increasing overall efficiency and enabling teams to scale their operations without needing a proportional increase in human resources.
In our ongoing series, we will dive deep into each of these capabilities, exploring how DataWeave leverages cutting-edge AI technologies like Generative AI and LLMs to solve complex challenges for retailers and brands.

In the meantime, talk to us to learn more!
September 18, 2024
A Guide to Digital Shelf Metrics for Consumer Brands
Our world is increasingly going online. We work online, socialize online, and shop online every day. As a consumer brand, you need to ensure complete awareness of your brand’s online presence across eCommerce platforms, search engines, and media.

Only by deeply understanding the customer journey can you ensure that your product is reaching your ideal customers and maximizing your brand’s market share. You need data to intrinsically understand your customer journey and make changes where you’re lacking.

As the old adage goes: ‘You can’t manage what you don’t measure.’

You need digital shelf metrics to measure and start benchmarking your buyer’s journey. To find several of these types of key performance indicators (KPIs), you need a digital shelf analytics solution. These platforms allow you to track various metrics along the path to purchase from the awareness stage to the post-purchase phase across the entire internet, helping to inform online and offline sales strategies.

Digital shelf analytics will help you gain insights into how your brand is doing versus the competition, which areas are lagging behind in historical performance, and what activities are driving sales. There are innumerable ways in which you can leverage these valuable insights. But how do you know which KPIs to start tracking with your digital shelf analytics solution?

Here, we’ve summarized the top metric types your peers report, track and base their decisions on.

With these KPIs in hand, consumer brands like yours can ensure that their products are consistently visible and appealing to their target audience across online marketplaces, ultimately enhancing conversion rates, market share, and profitability.

Read this guide to learn more about the top digital shelf metrics consumer brands are tracking and how to use them in your own strategy.

1. Share of Search

Share of Search (SoS) is a KPI in digital shelf analytics that measures how frequently a consumer brand’s products appear in search results on eCommerce platforms relative to the competition for specific keywords. A good digital shelf analytics solution will be able to show this metric across all the top marketplaces and retailers, such as Amazon and Walmart, but also more niche marketplaces for industry-specific selling.

This metric provides brands with a quantifiable way to measure how frequently their products are being “served up” to customers on online marketplaces. Essentially, it measures visibility and discoverability.

With Share of Search on DataWeave, you can slice and dice your data in innumerable ways. These are a few important views you can see:
- Aggregated SoS
- Organic and Sponsored SoS scores
- SoS scores across brands, retailers, keywords, cities
- Historical SoS score trends
Once you have benchmarked your SoS and category presence relative to your competition, you need to start interpreting the data. Here are some questions you can ask yourself to help interpret your findings:
- Which of my key categories have the lowest SoS score?
- Which products feature low on search results because they are out of stock?
- Are my competitors’ products faring better due to sponsored searches?
- Is my SoS low due to poor content quality?
With insights in hand, you will know which actions to take to drive the biggest impact. For example, you could increase sponsored search results or improve organic reach by optimizing product pages.

Understanding your SoS is essential to maximizing the awareness phase of your customer journey. It will help you improve your brand visibility and increase product conversions through better search and category presence.

2. Share of Media

Share of Media (SoM) is a KPI that is just as impactful, if not more so, than the SoS metric. However, only a limited number of brands track it or use it to drive strategic action. This makes it a perfect opportunity for brands looking to get an edge on the competition.

But what is SoM in digital shelf analytics? Essentially, it’s a way of measuring retail media advertising activities like brand-sponsored banners, listings, videos, ads, and promotions that sometimes blend into search results. The main types of retail media advertising exist in two categories: banner advertising and sponsored listings.

Banner advertising involves strategically placing designed banners within websites and search listings. These banners raise brand awareness and drive traffic to online storefronts.

Sponsored listings are paid placements within search results on search engines or eCommerce platforms. They are prioritized based on the total bid amount and the product’s relevance. These paid listings are marked with “sponsored” or “ad.”

It’s important to run these types of advertising campaigns on eCommerce platforms to gain customer visibility. In fact, “some 57% of US consumers started their online shopping searches on Amazon as of Q2 2023.” If you aren’t showing up, paying for placement can help.

These listings serve to enhance your brand’s overall visibility, help you gain more precise reach, increase conversions, and drive better brand awareness and recall with your customers.

These efforts aren’t free, however, so measuring their effectiveness is critical not only to gain all the listed benefits but to also not waste your valuable marketing budget. The SoM KPI can help a consumer brand answer questions like:
- Where are the opportunities to increase paid ads?
- Which categories could benefit from a promotional boost or a strategic and streamlined allocation of ad spend?
- Which of my competitors have active banners and what is their share of media by keyword?
- How has my ad spend trended historically in comparison to my competitor?
DataWeave’s digital shelf analytics (DSA) is among the first providers to offer Share of Media KPI tracking and analysis. This is because it requires advanced, multi-modal AI to gather, view, and aggregate listings that encompass text, images, and video. With Share of Media tracking facilitated by DataWeave, consumer brands can track and analyze the effectiveness of their own promotional investments as well as those of their competitors.

3. Content Quality

The content quality metric measures how well your product content adheres to the retailer’s specific guidelines, which are in place to steer traffic and sales on their sites.

With the help of a DSA platform’s AI and ML capabilities, you can measure different elements of your product detail pages (PDPs), such as titles, descriptions, images, videos, and even customer reviews. You need to know which elements are missing, where they are missing, and which ones are negatively affecting sales so you can take corrective action.

Did you know that the average cart abandonment rate is 69.99%? The quality of your content can significantly impact this number. Ensuring that your content is high-quality will help influence product discoverability, customer engagement, and conversion rates. It will also help position you ahead of the competition. If your content quality is poor, you may find yourself with lower search rankings, a higher return rate, and more abandoned carts.

Here are some questions you can answer with the help of the content quality digital shelf metric:
- Is my product content at a retail site exactly what was syndicated?
- Are there any retailer initiated changes to my product content?
- Are my product content updates reflected on the retailer platforms?
- How well does my product content comply with the retailer guidelines?
- How do I optimize my product content for enhanced discoverability and conversion?
DataWeave’s content quality digital shelf analysis helps consumer brands ensure that product content on eCommerce platforms is high-quality and benchmark their product listings against the competition. It does this through a combination of AI-driven quality analysis and by presenting brands with actionable recommendations. These optimized suggestions are based on the top-performing products so you can focus your valuable time on the areas that will drive the biggest impact.

4. Pricing & Promotions

Your customers can easily shop around to find the best price for the product you’re selling. If your competitor is selling it cheaper, you’ll lose that sale.

That’s why it’s essential to understand the pricing and promotional landscape for each of your products and categories. This can be a challenge, especially if it’s a common product or comes in multiple pack sizes or variants.

It’s equally important to track pricing and promotions even at individual, physical stores. Doing so will allow you to remain competitive and responsive to local market dynamics by tailoring your pricing strategies based on regional competition. You don’t want your products to be overpriced (lost sales) or underpriced (lost profit) in specific markets.

Harmonizing insights when operating an omnichannel consumer brand is extremely difficult without the aid of a digital shelf analytics solution. Insights need to be aggregated between desktop sites, mobile sites, and mobile applications, as well as from physical storefronts.

Questions you can answer with the help of the pricing & promotions digital shelf metric include:
- How do my product prices and promotions compare to my competitors?
- How consistent is my product pricing across retail websites?
- How does my product pricing vary across regions, ZIPs, and stores?
- How do price changes influence my sales numbers?
- Are there regional differences in pricing and promotion effectiveness?
DataWeave’s digital shelf analytics platform stands out with its sophisticated location-aware capabilities, which enable the aggregation and analysis of localized pricing and promotions. The platform defines locations based on a range of identifiers, such as latitudes and longitudes, regions, states, ZIP codes, or specific store numbers.

The platform can also extract promotional information, such as credit card-based or volume-based promotions. You can see variances across retailers, split by price groups, brands, and competitors. DataWeave specializes in enabling brands to conduct in-depth analyses across a wide array of attributes so you can answer just about any pricing or promotional question you have.

5. Availability

The availability KPI in digital shelf analytics measures the in-stock and availability rates for a brand’s products across eCommerce and physical locations. Similar to the pricing and promotions metric, it relies heavily on location awareness, down to individual stores. Measuring both online availability and offline in-stock rates will help you understand the big picture and take more informed replenishment action.

When you start leveraging the availability KPI with the help of digital shelf analytics, you can improve inventory management, boost product discoverability, increase the frequency with which your online product listings convert, and generally drive more sales. This KPI is essential for ensuring your customers can always find and buy the products they want.

With the availability KPI, you can start answering questions like:
- What is my overall in-stock rate?
- Which of my products frequently go out of stock?
- How does product availability vary across different regions and stores?
- What is the impact of availability on my conversion rates?
- Are there any seasonal trends in product availability that I need to address?
- How quickly are we resolving stockout issues across different locations?
- What are my biggest opportunities to reduce stockouts?
DataWeave enables consumer brands to track their product availability metric through automated data collection from various eCommerce platforms in conjunction with physical in-stock rates. The platform provides granular, store-level insights so you can understand regional stock variations and optimize inventory distribution. By tracking historical availability data, you can identify seasonal patterns and predict future demand to pre-empt stockout issues. All of this can be configured with automatic notifications to alert you when there has been a stockout event or when a low stock threshold has been passed, facilitating timely replenishment.

6. Ratings & Reviews

The final KPI in our guide is the ratings & reviews digital shelf metric. Consumers rely heavily on genuine feedback from their peers and refer to star ratings, posted comments, and uploaded pictures to inform their buying decisions. This KPI analyzes the impact of customer feedback and reviews on your products’ performance across eCommerce platforms so you can measure overall brand perception and isolate areas of opportunity.

This metric does something other digital shelf metrics don’t; it can inform your product strategy. It can help you identify repeat complaints that your product team can address with the manufacturer or use for the design of future products.

Some questions you can answer with this powerful KPI include:
- What is the overall customer sentiment towards my products based on ratings and reviews?
- Which product features are frequently mentioned positively or negatively by customers?
- How do my product ratings and reviews compare to those of my competitors?
- Are there common issues or complaints that need to be addressed to improve customer satisfaction?
- Which products have the highest and lowest ratings, and why?
With DataWeave’s digital ratings and reviews feature, you can keep a pulse on customer sentiment to take short-term action as well as decide long-term strategy. You can leverage reviews to influence product perception, refine products, and enhance overall customer satisfaction.

DataWeave’s Digital Shelf Metrics

Each one of these metrics is interconnected and collectively influences a brand’s success. For instance, improving content quality and earning higher ratings can significantly enhance your product’s visibility in search results, thereby boosting the Share of Search digital shelf metric. By focusing on a comprehensive approach that integrates these metrics, brands can ensure their products are consistently visible, competitively priced, well-reviewed, and readily available.

DataWeave gives consumer brands the means to execute a holistic digital shelf strategy. From a single portal, track and improve digital shelf metrics like Share of Search, Share of Media, Pricing and promotions, Availability, and Ratings and Reviews.

Our solutions help audit and optimize the most critical KPIs that drive sales and market share for brands so you can stay competitive in a dynamic digital landscape and foster long-term customer satisfaction.

Ready to get started? Schedule a call with a specialist to see how it can work for your brand.
August 21, 2024
Insights on Pricing and Visibility of Leading Consumer Brands During Prime Day 2024
Amazon Prime Day 2024 saw U.S. shoppers spending a staggering $14.2 billion online during the two-day event—an 11% increase from last year. This surge in spending reflects a significant shift in consumer behavior and presents a wealth of insights for brands and retailers alike.

Unlike last year’s focus on essentials, Prime Day 2024 saw Americans enthusiastically embracing both necessities and discretionary purchases. The Consumer Electronics and Health & Beauty categories, for example, experienced a notable uptick in interest, driven by major retailers slashing prices across CPG and Grocery segments, amid other reasons. Check out our first article in the Prime Day series 2024, analyzing retail insights across categories during the event.

This year, small businesses gained unprecedented visibility on Amazon, pushing relatively new brands into visibility.

At DataWeave, we recognize the critical importance of understanding these market dynamics for brands navigating the competitive eCommerce landscape. To provide actionable insights, we conducted an extensive analysis of over 47,000 SKUs across key categories before and during Amazon during Prime Day 2024. Our study delves into:
- Pricing strategies: How did brands adjust their discounts to capitalize on the Prime Day frenzy?
- Share of Search: Which brands achieved the highest visibility for major search keywords?
Dive into these insights below to uncover how brands performed during Amazon Prime Day 2024, and learn how you can leverage these findings to enhance your brand’s digital shelf performance.

Our Findings

Most brands offered substantial discounts before Prime Day, then added smaller discounts during the event. This strategy creates a perception of value while still allowing room for Prime Day-specific deals. To understand the real value offered by brands, we conducted an extensive analysis of brand performance, examining both pricing strategies and visibility on the platform. Our approach focuses on two key metrics:
1. Discounts: We analyzed both the Absolute Discount (total markdown relative to MSRP a week before Prime Day) and the Additional Discount (the price reduction during Prime Day compared to the week before).
2. Share of Search (SoS): We examined the visibility of brands in the top 20 search results. We also separately tracked this metric for organic and sponsored search results.
Let’s dive into the category and brand specific insights:

Consumer Electronics

Once again, in 2024, the Consumer Electronics category dominated discounts. Amazon’s own brands lead with the highest average Absolute Discount (44.2%) and a significant Additional Discount (12.5%), showcasing its aggressive push for Prime Day.

In a surprising twist, Amazon’s homepage wasn’t dominated by its own brands. Instead, tech giants like Apple and Samsung took centre stage. Despite this, Amazon’s own brands offered significant discounts across electronics products, including Amazon Kindle, Fire TVs, Fire TV Sticks, Echo Dot, and more, aiming to capture market share via markdowns.

Soundcore (earphone audio products brand) offered the highest discount during Prime Day, at 30.10%. Other headphone, earbuds, and wireless headphone brands including Sony, Beats, JBL, and more also offered significant discounts.

Premium brands like Apple (17.90% Absolute, 9.00% Additional) and Bose (23.10% Absolute, 16.00% Additional) offered relatively modest discounts, aligning with their brand positioning, but also taking advantage of the Prime Day frenzy.

Share of Search Insights in Consumer Electronics

JBL emerged as the standout performer, with the most significant increase in SoS, jumping from 14.3% pre-event to 25.8% during Prime Day, driven entirely by organic growth. Beats also saw a remarkable rise, increasing from 2.8% to 12.8%, again through organic listings only. Samsung maintained its strong presence, growing from 18.6% to 26.8%, with most of its growth influenced by increased ad spend.

Apple, despite already having a high pre-event SoS, managed to increase its share further from 23.0% to 31.0%, with some contribution via sponsored ads. LG saw a substantial increase from 1.3% to 6.9%, primarily through sponsored listings, opting for an inorganic approach to drive visibility during the sale.

Amazon and its AmazonBasics brand both saw notable increases in SoS, relying solely on organic growth. This is, of course, not surprising since Amazon controls its organic ranking algorithm.

Interestingly, some brands experienced decreases in SoS. Sony, Motorola, and Hisense all saw reductions in their share, with Hisense’s decline coming entirely from a reduction in sponsored listings.

Key Takeaway: Prime Day 2024 saw a significant reshuffling of brand visibility in the Consumer Electronics category. While some established brands like JBL, Beats, Samsung, and Apple strengthened their positions through a mix of organic and sponsored growth, others faced increased competition for consumer attention. The event highlighted the importance of a balanced approach to visibility, with successful brands leveraging both organic search optimization and strategic use of sponsored listings to maximize their presence during this high-traffic period.

Apparel

In the Apparel category, Adidas led with the highest Absolute Discount (27.2%) and a significant Additional Discount (9.8%). Value brands like Hanes (innerwear brand) and Anrabess offered substantial discounts, while Amazon Essentials maintained high discounts across the board (16.5% Absolute, 15.3% Additional).

Some brands like Cupshe (swimwear and vacation apparel brand) offered relatively lower additional markdowns. Meanwhile CRZ Yoga (athleisure brand) did not offer additional markdowns on Prime Day.

Share of Search Insights in Apparel

Gildan (activewear brand) emerged as the top performer in terms of SoS growth, increasing from 8.1% pre-event to 12.1% during Prime Day, driven entirely by organic growth. CRZ Yoga (an athleisure apparel brand) and Dokotoo (women’s casualwear brand) also saw significant increases in their SoS, rising by 2.8 and 2.3 percentage points respectively, again through organic listings only.

Amazon Essentials continued to perform well, increasing its visibility from 7.0% to 9.1%, aligning with its competitive pricing strategy. Coofandy also saw a notable increase, growing from 7.8% to 9.9%.

Interestingly, some brands that were previously highlighted for growth actually experienced decreases in SoS. Automet (clothing & accessories brand) saw a slight decline from 12.5% to 12.1%, while Anrabess (women’s fashion brand) dropped from 15.8% to 14.5%. Cupshe (swimwear brand) experienced the most significant decrease, falling from 10.6% to 5.5%.

Adidas, despite leading in discounts, saw only a modest increase in SoS from 7.0% to 8.0%. Notably, none of the brands visible in the top search results utilized sponsored listings, with all changes in SoS coming from organic growth or decline. This indicates a lack of maturity in this category in leveraging retail media.

Key Takeaway: Prime Day 2024 in the apparel category showcased the importance of organic search optimization. While some brands like Gildan and CRZ Yoga significantly improved their visibility, others faced challenges in maintaining their pre-event positions. The absence of sponsored listings across all brands highlights a unique dynamic in the apparel category, where organic search performance appears to be the primary driver of visibility during high-traffic events like Prime Day.

This suggests that Apparel brands may need to focus more on SEO strategies and organic content optimization to maximize their presence during major shopping events, rather than relying on paid promotions. On the other hand, smartly leveraging retail media to boost visibility can give apparel brands a competitive edge.

Health & Beauty

The Health & Beauty category this year got a push thanks to Amazon’s subscription offering. Prime members who subscribed for regular usage products like toothpaste and health aids or medicines availed higher discounts.

Amid Health & Beauty brands, Neutrogena led with the highest Absolute Discount (32.7%) and a significant Additional Discount (11.7%). Sun Bum moisturizers & sunscreen (23.3%) and Viking Revolution (23.1%) offered the highest Additional Discounts, indicating a strong Prime Day focus.

Premium brands like L’Oreal Paris and Philips Sonicare offered moderate discounts, balancing promotions with their intended brand image.

Share of Search Insights in Health & Beauty

Banana Boat (sunscreen brand) emerged as the standout performer, seeing the largest increase in SoS from 6.5% to 13.4%, achieved entirely through organic growth. Nyx Professional Makeup also saw a significant jump, rising from 3.9% to 8.9%, again solely through organic listings.

Contrary to previous analysis, e.l.f. actually experienced substantial growth, increasing from 9.0% to 13.1% SoS, with a strong focus on organic growth (4.4%) slightly offset by a minor decrease in sponsored listings (-0.2%).

Neutrogena maintained its strong performance, aligning with its aggressive discounting strategy, as its SoS increased from 14.6% to 18.5% through organic growth. Colgate also saw a notable increase from 11.0% to 13.7% SoS.

Interestingly, some brands employed a mixed strategy. Dove and Garnier saw overall increases in SoS, but achieved this through different means. Dove relied heavily on sponsored growth, while Garnier offset a decrease in organic listings with strong sponsored content growth.

Contrary to previous observations, Oral-B experienced a decrease in SoS from 18.5% to 15.3%, entirely in organic listings. Without any additional spend on sponsored listings to compensate, it lost significant ground in its visibility. Other brands facing significant declines include Tresemme, OGX, Philips Sonicare, and most notably, Viking Revolution, which dropped from 17.2% to 10.7% in its SoS.

Key Takeaway: The Health & Beauty category during Prime Day 2024 showcased a diverse range of strategies and outcomes. While some brands like Banana Boat and Nyx Professional Makeup achieved significant visibility gains through organic growth, others like Dove and Garnier relied more on sponsored content.

The success of e.l.f. and Neutrogena in aligning discounting strategies with increased visibility stands in contrast to the challenges faced by previously strong performers like Oral-B and Viking Revolution. This varied landscape shows the fierce competition in the category and the need for brands to employ multi-faceted strategies that balance organic optimization, sponsored content, and competitive pricing to succeed in high-stakes events like Prime Day.

Brand Strategies and Future Implications

Our analysis reveals several key trends:
- Brand Positioning Matters: Premium brands like Apple and Bose maintained their positioning with modest discounts, while value-oriented brands like Soundcore and Hanes offered deeper cuts to attract price-sensitive shoppers.
- Visibility vs. Discounting: Some brands, particularly in the Consumer Electronics category, prioritized increasing their visibility (Share of Search) over offering steep discounts. This strategy suggests a focus on long-term visibility and brand perception rather than short-term sales boosts.
- Category-Specific Approaches: Apparel brands uniquely relied on organic search visibility, eschewing sponsored listings entirely. In contrast, several Health & Beauty brands leveraged sponsored content significantly to boost their presence.
- Emerging Brand Opportunities: Lesser-known brands, especially in the Apparel and Health & Beauty categories, used Prime Day as a launchpad to increase their visibility, often outpacing established names in Share of Search growth.
- Amazon’s Dual Strategy: As both a platform and a brand, Amazon showcased its ability to offer deep discounts on its own products while also providing a stage for other brands to shine.
Stay tuned to our blog for more in-depth analyses of brand and retailer performance and strategies across various retail events. Reach out to us today to learn how you can leverage data-driven insights to optimize your brand’s eCommerce strategy and performance.
July 26, 2024
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.
October 16, 2023
5 Ways DataWeave Helps Brands Drive Growth With Amazon Ads

Consumers are discovering and trialing new eCommerce marketplaces, brands and products at a faster rate than ever before, given the vast amount of choices encountered browsing for products online. A recent analysis shows how events like Amazon Prime Day, Black Friday, and Cyber Monday are especially fruitful for new-to-brand customer advertising, encouraging B2C marketers to increase their digital advertising spend to fuel product discovery, sales and market share for their brands.

DataWeave joins Amazon Advertising partner network

The majority of eCommerce consumers are discovering products via relevant keywords attributable to their needs, with most clicks happening on page one results for the first few products listed. Simplifying the digital shopping experience is critical for brands to be in the consideration set for the majority of consumers who won’t venture past page one results.

An internal analysis conducted shows getting a product to page one on retailer websites can improve sales by as much as 50 percent, but figuring out the right levers to pull to get there organically—without paid advertising—is a real challenge, especially given fast-changing algorithms. While more than half of all retail related online browsing sessions are “organic”, sometimes brands need to boost their product visibility by investing in sponsored (paid) opportunities to improve a product’s rank.

Data analytics can equip brands with intelligence to help them decide when, where, and how to make digital advertising investments profitably, while simultaneously acting on insights that help drive organic growth. Considering a majority of U.S. consumers begin their product discovery on marketplaces like Amazon, it makes sense for brands to prioritize digital advertising opportunities with Amazon.

Maximize Return on Ad Spend (ROAS) with Amazon Ads

Brands use Amazon Ads to drive brand awareness, acquire new customers, drive sales and gain market share, with the goal of furthering their marketing return on investment. Top performing advertisers average 40 percent greater year-on-year (YoY) sales growth, 50 percent greater YoY growth in customer product page viewership on Amazon, and 30 percent higher returns on ad spend (ROAS) with Amazon Ads, according to a recent analysis. Sponsored Products, Sponsored Brands, Amazon DSP and Sponsored Display are among the types of Amazon Ads options cited that produce maximum return.

Ensuring your product listings appear at the top of page one results on Amazon for the most relevant discovery keywords is therefore the most important determinant for maximizing ROAS. DataWeave has become a vetted partner and measurement provider in the Amazon Advertising Partner Network, with the goal of supporting brands to optimize digital advertising campaigns by providing visibility to Digital Shelf Analytics (DSA) key performance indicators (KPIs), like Share of Search, Pricing and Product Availability, Content Audits, Ratings and Reviews, and Sales Performance and Market Share.

Below is a summary of how our Digital Shelf solutions, in partnership with Amazon Ads, can improve the performance of your Amazon Ads campaigns

1. Keyword Recommendations Improve Share of Search

With the DataWeave Share of Search solution, brands can monitor their placement of both organic and paid discovery keywords relative to their competition. Once your keywords are determined, you are also provided a weighted Share of Search score that helps measure how well each keyword performs relative to product discoverability. Below is an example of insights you’d gain.

Share of Keyword Search

Brands can provide their own list of keywords to monitor, or through our Amazon Ads collaborative solution, learn which keywords are the “best” for them to measure in the realm of Amazon. Performance results are based on data that shows which keywords consumers are actually using when browsing online alongside other keywords brands request to measure. Users are able to see exactly which keywords are most popular, competitive (and even unexpected), and relevant at an Amazon Standard Identification Number (ASIN) level of granularity.

We can also estimate the degree of relevance and estimated traffic for the recommended keywords. Brands can then use these insights to adjust campaign strategies based on these parameters, which can boost product discoverability and rank visibility. A brand could assume people find its products by brand name, yet traffic insights may reveal a majority of people look for a generic product type before they end up buying that particular brand.

2. Content Audits Increase Discovery Relevancy Scores

Strong product content is critical to succeeding on Amazon. Thorough, accurate, and descriptive content leads to better click through rates (CTR), conversion rates, more positive reviews, and fewer returns, which results in increased discoverability. DataWeave’s Content Audit solution reviews existing copy and images on a per-attribute basis to highlight any gaps essential to improving visibility, as seen in the example below.

Content Analysis

To further growth, it is equally as important that your product content aligns with your advertising strategy. With Amazon Ads partner add-on, our solution can also audit your content to measure how effectively you are incorporating Amazon Ads keywords into your product content to enhance discovery relevancy.

3. Discover More Opportunities with Pricing and Product Availability Insights

Quality content and keyword updates will only get you so far if your products are not consistently available and priced competitively. With DataWeave’s Pricing and Promotions and Product Availability modules, advertisers can monitor their selling prices and availability trends alongside their competitors to uncover more opportunities to incorporate into advertising campaigns, as seen in the Pricing and Promotions dashboard example below.

Promotion Analysis

Additionally, product targeting recommendations can be utilized to target a competitor’s ASIN that may be overpriced or that is having issues staying in stock. Alternatively, broaden your strategy to target specific brands, complementary products, or category listing pages.

You can also create alerts on your own products to monitor when items are low on inventory or out of stock to ensure key products are consistently available when customers are shopping.

4. Leverage Ratings and Reviews to Increase Conversion

Product ratings and reviews are also a critical component to running a successful Amazon Ads campaign. A large number of reviews and a positive star rating will provide customers with the confidence to purchase, resulting in higher conversion rates. Conversely, negative feedback can have a detrimental impact, resulting in lost sales and wasted ad spend. DataWeave’s Ratings and Reviews module can help you monitor your reviews and extract attribute-level insights on your products. This information can then be utilized to further optimize your advertising strategy.

If you see consistent feedback in your reviews on aspects of a product not meeting customer expectations, address them in your product content to prevent potential misplaced expectations. Alternatively, if customer reviews are raving about certain product features, ensure these are promoted and relevant keywords are populated throughout your descriptions and feature bullets. Below is an example of insights seen within the DSA Ratings & Reviews dashboard.

Ratings and Reviews

5. Correlate Digital Shelf KPIs to Sales Performance and Market Share

The newest DSA module, Sales Performance and Market Share, provides SKU, sub-category, and brand-level sales and market share estimates on Amazon for brands and their competitors, via customer defined taxonomies, to easily benchmark performance results.

This data can also be correlated with other Digital Shelf KPIs, like Content Audit and Product Availability, giving brands an easy way to check the effect of attribute changes and how they impact sales and market share. Similarly, brands can see how search rank, both organic and sponsored, affects sales and market share estimates.

Understanding the correlation between your advertising campaigns and your Digital Shelf brand visibility will help you identify which areas to prioritize to drive sales and win more market share.

Digital Shelf Insights Help Brands Win with Amazon Ads

The need for access to flexible, actionable eCommerce insights is growing exponentially as a way to help brands drive growth, increase their Share of Voice, and to gain a competitive edge. As a result, more global brands are seeking Digital Shelf Analytics for access to near real-time marketplace changes and to develop data-driven growth strategies that leverage pricing, merchandising, and competitive insights at scale.

By monitoring, measuring and analyzing key performance indicators (KPIs) like Sales Performance and Market Share, Share of Search, Content Audits, Product Availability, Pricing and Promotions and Ratings and Reviews alongside competitors, brands will know what actions to take to boost brand visibility, customer satisfaction, and online sales.

DataWeave’s acceptance into the Amazon Advertising Partner Network enables Amazon advertisers to effectively build their Amazon growth strategies and determine systems that enable faster and smarter advertising and marketing decision-making to optimize product discoverability and overall results.

Connect with us now to learn how we can scale with your brand’s analytical needs, or for access to more details regarding our Amazon Ads Partnership or Digital Shelf solutions.

UPDATED: Read the full press release here

August 23, 2022
The Role of eCommerce in Sustainable Fashion

Today, environmental damage is rapidly occurring on a global scale. And there are many reasons and causes for this. Global warming is one, deforestation, over population are some others. The list is long. In a small way, the retail & clothing industry contributes to environmental damage too. The good news is that sustainable fashion addresses this issue. Sustainable clothing is designed using sustainable fabrics like organic cotton, hemp, and Pima cotton that have less of a negative impact on the planet.

Sustainable clothing and its benefits

In this blog, we will discuss the rise of sustainable clothing and its benefits. We will also discuss marketplaces for sustainable fashion.

Benefits of Sustainable Fashion

a. Reduces carbon footprint

The fashion industry emits numerous greenhouse gases annually. Most clothes are made from fossil fuels and require significantly more energy in production. Sustainable brands often use natural or recycled fabrics that require less chemical treatment, water, and energy. Organic fabrics such as linen, hemp, and organic cotton are biodegradable and environmentally sound.

b. Saves animal lives

Leather isn’t a by-product of the meat industry, and it’s estimated that it alone is slaughtering and killing over 430 million animals annually. Sustainable fashion brands are increasingly embracing the use of cruelty-free alternatives. Various alternatives include polyester made with ocean trash, plant-based compostable sneakers, bags from recycled seatbelts, silk created from yeast, and bio-fabricated vegan wool. Another interesting leather alternative comes from pineapples, where the fabric is produced using the leaves of pineapples.

c. Requires less water

Water is used in the dyeing and finishing process for nearly all items in the fashion industry. It takes 2,700 liters of water to produce a single T-shirt. Cotton is highly dependent on water but is usually grown in hot and dry areas. Linen, hemp, Refibra, and recycled fibers are some other sustainable fabrics that require little to no water during production.

d. Supports safer working conditions

Endless working hours, unacceptable health & safety conditions, and minimum wages, are the reality for most garment workers in the fast fashion sector. A few informative documentaries like “The True Cost” or “Fashion Factories Undercover” document the social injustices of the fast fashion industry. Eco-ethical brands advocate for sustainable fashion, health care, humane working conditions, and fair wages for their workers.

e. Healthy for people and the environment

Fast fashion products often undergo an intense chemical process where 8,000 types of chemicals are used to bleach, dye, and wet process garments. Those chemicals often lead to diseases or fatal accidents for workers and inflict serious congenital disabilities on their children. These chemicals harm our health, as our skin absorbs anything we put on it.

5 Sustainable & Ethical Online Marketplaces

Here is a list of five earth-minded and socially responsible marketplaces that have sustainable and fair trade brands for the discerning and mindful shopper:

1. thegreenlabels

Netherlands-based webshop thegreenlabels is a sustainable fashion retailer that sells sneakers, womenswear, and accessories from various “green labels” brands. Founded in 2018, this is a marketplace where people can buy products from brands that care about a positive impact on the environment. All brands featured here guarantee fair working conditions and represent at least one of these 4 values – “CLEAN PROCESS” environmentally friendly production, clothes that support “LOCAL” communities, “VEGAN” brands to assure no animals were harmed and “WASTE REDUCTION”

2. LVRSustainable

LVRSustainable

Luisa Via Roma started as a family-owned boutique in the early 1900s. They have grown into a luxury e-retailer and created an LVRSustainable section for people trying to insert sustainability into their wardrobes. They have brands rated ‘Good’ or ‘Great.’ The site offers a wide range of products like bags, accessories, sports, shoes, lingerie, and much more for men, women, and kids. You can find organic, vegan, eco-friendly, ethical, and recycled & upcycled items here.

3. Brothers We Stand

Brothers We Stand

Brothers We Stand is a retailer set up in solidarity with the people who make our clothes. This retailer conducts rigorous research to ensure that every product in their collection meets the following three standards: designed to please, ethical production, and created to last. It’s a great platform to shop for ethical and sustainable menswear. They also have their private clothing line along with other brands.

4. Labell-D

Labell-D was launched with a clear mission to reduce the negative impact of fast fashion on the planet. This retailer wants to make Responsible Fashion the new norm. They intend to make sustainable clothing and fashion easy for both brands and consumers. Labell-D has a transparent accreditation process where they evaluate the brand’s carbon footprint and environmental impact. Their verification assessment includes animal welfare, emissions, materials, production processes, chemical usage, waste management, and traceability.

5. Cerqular

Cerqular wants to make sustainable shopping affordable and accessible for all. The retailer promises that every product and seller is verified as organic, recycled, sustainable, carbon-neutral, eco-friendly, vegan, or circular. They have a wide range of sellers and do not limit products only from luxury brands, so sustainable shopping is no longer expensive or inconvenient.

Conclusion

The fashion industry is a contributor to worldwide carbon emissions. Sustainable fashion is the new big thing giving rise to more and more sustainable brands and marketplaces.

To stand out and shine in the crowded eCommerce space is not easy. Having a robust Digital Shelf becomes critical for brands. A brand’s Digital Shelf is all of the ways their customers digitally interact with the brand, not only on marketplaces but on the brand’s DTC website & shoppable social media. This is why brands need to closely track & optimize their Digital Shelf KPIs like assortment, availability, pricing, ratings & reviews, product discoverability & product content to increase their online sales.

Want to learn how DataWeave can help you win the Digital Shelf? Sign up for a demo with our team to know more.

July 18, 2022