The DataWeave Blog

Category: Customer Sentiments

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
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
11 Reasons why your eCommerce Business is failing

No matter where your eCommerce business sells, there are some fundamentals that brands have to get right to achieve sales targets. Brands need to find the right product/market fit, nail their lead acquisition strategy, and design a qualified sales funnel to turn prospects into leads and eventually returning customers. They will also have to analyze their customer’s buying journey and get insights into competitors’ strategies to understand what works for their business.

If your eCommerce business is struggling, read this blog to learn about steps you can take to increase sales and keep your business afloat.

1. Lack of social proof

Customers often check for reviews or testimonials before making a purchase. Our decisions are consciously or unconsciously influenced by the opinions, choices, and actions of people around us. Social proof helps brands build customer trust, adds credibility to their business, improves brand presence, and validates customers’ buying decisions. 92% of consumers are more likely to trust user-generated content (UGC) and non-paid recommendations than any other type of advertising. Additionally, brands should also find ways to combat negative reviews since bad reviews can sometimes be extremely damaging.

Understanding these reviews or the impact of your brand’s social proof is critical. At DataWeave, we help brands analyze online reviews to understand customer sentiment and adapt to feedback to enhance their experience with your brand.

2. Slow site speed

Site speed of the home page and checkout page on your D2C website can be a roadblock. Slow sections on your site like My Accounts, checkout, and cart are often overlooked when it comes to tracking site speed. Brands should run their checkout process at least once a month to ensure it’s fast, smooth, and bug-free. You can optimize images, strip unused scripts, implement HTTP/2, etc., to improve site speed and performance.

3. Poor customer service

69% of US consumers say customer service is very important when it comes to their loyalty to a brand. Guaranteeing a return customer is important to maintaining customer loyalty. While the focus is on the first purchase for new customers, your brand’s customer service will determine if first-time customers become repeat buyers. Loyal customers are known to spend 67% more on a brand product than new customers, even if they make up only 20% of your audience.

Types of customer service

4. Failure to send traffic to popular products

Be it your own D2C website, or when selling on a marketplace, you should be able to drive traffic to your best-selling products. One of the best ways for sending traffic to popular products on your website is to run paid ad campaigns and reach new audiences with influencer marketing on social media. Brands can also attract customers with organic media such as writing blogs and producing podcasts.

If you’re looking at driving traffic to key products on Amazon & other such marketplaces, sponsored ads are the way to go! Sponsored ads help your best-selling products more discoverable & helps shoppers find your brand with ease.

5. Inadequate pricing

Finding the right pricing strategy for your eCommerce business is crucial for optimizing sales and increasing revenue. The first step is to perform a competitor and historical data analysis to get a general idea of the market and then develop a pricing strategy that is the right fit for your products. Brands also have to ensure that they have dynamic pricing that can adjust according to supply and demand.

Our Digital Shelf solution at DataWeave helps brands track pricing for products across different pack sizes & variants across multiple online retailers and marketplaces helping them stay competitive in the market.

Optimize the right pricing strategy

6. Not targeting the right audience

One of the biggest mistakes that eCommerce businesses can make is targeting the wrong audience. It’s crucial for brands to define that target audience and then tailor products and marketing toward them. To increase sales as an eCommerce business, brands have to understand their audience, their interests, and how to appeal to their interest. Start by creating ideal buyer personas that represent your ideal customers. Also, segmenting audiences and targeting various groups based on buyer personas for ad campaigns will lead to better sales and revenue.

Targeting the right audience

7. Poor product descriptions

One of the major and common mistakes by eCommerce brands is using irrelevant product descriptions that are not optimized for the product. Customers don’t add products to their cart if they have difficulty finding sufficient information relevant to the product. Brands should write attention-grabbing descriptions optimized for SEO that are informative for the users. Here are some tips to optimize content to drive more eCommerce sales.

At DataWeave, our AI-Powered solution helps brands optimize content and visuals across product pages to improve discoverability.

8. Not having multiple revenue streams

Due to COVID-19, many businesses have had to modify or temporarily shut down their daily operations. However, finding new revenue streams can be a great way for eCommerce businesses to make up for the lost income and keep the company afloat. The best solution is to diversify your product offerings by offering commonly purchased products in bundles.

9. Low-quality visuals

Businesses fail to hit their sales targets because of low-quality visuals in product descriptions. High-quality and custom images can improve conversion rates from both marketplaces and image-based channels like social media. Social media users are attracted to exciting, high-quality content that conveys a desirable lifestyle. Brands should use high-resolution, attractive pictures of their products. Brands can also utilize UGC and influencers to help build up their content libraries.

Low-quality visuals

10. Wrong Assortment. Poor Availability

When your target audience lands on your eCommerce store and cannot find what they’re looking for, it leads to a poor shopping experience, but more importantly a lost sale for your brand! While you cannot have endless inventory, it’s essential to optimize your assortment & product availability to decrease the chances of your customer walking away. Assortment & availability optimization begins with analyzing current and historical inventory trends. If done manually, assortment can be a time-consuming task. A healthy assortment can increase retail sales by creating a positive shopping experience for your customers and encouraging them to return to your store again.

11. Bad eCommerce UX

Offering a sub-standard user experience is a common reason why eCommerce businesses find it difficult to increase sales. According to a study, the conversions can fall by up to 7% for every one-second delay in page load time. Businesses can use a countdown clock on their landing page and exit pop-ups to improve conversations. Your landing page and product descriptions should provide information that helps your users make a better and more informed decision.

Conclusion

If your eCommerce’s business sales are tanking, improving site speed, customer service, social proof, and product descriptions are some of the levers you can pull to remedy the situation. Brands should also work on improving online reviews & ratings, availability, assortment, visuals, and website UX to improve customer experience. These steps not only increase loyalty but also improve customer retention.

Need help tracking online pricing for your eCommerce business? Or decoding customer sentiment from reviews they’ve left for your products? Or do you need insights into your product assortment and availability? Sign up for a demo with our team to know how DataWeave can help!

April 13, 2022
9 Things to Build a Thriving Fashion eCommerce Brand

According to the Statista Fashion eCommerce report 2021, the compound annual growth rate (CAGR) for online fashion is predicted to be 10.3% between 2018-2023. The widespread need for trendy fashion presents a challenge for fashion brands to succeed in a highly crowded and competitive space. With eCommerce shopping becoming more prevalent, fashion brands aren’t just competing for brick-and-mortar sales. Instead, they’re also competing for those late-night or impulse purchases from online customers.

Looking to 2022 and beyond, this blog will highlight 9 things to build a thriving fashion eCommerce brand:

1. Allow shopping on multiple channels

Breakdown of Shopping journeys in Apparel

Typically buyers from diverse age groups prefer different sales channels. Some prefer large retailers, and some choose web stores. If you know where your customers like to purchase your products, you can leverage the power of search engines and marketplaces to improve your sales. Multi-channel retailing helps fashion eCommerce brands to sell and promote products on a platform and device of the audience’s choice.

A brand should offer support and access to its products across all platforms, channels, and devices. It helps fashion brands to reach customers where they prefer to shop. If your customers prefer to shop on a computer or an app, your brand can offer a seamless customer experience.

2. Don’t sell on the Homepage

Your online fashion store homepage is more about increasing credibility and trust among potential buyers. Your ideal home page shouldn’t display products or their prices. Instead, it would be best to integrate promotional and marketing strategies on the landing page to encourage visitors to explore your product categories and the rest of the website. You should have an intuitive interface that makes navigating the pages easier. You can also use the homepage to promote seasonal offers and new launches. Fashion brands can also display customer reviews, awards, brand achievements, and web security trust seals to increase the conversion rate.

Don’t sell on the homepage

3. Product Descriptions with Unique Stories

Product descriptions often get overlooked or underutilized even though they are important for eCommerce businesses. Your products won’t sell with spammy and same product descriptions. The modern product description is all about communicating a product’s worth and value with a story that captivates your buyer’s attention. Identify areas where your content & images don’t align with your product or represent it in the best light. Make sure to deliver an enhanced consistent brand experience across all online channels to improve your conversions.

4. Focus on Review and Ratings

Rating & Review of a fashion brand

Customer reviews have a huge influence on a buyer’s purchase decision, especially in the fashion industry. Encourage your consumers to leave reviews on your brand website. Reviews help fashion brands to build trust for their products and convert customers. Legitimate customer reviews help your shoppers to get crucial insights into what previous buyers liked or disliked about a particular product.

However, you should stay away from paid-for or false reviews usually encouraged by unscrupulous sellers as they are easy to spot and hurt your rankings. You must remember that receiving reviews also includes dealing with negative comments. They should be used to improve your upcoming product offerings.

5. Sell Looks

The product can be combined with in the detail page

Successful fashion brands don’t simply sell individual products. Instead, they sell complete looks that inspire shoppers to purchase the entire stylish look. As an online fashion brand, you’re not selling clothes; you’re selling an elegant collection of wearable art. When visitors reach your online store, you should appeal to their fantasies and sentiments through aesthetic look books that are both pleasing and congruent with your brand. Most successful online fashion shops are inspirational and visual. Look books help brands pair their previous season items or dead stock with new stock and increase sales. Brands can also share these look books on social media or in their monthly newsletters to increase reach.

6. Provide Promotions and Offers

Fashion brands can take advantage of plenty of sales throughout the year, from New Year celebrations to Black Friday, Cyber Monday, and Christmas. Brands can leverage these high sales periods to sell looks and gift items to boost sales. Just make sure you’re measuring the effectiveness of your online promotions. Holiday and festive sales also offer an excellent opportunity to plan strategic discounts to get rid of old stock. Since trends in the fashion industry have been changing rapidly, you can use discounts to get rid of dead-stock or out-of-trend items each season.

7. Be active on social media

Social media is a way to promote your brand, increase trust among your audience, and entertain your audience with exciting content. You can also engage the audience by providing gift coupons or giveaways. Brands can promote products while keeping their audience engaged with engaging content and promotional offers.

Social media is a great way to get influencer support, either organically or through a paid partnership. Brands have to focus on every element of social media marketing strategy, right from choosing a platform, creating Instagram/Facebook shops, jumping on trends/events, and tracking customer sentiment.

8. High-quality product photography

Capture every detail of your product

Nothing is worse than ordering a piece of clothing online and not getting what you saw on the website. Not being able to accurately convey fashion products will hurt your bottom line. Fashion brands must use top-notch product photography that includes high-quality visuals, such as multiple angle views, 360-degree images of each product, accurate depictions of all color options, and the option to zoom in on product attributes.

High-quality product photography

A recent game-changer in the fashion industry has been including different sets of models to accurately feature clothes of various shapes, heights, and weights. Instead of displaying a dress in only one size, fashion brands can have multiple models wearing various sizes for the same article of clothing.

9. Stay up to date with new trends

Fashion eCommerce brands have to be particularly careful of continuously updating their product offering with the latest fashion trends for each season. They can boost sales with an in-demand product assortment. Continuously updated fashion inventory signifies that the brand is up-to-date with the latest fashion trends in the market and has unique products to offer. You can always get creative with new styling, better looks, and personalized product recommendations.

Conclusion

Fashion eCommerce is rapidly growing and transforming at a staggering rate as technologies continue to advance. Traditional fashion brands can now expand their reach from brick-and-mortar shops to digital and eCommerce platforms to reach shoppers across the globe. The new digital selling opportunities also come with considerable challenges – from staying up to date with ever-evolving trends to managing dead stock.
Are you a fashion brand that needs help monitoring your product content? Or measuring the effectiveness of your online promotions? Or decoding customer sentiment from reviews they’ve left for your products? Sign up for a demo with our team to know how DataWeave can help!

March 31, 2022
Fake Reviews: A Real Pain Point for Brands
Online reviews have revolutionized how customers purchase products and services. In fact, eCommerce success for certain products hinges on the ratings and reviews. With this, have come the pitfalls of corruption in eCommerce.

New brands trying to establish a presence and capture critical mass have been known to resort to soliciting fake and paid reviews to uplift their brand in search rankings. Similarly, these brands can also encourage fake negative reviews on competitor’s listings to bring down their value. Bots and paid manual reviews are usually employed to rake up the review count. Review sites like TrustPilot, Google Reviews, and marketplaces like Amazon are littered with fraudulent reviews. In fact, Guardian calculated that 3.6% of all reviews on TripAdvisor were fraudulent. According to a 2021 report by Statista, 46% of the 2.7 million online fake reviews that were removed were five-star reviews!

Fake online reviews are misleading since customers shopping both online and offline rely on reviews to make purchase decisions. Fake reviews also pose further problems because they deceive consumers into spending money on a product or with a company they may not have otherwise chosen.

Federal Trade Commission (FTC) made a recent announcement to send penalties to over 700 brands and retailers for fake endorsements and reviews. While this notice references influencer content and testimonials, it also applies to customer reviews.

In this blog, we will discuss the importance of reviews for brands and retailers, spotting fake reviews on Amazon, and steps that eCommerce companies can take to tackle fake reviews.

Importance of reviews for Brands and Retailers

Customers do not make blind purchases. Consumers read reviews before buying products. Statistics show that irrespective of the industry, having a positive online presence is essential and has become an integral part of branding. It also indicates that customers have a high confidence level in fellow consumers’ opinions. Overall, positive online ratings & reviews can help skyrocket eCommerce sales.

Customers are more likely to purchase if other customers, even strangers, agree that it was a great purchase. Reviews also make brands more visible.

Why are fake online reviews so resilient?

A significant reason is that the ROI of getting fake reviews increases profitability & sales multifold. For example, an extra star on Yelp can increase a restaurant’s revenue by 5% to 9%. FTC has said that the expenditure on fake reviews can provide a 20x return. However, fake and incentivized reviews are a huge problem. Amazon, one of the largest eCommerce marketplaces, banned incentivized reviews in 2016. It took down suspicious reviews and has taken legal action against sellers who violate its policies.

Online Reviews

How to Spot a Fake Review on Amazon

Marketplaces, Google, and review sites like Yelp can get hundreds of thousands of reviews daily. In a survey by PCMag that interviewed 1,000 US shoppers who looked forward to shopping on Prime Day 2020, only 16% were very confident about detecting fake Amazon product reviews, and 24% were confident they could do it. The rest of the survey respondents were somewhat or not confident they could pick out the fakes on Amazon. Here are our best tips for spotting fake reviews on marketplaces like Amazon:
- Duplicate Content: If you notice dozens of reviews with the same description and title as if they were copied and pasted multiple times, they’re most likely fake reviews.
- Multiple Reviews on the Same Day: Another identification of fake reviews is when there are dozens or multiple reviews on a single day. There can be a bunch of both positive and negative reviews for products.
- Unverified or Anonymous Reviewers: You can see if the review is from a verified buyer on Amazon. Brands can also check if they have any record of the reviewer’s purchase to weed out fake reviews.
- Incorrect Language: Fake reviews can come from people outside your country. If you notice multiple reviews with similar incorrect words and common errors, there is a good chance those reviews are fake, and someone paid the reviewer to write them.
What can eCommerce brands do to protect themselves against fake reviews?
- Follow a zero-tolerance policy for fake reviews.
The major step is to ensure that fake reviews are never posted on your site. Allowing fake reviews negatively affects your business and your bottom line. You can hire a third-party UGC moderator that uses data-driven, anti-fraud methods to evaluate reviews. It will be a much more successful and quicker step in protecting your brand’s reputation.
- Don’t screen out negative reviews.
While receiving a negative review might be the worst nightmare, they’re necessary for a successful UGC program. Customers are more likely to purchase from a business that responds to all reviews, including negative reviews. Customers said that negative reviews have more detailed product information, while 32% of those customers think they’re less likely to be fake. Besides, brands that respond to negative reviews gain customers’ trust and loyalty.
Here are some Tips on how to Respond to Negative reviews online.
- Be transparent about how you collect UGC.
Brands can ensure that their customers trust user-generated content by being honest about how they collected it. Companies should never ask for paid or incentivized positive reviews. Instead, brands should empower their customers to leave honest feedback. If you’re offering free products, a chance to win something, or discount coupons in exchange for an unbiased review, then the review should specify how it was collected. For example, you can add indicators like “this reviewer received a coupon or a free product in exchange for honest feedback.
- Maintain trust
Having fake reviews causes a loss of trust, with many consumers believing that they have seen fake reviews for online and offline businesses. Removing fake reviews doesn’t only help with revenue and brand trust, but it also helps brands to maintain trust among their existing and future customers.

Conclusion

Fake reviews are one of the biggest reputation killers and a huge problem for eCommerce platforms, brands, and customers. Brands must take the necessary steps to minimize the risk of fake reviews and expand businesses among authentic users. Although modern text generation tools are becoming more competent in writing realistic reviews, there are AI- and ML-backed tools that can accurately detect reviews written by other machines.

Need help tracking your online ratings & reviews? Or decoding customer sentiment from reviews they’ve left for your products? DataWeave offers a customizable and scaleable data solution to analyse ratings and reviews for online retailers and brands vis v vis their competitors.
Sign up for a demo with our team to know how DataWeave can help.
March 27, 2022