The DataWeave Blog

Category: Digital Shelf

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

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

Our Methodology

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

Who’s Offering the Best Deals Across Categories?

Our pre- Black Friday analysis reveals a clear pattern of premium brands offering deeper discounts across categories ahead of the holiday. Here are some key findings around retail players:
- Walmart emerges as the most aggressive discounter across categories, leading in Health & Beauty (57.07%), Apparel (48.97%), and Consumer Electronics (43.35%).
- Amazon maintains consistent but lower discounts (28-29%) across categories, suggesting potential deeper cuts ahead.
- Best Buy and Sephora, both category specialists, play it conservative compared to mass retail players.
Let’s look at each category more closely to get a detailed snapshot of the deals this Thanksgiving week:

Health & Beauty

Our analysis reveals that it’s not electronics, but the health & beauty category that leads with the widest discount range pre Black Friday, making it the category to watch out for.
- Walmart takes the lead with an aggressive 57.1% average discount in this category, capitalizing on its value-oriented reputation.
- Beauty specialist Sephora holds modest beauty discounts (32.81%) compared to other retailers.
- Amazon offers the broadest range of SKUs (571) in the category.
Among the health & beauty brands we analyzed, cosmetics brand Tarte and viral K-Beauty skincare brand COSRX stand out with discounts above 40%, appealing to cost-conscious beauty enthusiasts.

Consumer Electronics

Our pre- Black Friday analysis reveals interesting insights about consumer electronics deals this season.
- Walmart, once again, emerges as the frontrunner in the category with 43.4% average discounts.
- Best Buy plays it conservative in electronics (30.75%), despite being a category specialist, but offers the most extensive SKU coverage (3030).
- Amazon’s consistent 29.7% discount across 1,749 SKUs suggests they’re probably holding back their best deals for Prime members during Black Friday.
Brand-specific data for the category reveals significant deals on Speck (48.07%) and smart TV brand Insignia (39.22%), making accessories and mid-tier electronics attractive for early shoppers. Core computing (HP at 32.14%) and electronics brands maintain more conservative discounts. It remains to be seen if this changes on Black Friday or Cyber Monday.

Apparel

Our analysis of the apparel category reveals several highlights:
- In the apparel category too, Walmart dominates with an impressive 49% average discount, effectively targeting price-sensitive shoppers in the fashion segment.
- Nordstrom and Neiman Marcus, both known for apparel, offer significant discounts at 43.2% and 37.8% respectively.
- Amazon’s expansive SKU coverage (1344) is countered by a modest 29.5% discount, showing its focus on variety over depth of discounts.
Premium fashion brands dominate the highest discounts this Black Friday in the apparel category. Vince Camuto leads with over 45.1% average discount. Notably, Levi and Nike’s aggressive 44.43% and 43.50% discounts suggests significant inventory positions or intent to capture market share.

Home & Furniture

Our analysis reveals an interesting trend across the category.
- In the home & furniture category too, Walmart leads at 41.8% average discounts. Target follows closely, but with significantly lesser SKUs on offer.
- Amazon’s 28.1% discount, though the lowest among major players, spans a substantial 1,982 SKUs, reinforcing its position as a marketplace for diverse needs.
Top 3 Products With the Highest Discounts Across Retailers

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

Top Discounted Products in Consumer Electronics

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

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

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

Top Discounted Products in Health & Beauty

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

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

Looking Ahead

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

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

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

Stay tuned for our Black Friday Cyber Monday analysis next week, where we’ll track how these early discounts compare to the main event’s deals!
November 28, 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
Normalizing Size and Color in Fashion Using AI to Power Competitive Price Intelligence
Fashion is as dynamic a market as any—and more competitive than most others. Consumer trends and customer needs are always evolving, making it challenging for fashion and apparel brands to keep up.

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

There are three main categories in fashion and apparel. These include:
- Apparel and clothing (i.e., shirts, pants, dresses, and other apparel)
- Footwear (i.e., sneakers, sandals, heels, and other products)
- Accessories (i.e., bags, belts, watches, and so on)
If you look at all of these product types across all sorts of retailers, there is a massive amount of overlapping data based on product attributes like style and size that are difficult to normalize.

Fashion Attributes

Style, color, and size are the main attribute categories in fashion and apparel. Style attributes include things like design, look, and overall aesthetics of the product. They’re very dependent on the actual product category of fashion as well. A shirt might have a slim fit attribute associated with it, whereas a belt might have a length. All these different attributes are usually labeled within a product listing and affect the consumer’s decision-making process:
- Color (red, blue, sea green, etc.)
- Pattern (solid, striped, checked, floral, etc.)
- Material (cotton, polyester, leather, denim, silk, etc.)
- Fit (regular, slim, relaxed, oversized, tailored, etc.)
- Type (casual, formal, sporty, vintage, streetwear)
Color Complexity in Fashion

Color is perhaps the most visually distinctive attribute in fashion, yet it presents unique challenges for retailers. This is because color naming can vary across retailers and marketplaces. There are several major differences in color convention:
- A single color can be labeled differently across brands (e.g., “navy,” “midnight blue,” “deep blue”)
- Seasonal color names (e.g., “summer sage” vs. “forest green”)
- Marketing-driven names (e.g., “sunset coral” vs. “pale orange”)
Size: The Other Critical Dimension

Size in fashion refers to the dimensions or measurements that determine how fashion products fit. Depending on whether the product is a clothing item, shoes, or a hat, there will be different sizing options. Types of sizes include:
- Standard sizes (XS, S, M, L, XL, XXL, XXL)
- Custom sizes (based on brand, retailer, country, etc.)
A single type of product may have different sizing labels. For instance, one pants listing may use traditional S, M, L, XL sizing, while another pants listing may use 24, 25, or 26, to refer to the waist measurement.

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

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

Pricing Based on Size and Color

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

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

Different colorways (any of a range of combinations of colors in which a style or design is available) of the same product often command different prices also. This is based on:
- Dye costs (some colors require more expensive processes)
- Seasonal demand (traditional colors vs. trend colors)
- Exclusivity (limited edition colors)
An example of price variations by size is a women’s shirt that is being sold on Amazon as shown below. For this product, there are no style attributes to choose from. The only parameter the shopper has to select is the size they’d like to purchase. They can choose from S to XL. On the top, we can see that the product in size S is ₹389. Below, the size XL version of this same shirt is ₹399. This price increase is correlated to the change in size.

So why are these same products priced differently? In an analysis of One Six, a plus-size clothing brand, several reasons for this difference in plus-size clothing were determined.
- Extra material is needed, hence an increase in production costs
- Extra stitching costs, hence an increase in production costs
- Production of plus-size clothing often means acquiring specialized machinery
- Smaller scale production runs for plus-size clothing means these initiatives often don’t benefit from cost savings
Some sizes are sold more than others, meaning that in-demand sizes for certain apparel can affect pricing as well. Brands want to be able to charge as much as possible for their listing without risking losing a sale to a competitor.

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

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

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

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

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

Getting Color and Size Level Pricing Intelligence

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

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

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

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

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

Product Matching Size and Color in Apparel and Fashion

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

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

Interested in learning more about DataWeave? Click here to get in touch!
November 6, 2024
Mastering Retail Media Metrics: A Deep Dive into Share of Media
Brands are investing millions of dollars in digital retail media to make their products stand out amid unrelenting competition.

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

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

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

What is the Share of Media?

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

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

Banner Advertising

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

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

Sponsored Listings

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

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

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

The Power of Banner Ads and Sponsored Listings

Banner ads and sponsored listings are great choices for boosting customer engagement and product sales. Here are four key advantages they offer:
- Enhanced Visibility: Digital retail media strategically places your brand where it will stand out—outshining competitors and grabbing the attention of high-purchase-intent consumers.
- Precision in Reach: These ads target specific keywords or categories, allowing for highly focused advertising based on demographics and search intent.
- Minimal Conversion Friction: Smooth transitions from ads to a brand’s native store or product listing on the marketplace keep conversion friction to a minimum.
- Brand Awareness and Recall: Consistent exposure to your brand through banner ads and sponsored product listings can leave lasting impressions and build brand recognition.
The bottom line is that it’s increasingly important for brands to monitor their Share of Media.

How to Monitor Your Brand’s Share of Media

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

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

Share of Media by Keyword

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

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

Share of Media by Category

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

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

Share of Media: An Essential Ecommerce Metric

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

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

For more information on how Digital Shelf Analytics can enhance your brand’s digital shelf presence, request a demo or contact us at contact@dataweave.com.
October 14, 2024
The Complete Guide to Competitive Pricing Strategies in Retail and E-commerce

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

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

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

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

What is Competitive Pricing?

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

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

Competitive Pricing Models

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

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

Price Skimming

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

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

Premium Pricing

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

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

Price Matching

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

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

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

Penetration Pricing

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

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

Loss Leader Pricing

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

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

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

Key Advantages of Competitive Pricing

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

It is Responsive

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

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

It is Simple to Execute and Manage

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

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

It Can Be Combined with Other Pricing Strategies

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

Key Disadvantages of Competitive Pricing

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

It De-emphasizes Consumer Demand

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

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

You Risk Price Wars

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

There’s Potential for Complacency

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

4 Tips for a Successful Competitive Pricing Strategy in Retail

Here are four competition-based pricing tips for retailers:

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

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

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

Retailer Tip #2. Price Dynamically

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

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

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

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

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

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

Retailer Tip #4. Stay in Tune with Consumer Demand

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

5 Tips for a Successful Competitive Pricing Strategy for Consumer Brands

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

Brand Tip #1. Identify Competing Products for Accurate Comparisons

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

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

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

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

Brand Tip #3. Consider Brand Perception

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

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

Brand Tip #4. Leverage Value-Based Differentiation

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

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

Brand Tip #5. Stay Vigilant with Price Monitoring

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

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

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

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

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

AI-Driven Product Matching

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

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

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

Accurate and Comprehensive Data

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

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

Normalized Measurement Units

Accurate price comparisons are dependent on normalized unit measurements.

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

This normalization ensures accurate pricing analysis.

Timely Actionable Insights

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

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

In Conclusion

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

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

October 14, 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
Back-to-School 2024 Pricing Strategies: What Retailers and Brands Need to Know
As summer winds down, families across the US have been gearing up for the annual back-to-school shopping season. The back-to-school season has always been a significant event in the retail calendar, but its importance has grown in recent years. With inflation still impacting many households, parents and guardians are more discerning than ever about their purchases, seeking the best value for their money.

The National Retail Federation has forecasted that this season could see one of the highest levels of spending in recent years, reaching up to $86.6 billion. As shoppers eagerly stock up on back-to-school and back-to-college essentials, it’s crucial for retailers and brands to refine their pricing strategies in order to capture a larger share of the market.

To understand how retailers are responding to the back-to-school rush this season, our proprietary analysis delves into pricing trends, discount strategies, and brand visibility across major US retailers, including Amazon, Walmart, Kroger, and Target. By examining 1000 exactly matching products in popular back-to-school categories, our analysis provides valuable insights into the pricing strategies adopted by leading retailers and brands this year.

Price Changes: A Tale of Moderation

The most notable trend in our analysis is the much smaller annual price increases this year, in contrast to last year’s sharp price hikes. This shift is a reaction to growing consumer frustration about rising prices. After enduring persistent inflation and steep price growth, which peaked last year, consumers have become increasingly frustrated. As a result, retailers have had to scale back and implement more moderate price increases this year.

Kroger led the pack with the highest price increases, showing a 5.3% increase this year, which follows a staggering 19.9% rise last year. Walmart’s dramatic price increase of 14.9% is now followed by a muted 3.1% hike. Amazon and Target demonstrated a similar pattern of slowing price hikes, with increases of 2.3% and 2.7% respectively in the latest period. This trend indicates that retailers are still adjusting to increased costs but are also mindful of maintaining customer loyalty in a competitive market.

When examining specific product categories, we observe diverse pricing trends. Electronics and apparel saw the largest price increases between 2022 and 2023, likely due to supply chain disruptions and volatile demand. However, the pace of these increases slowed in 2024, indicating a gradual return to more stable market conditions. Notably, backpacks remain an outlier, with prices continuing to rise sharply by 22%.

Interestingly, some categories, such as office organization and planners, experienced a price decline in 2024. This could signal an oversupply or shifting consumer preferences, presenting potential opportunities for both retailers and shoppers.

Brand Visibility: The Search for Prominence

In the digital age, a brand’s visibility in online searches can significantly impact its success during the back-to-school season. Our analysis of the share of search across major retailers provides valuable insights into brand prominence and marketing effectiveness.

Sharpie and Crayola emerged as the strongest performers overall, with particularly high visibility on Target. This suggests strong consumer recognition and demand for these traditional school supply brands. BIC showed strength on Amazon and Target but lagged on Kroger, while Pilot maintained a more balanced presence across most retailers.

The variation in brand visibility across retailers also hints at potential partnerships or targeted marketing strategies. For instance, Sharpie’s notably high visibility on Target (5.16% share of search) could indicate a specific partnership.

Talk to us to get more insights on the most prominent brands broken down by specific product categories.

Navigating the 2024 Back-to-School Landscape

As we look ahead to the 2024 back-to-school shopping season, several key takeaways emerge for retailers and brands:
1. Price sensitivity remains high, but the rate of increase is moderating. Retailers should carefully balance the need to cover costs with maintaining competitive pricing.
2. Strategic discounting can be a powerful tool, especially for lesser-known brands looking to gain market share. However, established brands would need to rely more on quality, visibility, and brand loyalty.
3. Online visibility is crucial. Brands should invest in strong SEO and retail media strategies, tailored to different retail platforms.
4. Category-specific strategies are essential. What works for backpacks may not work for writing instruments, so a nuanced approach is key.
5. Retailers and brands should be prepared for potential shifts in consumer behavior, such as increased demand for value-priced items or changes in category preferences.
By staying attuned to these trends and remaining flexible in their strategies, businesses can position themselves for success in the competitive back-to-school retail landscape of 2024. As always, the key lies in understanding and responding to consumer needs while maintaining a keen eye on market dynamics.

Stay tuned to our blog to know more about how retailers can stay aware of changing pricing trends. Reach out to us today to learn more.
September 12, 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
How Digital Shelf Analytics Can Fix Common Revenue Growth Management Challenges for Consumer Brands
As consumer goods brands increasingly turn to eCommerce marketplaces as a source of profitable growth, it becomes harder for teams to grapple with the complexity of revenue growth management.

This complexity emerges from multiple fonts: there are hundreds, and even thousands, of competitors to consider when formulating strategies for managing pricing, promotion, and assortment changes. The world is currently experiencing a period of unprecedented supply chain instability, shifting more consumers away from traditional retail and into eCommerce shopping. And finally, consumer buying patterns, preferences, and trends are constantly shifting.

Revenue growth management (RGM) and net revenue management (NRM) were once less complex processes; but that is no longer the case. Now, some 80% of consumer brand CEOs report that they “aren’t satisfied with their RGM results.”

Gathering data, analyzing it, and acting on it quickly stand out as major challenges that businesses must overcome to grow their market share, earn more profits, and capitalize on market shifts in real time. In this article, we’ll dive into RGM and NRM, the obstacles business teams face, and explore how using technology for digital shelf analytics can help bridge the gap.

What is Net Revenue Management (NRM) or Revenue Growth Management (RGM)?

Every consumer goods company aims to increase profits and grow market share. This requires a concerted effort in RGM and net revenue management (NRM) strategy. Whether a company has a specific team dedicated to this task or relies on the abilities of business analysts or merchandisers, this function is crucial.

It’s worth mentioning that though the terms NRM and RGM are often used interchangeably, there are subtle differences. While both net revenue management and revenue growth management focus on maximizing overall revenue for the brand, NRM typically has a narrower focus and is specific to optimizing profitability through product pricing, promotion, product mix, and cost management. RGM strategies are a bit broader and tend to look at the top line to grow market share and expand the customer base.

The Challenges Revenue Teams Face

Differentiating between ‘good growth’ and ‘bad growth’ is central to NRM and RGM. Net revenue management and revenue growth management teams need the data and tools in place to determine if growth in one area is coming at the expense of another so as not to cannibalize business. Tracking and analyzing extensive data to successfully take action on opportunities and determine whether strategies are working as intended consumes a tremendous amount of mental bandwidth. The fact that these decisions are incredibly time-sensitive only compounds the issue.

To cope, many teams in charge of NRM or RGM employ digital shelf analytics strategies to help speed up data aggregation and analysis to make sure they’re capitalizing on potential opportunities.

eCommerce has added a whole new layer of complexity to consumer goods sales. Instead of a few relatively stable prices at big-box stores, a single item for sale may experience high price volatility, with dozens of minute pricing changes occurring online each day. In some cases, consumers become blind to price volatility, letting brands increase prices, but consumer sentiment, the overall price elasticity of the product, and dozens of other factors go into determining the final price of an online product. Net revenue teams need to modernize and adapt to changing eCommerce environments to competitively price, promote, and grow their revenue.

Here are the top three challenges standing in the way of net revenue management and revenue growth management teams and solutions to address these issues.

Challenge 1: Incomplete or Inaccurate Data

Incomplete and inaccurate data are critical for Net Revenue Management and Revenue Growth Management teams to get under control when attempting to modernize in a digital-centric selling environment. As more competitors enter the market, many brands find it hard to make strategic decisions without the complete picture.

Data may be incomplete or inaccurate because a brand is analyzing only part of the market, such as Amazon or another enterprise-scale eCommerce marketplace. Additionally, they might not be analyzing all types of online media, such as branded ads, sponsored search listings, or sponsored category listings.

Most importantly, another pitfall is the lack of hyperlocal data. Generalized data across regions, states, ZIPs, and stores can skew the decision-making process and result in poor outcomes.

Overcoming Incomplete or Inaccurate Data

In order to get the full picture, consumer brands need to ensure they have a view of the entire competitive landscape across their channels. This includes gathering data down to the case pack, the unique product identifier, and the geography, including ZIP and store. They also need the respective MSRP by SKU, the unit normalized price, and the selling price at a specific moment in time. This is done by aggregating brick-and-mortar store information available online, such as when stores list curbside pickup SKUs and pricing online.

Individual teams cannot manually gather all this detailed data. The growth in eCommerce means there is simply too much data to find and aggregate. Instead, they can employ digital shelf technology to get more data from more sites. Teams can leverage AI to better match product listings, ads, and even visuals to avoid missing data on listings that lack common attributes, such as UPCs for normalization.

To add to this, advanced pricing intelligence systems can cache URLs to help teams audit and verify their data, avoiding delays and confusion when ad hoc requests arise.

Challenge 2: Difficulty in Making Sense of the Competitive Landscape

Once net revenue management and revenue growth management teams have gathered all of the available data, it’s time to make sense of it. This is a monumental challenge, and ends up being the stage where most NRM and RGM teams flounder. Disparate marketplaces include different product attributes and images. This makes it extremely complicated to sync competitors’ data to ready it for analysis, especially if this analysis is carried out manually in Excel. These are some of the attributes that teams need to harmonize in order to make sense of the competitive landscape:
- Product identifiers (UPC, SKU, Internal Code)
- Size, case, pack, volume, bundled offerings
- Language
- Currency
- Stock Status (Whether the product is available or not)
- Platform-specific attributes such as ‘Amazon’s Choice,’ ‘Best Seller,’ etc.
Teams also need to group and classify various categories of promotions. These can include sponsored listings, banner ads, coupons, bank offers, and others. Each of these categories needs to be tracked separately. This vast array of data points across hundreds of sites creates a big data problem for teams.

Making Sense of the Competitive Landscape

The best way to overcome this challenge is to task a digital shelf analytics system with gathering and harmonizing data automatically across the consumer goods competitive landscape. Competitive and market intelligence tools can help break down an overwhelming amount of data, matching similar products across competing brands and analyzing their various strengths and weaknesses. Once the technology matches complex product attributes and identifiers, it becomes easier for teams to gain insights and exploit findings. In a sense, the data needs to be cleaned before analysis can occur.

Technology can gather data in multiple ways, and the best systems employ several methods to get the best matches. Data consumption modes include API integrations, CSV and Excel file uploads, and proprietary scrapers that view websites independently of direct inputs. Having all the data in a single place helps net revenue management and revenue growth management teams gain indicative insights on product popularity, pricing, and sales, on their own and competitor products.

Challenge 3: Lack of Timely Visibility

The final challenge that many net revenue management and revenue growth management teams face is something of a ‘silent killer’ — timeliness. Even if they successfully gather data across the entire competitive landscape and harmonize that data into a format for easy analysis, a lack of timeliness can render even the best actions irrelevant.

Speed is of the utmost importance when there are market changes. If a product goes viral and competitors raise prices in response to increased demand, without timely visibility, the trend may be over before a consumer goods brand can successfully increase its prices for the duration of the trend. This can mean lost margins.

Another example is analyzing data and incorporating lagging promotional and sales data into analyses. This can skew pricing strategies because timely data is not accessible to inform decision-making. Many teams waste time firefighting due to a lack of timely pricing and promotional intelligence data.

Get Near Real-Time Insights for Faster Decision Making

Using technology that allows for net revenue management and revenue growth management teams at consumer goods brands to establish update frequencies can be a game changer. Teams can set update frequencies based on their need. They can set up the system to check a fast-moving product daily, while a slow-moving item might only need to be checked weekly, monthly, or even quarterly. This allows teams to focus on the highest-impact products first and address the largest exceptions before they lose out on an opportunity. Managing exceptions with a digital shelf analytics platform saves teams significant time instead of poring over low-impact changes in the data.

Digital Shelf Analytics for Net Revenue Management

Modernizing a consumer goods brand’s net revenue management or revenue growth management processes requires advanced digital shelf analytics. DataWeave provides consumer goods companies with the technology they need for quick and accurate pricing, promotional, and assortment intelligence. By tracking over 200 million products each day, users can be sure they get the widest and most timely view of the competitive landscape. DataWeave’s deep industry knowledge is baked into every aspect of its platform.

Learn more by requesting a demo today!
August 20, 2024
Competitor Price Monitoring in E-commerce: Everything You Need to Know
Picture this: You wake up one morning to discover that your top competitor reduced their prices overnight. And now your shopper traffic has tanked and your sales have taken a hit.

Unfortunately, this is a common scenario because your customers can compare prices online in seconds—and loyalty lies with the budget.

So, how can you protect your business? Price monitoring.

Price monitoring solutions can help you keep abreast of competitor price changes—which, of course, will help you improve your pricing strategies, retain your customers, and maximize your profits.

How? In this article, we’ll explore:
- What is price monitoring
- The key benefits of price monitoring for retailers and brands
- What a capable price monitoring solution can do
What Is Price Monitoring?

Price monitoring is the process of tracking and analyzing your competitor’s prices across various online and offline platforms. By monitoring competitors’ prices, you can understand market price trends and adjust your prices strategically—which, in turn, helps you remain competitive, increase margins, and improve customer retention.

5 Benefits of Price Monitoring

Competitor price monitoring can help you:
1. Gain a competitive edge: Competitor price tracking allows you to adjust your prices to remain attractive to consumers.
2. Maximize revenue: With timely pricing data, you’re empowered to identify optimum price points that strike a delicate balance between maximizing revenue and maintaining customer loyalty.
3. Retain customers: Consumers are looking for the most value for their dollar, so maintaining consistently competitive pricing is crucial for retaining loyal customers.
4. Understand promotional effectiveness: Price monitoring helps businesses evaluate the effectiveness of their promotions and discounts. By comparing the impact of different pricing strategies, businesses can refine their promotional tactics to maximize sales and customer engagement.
5. Understand market movements: By analyzing historical pricing data, you’re better positioned to anticipate future pricing changes — and adjust your strategies accordingly.
4 Essential Capabilities of Price Monitoring Software

Here are four capabilities to look for when choosing a price monitoring system.

1. AI-Driven Product Matching

Product matching is the process of identifying identical or similar products across different platforms to ensure accurate price comparisons.

If your price monitoring solution can’t reliably match your products with competitors’ across various sales channels at scale, you’ll end up with poor data. Inaccurate data will then lead you to make misinformed pricing decisions.

Product matching needs to be accurate and comprehensive, covering a wide range of products and product variations—even for including private label products.

For example, AI-driven product matching can recognize a specific brand and model of sneakers across multiple online stores—even if product descriptions and images differ. Here’s how it works in a nutshell:
- Sophisticated algorithms and deep learning architecture enable AI to identify and match products that aren’t identical but share key characteristics and features.
- Using unified systems for text and image recognition, the AI matches similar SKUs across hundreds of eCommerce stores and millions of products.
  The AI zeroes in on critical product elements in images, like a t-shirt’s shape, sleeve length, and color.
- The AI also extracts unique signatures from photos for rapid, efficient identification and grouping across billions of indexed items.
DataWeave’s AI algorithm can initially match products with 80–90% accuracy. Then, humans can bring contextual judgement and make nuanced decisions that the AI might miss to correct errors quickly and push for accuracy closer to 100%. By integrating AI automation with human validation, you can achieve accurate and reliable product-matching coverage at scale.

2. Accurate and Comprehensive Data Collection and Aggregation

The insights you derive are only as good as the data you collect. However, capturing comprehensive pricing data is tough when your competitors operate on multiple platforms.

For truly effective price monitoring insights, you need consistent, comprehensive, and highly accurate data. This means your chosen price monitoring system should:
- Scrape data from various sources, such as desktop and mobile sites and mobile applications.
- Pull data from various online platforms like aggregators, omnichannel retailers, delivery intermediaries, online marketplaces, and more.
- Handle data from different regions and languages.
- Collect data at regular intervals to ensure timeliness.
DataWeave’s online price monitoring software covers all of these bases and more with a fast, automated data source configuration system. It also allows you to painlessly add new data sources to scrape.

Instead of incomplete or inaccurate data, you’ll have comprehensive and up-to-date data, allowing you to respond quickly to market changes with confidence.

3. Seamless Normalization of Product Measurement Units

You can’t compare apples to oranges—or price-per-kilogram to price-per-pound.

For price monitoring to be accurate, there must be a way to normalize measurement units—so that we’re always comparing price-per-gram to price-per-gram. If we compare prices without taking into account measurement units, our data will be misleading at best.

Let’s take a closer look. Say that your top competitor sells 12oz cans of beans for $3, and you sell 15oz cans for $3.20. At first glance, your larger cans of beans will appear more expensive—but that’s not true. If we normalize the measurement unit—in this example, an oz—the larger can of beans offers more value to customers.

Unit of measure normalization facilitates sound price adjustments based on accurate and reliable data. For this reason, every business needs a price tracking tool that can guarantee accurate comparisons by normalizing unit measurements—including weight, volume, and quantity.

4. Actionable Data and an Intuitive User Experience

Knowledge is only powerful when applied—and price monitoring insights are only useful when they’re accessible and actionable.

For this reason, the best price monitoring software doesn’t just provide insights based on accurate and comprehensive data, but it also provides several ways to understand and deploy those insights.

Ideal price monitoring solutions provide customized pricing alerts, intuitive dashboards, detailed reports, and visuals that are easy to interpret—all tailored to each particular team or a team member’s needs. These features should make it easy for team members to compare prices against those of competitors in specific categories and product groupings.

Your price tracking tool should also permit flexible API integrations and offer straightforward data export options. This way, you can integrate competitive pricing data with your pricing software, Business Intelligence (BI) tools, or Enterprise Resource Planning (ERP) system.

4 Ways Retailers Can Leverage Price Monitoring

Retailers can use price monitoring tools to remain competitive without compromising profitability—here’s how:

1. Track Competitors’ Prices

Competitor price monitoring helps you avoid being undercut—and, as a result, maintain market share. By tracking competitor prices in real-time, you can adjust prices to remain competitive, especially in dynamic markets. Ideally, you should monitor both direct competitors selling the same products and indirect competitors selling similar or alternative products. This way, you’ll have a complete picture of market prices and can make more informed pricing adjustments.

2. Understand Historical and Seasonal Price Trends

As a retailer, you may want to analyze historical data to identify price patterns and predict future price movements—especially in relation to holidays and seasonal products. Knowing what’s coming, you’re better positioned to plan for pricing changes and promotional campaigns.

3. Implement Dynamic Pricing

Dynamic pricing is the process of adjusting prices based on real-time market conditions, product demand, and competitors’ prices—allowing you to respond faster to market changes to maintain optimized prices.

4. Optimize Promotional Strategies

Price monitoring tools can track retail promotions across numerous online and offline sales avenues, providing insight into the nature and timing of competitors’ promotions. This data can help you determine which promotions are most effective—and which aren’t—allowing you to improve your own promotions and discounts, and allocate marketing resources where it matters most. This is especially beneficial during peak sales periods.

3 Ways Brands Can Employ Price Monitoring

Here are three ways brands can use price monitoring to remain profitable, protect brand equity, and gain a competitive edge.

1. Maintain Consistent Retail Prices

Minimum advertised price (MAP) policies are designed to prevent retailers from devaluing a brand while ensuring fair competition among retailers. Price monitoring applications allow your brand to track retailers’ prices to detect MAP policy violations. Data in hand, you can maintain consistent pricing across online sales channels, physical stores, and retail stores’ digital shelves — and, critically, protect your brand equity.

2. Improve Product and Brand Positioning

When you understand how your products’ prices compare to those of competitors, you can set prices to improve brand positioning. For example, if you want to position your brand as luxurious and high-quality, you need to set higher product prices than budget-friendly alternative products.

3. Ensure Product Availability

You can use a price monitoring solution to track product availability to ensure products are always in stock, even across different physical stores and online marketplaces. If a product is frequently sold out, you can adjust production levels or help retailers to improve their inventory management.

Key Takeaways: E-commerce Price Monitoring

Price monitoring software allows you to compare your products’ prices with competitors. This valuable data can help you:
- Optimize revenue through timely price changes and dynamic pricing
  Avoid being undercut by competitors
- Improve pricing strategies and promotions to increase sales and retain customers
- Maintain consistent prices across sales channels
To learn more, check out our article, What is Competitive Pricing Intelligence: The Ultimate Guide here or reach out and talk to us today!
August 1, 2024
Amazon Prime Day India 2024: Key Insights on Pricing and Visibility Across Categories and Brands
As the dust settles on Amazon’s 8th Prime Day extravaganza in India, held on July 20-21, 2024, the eCommerce giant has once again shattered records. This year’s event saw unprecedented engagement, with 24% more Prime members participating compared to 2023, marking the highest-ever Prime member involvement in the sale’s history.

At DataWeave, we’ve conducted an extensive analysis of this landmark event, examining over 47,000 SKUs across major categories for Flipkart and Amazon to uncover compelling insights into pricing strategies, competitive positioning, and emerging trends in the Indian eCommerce space. This follows our comprehensive analysis of Prime Day in the USA across categories and brands, which readers can explore for a global perspective on Amazon’s strategies.

Key Highlights:
- Tier-2 Cities Drive Growth: This year’s exponential growth was notably fueled by orders from tier-2 cities, highlighting the expanding reach of eCommerce in India.
- Swift Deliveries: Most Prime members’ orders from metros were delivered the same day or the next, while tier-2 cities saw deliveries in less than 2 days, highlighting the importance of delivery time when it comes to purchase decisions.
- Brand Participation: Over 450 top Indian and global brands participated, including Intel, Samsung, OnePlus, and Puma, alongside 3,200 new product launches from small and medium Indian businesses. This highlights Amazon’s policy to promote small, local businesses globally in 2024.
- Premium Products in Demand: Despite modest discounts across electronics and similar offerings, consumers chose to purchase premium products during Prime Day. With financial flexibility and no-cost EMI options, Indian consumers, especially Gen Z and millennials, are now ready to invest in premium products and experiences.
Our analysis focused on both the Additional Discounts offered during Prime Day (calculated relative to prices the week prior to the event), highlighting the event’s genuine benefits, and the Absolute Discounts offered during Prime Day, representing the total markdown relative to the MRP.

Cross-Category Discount Strategy

Our analysis this year reveals that the Consumer Electronics category saw the highest Absolute Discounts with an average of 48.9%, closely followed by Apparel at 46.9%. The Health & Beauty category had the lowest Absolute Discount at 32.1%.

However, Amazon offered the highest Additional Discount in Health & Beauty at 9.3%. Electronics and Apparel had additional discounts of 8.6% and 7.7% respectively.

Overall, Flipkart chose to not compete aggressively with Amazon during Prime Day this year. Only in Electronics did Flipkart offer an additional discount of 3.2% during the sale. Price changes in Apparel and Health & Beauty were negligible.

Category Deep Dive

Consumer Electronics

In Electronics, Earbuds (14.7%) and Wireless Headphones (12.5%) saw the highest Additional Discounts on Amazon, likely due to high demand for personal audio devices. Smartwatches followed closely at 12.5%, indicating a strong push in the wearable technology sector.

Larger electronic appliances like TVs saw more modest Additional Discounts (5.2%), despite a significant Absolute Discount (42.3%).

Smartphones, interestingly, had the lowest Additional Discount (2.8%) among the subcategories, potentially due to their already competitive pricing or brand-specific strategies.

Brand-level Insights in Consumer Electronics

During the sale event, Soundcore (headphone and earphone brand from Anker) led with the highest Additional Discount of 10.3%, followed closely by OnePlus at 9.3%. These brands clearly leveraged Prime Day to drive sales and potentially gain market share.

Sennheiser and Sony also offered significant additional discounts, indicating aggressive promotional strategies during the event.

Notably, some well-known brands like Apple and HP offered more conservative discounts, possibly due to their established market positions or differing promotional strategies.

Despite modest discounts though, Amazon revealed that the iPhone 13 and OnePlus 12R were among the top premium smartphones customers bought this Prime Day. Prime members shopped from top brands such as LG, IFB, Bosch, and Haier and upgraded to premium appliances through affordability options of no cost EMI, Bank discounts and exchange offers, claims Amazon.

These learnings offer valuable insight into the mindset of the modern Indian consumer, who is ready to purchase premium products. Brands can leverage more detailed market intelligence to drive their positioning in India.

Share of Search Analysis

The Share of Search (SoS) for a brand represents the number of its products in the top 20 search results for relevant search keywords on Amazon, relative to that of its competitors. It provides insights into a brand’s visibility during the sale event.

HP saw the most significant improvement in its Share of Search during Prime Day, gaining 9.2%, with strong growth in both organic (7.5%) and sponsored (1.7%) listings. LG also made substantial gains of 8.2% and 5.3% respectively. Both brands offered significant markdowns on laptops and accessories.

Surprisingly, some popular brands like Apple (-0.6%) and Acer (-1.0%) experienced slight decreases in their SoS. Lenovo notably lost 7.2% of its visibility share, with a significant decline in organic listings (-7.6%). Samsung maintained its strong position with an increase in SoS (3.7%).

Key Takeaways:

While some brands like Soundcore and OnePlus used aggressive discounting to drive sales, others like HP and LG focused on improving their search visibility. The data suggests that a combination of attractive discounts and improved search visibility was key to success during the event. Brands that managed to balance these factors effectively, like HP and Samsung, seemed to perform particularly well. Interestingly, some brands with lower discounts (like HP) still managed to significantly increase their SoS, indicating that factors beyond pricing played a role in visibility during the event.

Apparel

Within the subcategories analyzed, Women’s Shoes (13.4%) and Men’s Shoes (11.6%) saw the highest Additional Discounts on Amazon, indicating a strong focus on footwear during the event. Men’s Shirts followed closely at 11.1%

Women’s Tops had a more modest Additional Discount of 7.9% despite a high Absolute Discount before the event. Similarly, Women’s Dresses showed substantial Additional Discounts (10.4%).

Swimwear for both men and women saw low Additional Discounts (3.7% and 3.0% respectively). Innerwear categories for both men and women had more conservative discounts, with Men’s Innerwear showing the lowest Absolute Discount (19.9%) among all subcategories.

Brand-level Insights in Apparel

During the sale event, Sangani (innerwear brand) led with the highest Additional Discount of 41%, followed by Louis Philippe at 25%. These brands clearly leveraged Prime Day to drive sales and gain market share.

Puma offered the highest Absolute Discount at 60% with a significant Additional Discount of 20%, indicating a consistently aggressive promotional strategy. Chromozome (men’s innerwear brand) and Bacca Bucci (homegrown shoe brand of Shark Tank India fame) also offered substantial Absolute Discounts (57% and 56% respectively), but their Additional Discounts varied significantly (16% and 6% respectively).

Again, some well-known brands like Adidas, and Pepe Jeans offered more moderate Additional Discounts, possibly due to their established market positions.

Share of Search Analysis

Biba (women’s ethnic wear brand) saw the most significant improvement in its SoS, gaining 3.60%, entirely through investments in sponsored listings. Allen Solly and New Balance (shoe brand) also made substantial gains of 3.3% and 3.2% respectively.

Surprisingly, some popular brands like Louis Philippe (-2.00%) and Sangani (-2.10%) experienced decreases in their SoS. Louis Philippe lost its share due to a roll back of its sponsored listings, while Sangini lost ground organically.

Key Takeaways:

While some brands like Sangani and Louis Philippe used aggressive discounting to drive sales, others like Biba and Allen Solly focused on improving their search visibility through sponsored listings.

Some brands with high discounts (like Sangani) saw a decrease in SoS, while others with more modest discounts (like Biba) significantly increased their visibility. This indicates that factors beyond pricing played a crucial role in brand performance during the event.

The significant use of sponsored listings by some brands highlights the importance of paid advertising in gaining visibility during competitive events like Prime Day.

Health & Beauty

Health & Beauty emerged as a standout category during Amazon Prime Day India 2024, with significant discounts and competitive strategies at play.

Within the subcategories we analyzed, Moisturizer (11.9%) and Sunscreen (11.8%) saw the highest additional price reductions on Amazon, likely due to seasonal demand during Prime Days. Make-up followed closely at 10.6%.

Electric Toothbrushes had the highest Absolute Discount at 47.1%, but a lower Additional Discount of 6.0%, highlighting that these products were already significantly discounted before the event. Similarly, Beard Care products showed high Absolute Discounts (43.7%) but lower Additional Discounts (5.7%) during Prime Day.

Everyday essentials like Toothpaste saw more modest discounts (19.9% Absolute, 8.4% Additional), reflecting steady demand for these products.

Brand-level Insights in Health & Beauty

Vaseline led with the highest Additional Discount of 13.1%, followed by Maybelline at 9.5%. These brands clearly leveraged Prime Day to drive sales and potentially gain market share.

Honest Amish (beard care brand) and Nivea also offered substantial Absolute Discounts (15.6% and 8.2% respectively), but their Additional Discounts were lower, indicating pre-existing promotional strategies.

Once again, some well-known brands like Colgate, Dove, and Neutrogena offered more conservative discounts, possibly due to their established market positions or differing promotional strategies.

Share of Search Analysis

Maybelline saw the most significant improvement, gaining 5.6% in SoS, all through organic listings. The brand has been aggressively increasing market share with several new product launches and influencer campaigns. Nivea and Vaseline also made substantial gains of 5.2% and 3.8% respectively.

In this category as well, some popular brands like Dove (-0.4%), Pond’s (-0.8%), and Honest Amish (-0.8%) experienced slight decreases in their SoS. Parodontax (toothpaste brand) notably lost 1.3% SoS, with most of the decline in sponsored listings. Colgate maintained its strong position with a slight increase in SoS (0.2%), reflecting its dominant market presence.

Key Takeaways:

While some brands like Vaseline and Maybelline used aggressive discounting and improved visibility to drive sales, others like Colgate and Dove relied more on their established market positions.

None of the brands made any significant strides in sponsored listings, revealing that brands in this category are not yet fully leveraging retail media to help manage and boost their visibility on online marketplaces.

Final Thoughts

Amazon Prime Day 2024 has redefined the eCommerce landscape in India, yet again, showcasing diverse strategies employed by brands to maximize their impact. By understanding and leveraging these insights, brands and retailers can better navigate future sales events, optimizing their eCommerce strategies to achieve sustained growth and success.

Stay tuned to our blog for more in-depth analyses of brand and retailer performance across various retail events.

Reach out to us today to learn how you can leverage data-driven insights to optimize your eCommerce strategy.
August 1, 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
Cracking the Code: How Retailers Can Adapt to Plummeting Egg Prices in 2024
Virtually every cuisine in the world uses eggs. They’re in your breakfast, lunch, dinner, and dessert — which is perhaps why the global egg market is expected to generate $130.70 billion in revenue in 2024 and is projected to grow to approximately $193.56 billion by 2029.

More specifically, the United States is the fourth-largest egg producer worldwide. The country’s egg market is projected to generate $15.75 billion in 2024 and increase to $22.51 billion by 2029.

This growth is driven by several factors, most notably:
- Health-consciousness among consumers: Consumers value eggs for their essential nutrients and rich protein content.
- Demand for convenience foods: Consumers’ preferences are shifting toward quick and easy foods, which drives demand for shell eggs and pre-packaged boiled or scrambled eggs.
- Population Growth: A growing worldwide population increases the demand for eggs.
- Affordability and accessibility: Eggs are an affordable and accessible nutrient-dense food source for many.
Despite these factors contributing to the U.S. egg market’s growth, recent times have seen egg prices fall dramatically.

Based on a sample of 450 SKUs, DataWeave discovered that egg prices in the U.S. fell by 6.7% between April 2023 and April 2024, dipping to its lowest (-12.6%) in December 2023.

So, what’s causing the decrease in egg prices?

The Rise and Fall of Egg Prices: A Recent History

In 2022, avian influenza severely impacted the United States. The disease affected wild birds in nearly every state and devastated commercial flocks in approximately half of the country.

The 2022 incident was the first major outbreak since 2015 and led to the culling of more than 52.6 million birds, mainly poultry, to prevent the disease from spreading uncontrollably.

With almost 12 million fewer egg-laying hens, the United States produced around 109.5 billion eggs in 2022 — a drop of nearly two billion from the previous year.

Consequently, the cost of eggs soared, peaking at $4.82 a dozen — more than double the price of eggs in the previous year.

The avian flu continues to affect egg-laying hens and other poultry birds across the United States. As of April 2024, farms have killed a total of 85 million poultry birds in an attempt to contain the disease.

Despite the disease’s effects, production facilities have made significant efforts to repopulate flocks, leading to a steady increase in supply – and a much anticipated decrease in egg prices.

According to the U.S. Bureau of Labor Statistics, there was an increase in producer egg prices in 2022, reaching a peak in November 2022, at which point they began to fall.

Retailer’s egg prices followed suit. The egg price chart below depicts retailers’ declining egg prices over one year, from April 2023 to April 2024, with Giant Eagle showing the most significant price reductions and Walmart the least.

What Does the Future Hold for Egg Prices?

The USDA reported recent severe avian flu outbreaks in June 2024. These outbreaks are estimated to have affected 6.23 million birds.

With a reduction in egg-laying hens, egg prices are likely to increase — time will tell.

Nonetheless, the annual per capita consumption of eggs in the U.S. is projected to reach 284.4 per person in 2024 from 281.3 per person in 2023. So for now, producers and retailers can rest assured of the growing demand for eggs.

How Can Retailers Adapt to the Unpredictability of Egg Prices?

Egg prices were down to $2.69 for a dozen in May 2024. However, they are still significantly higher than consumers were used to just a few years ago—eggs were, on average, $1.46 a dozen in early 2020.

Additionally, while the avian flu puts pressure on producers, inflation and supply chain disruptions exert pressure on retailers.

With such challenging egg market conditions, what can retailers do to maintain customer loyalty amid reduced consumer spending while maintaining profitability?

1. Give the Customer What They Want: Increase Offerings of Organic, Cage-Free, and Free-Range Eggs

As mentioned, Data Bridge Market Research’s trends and forecast report highlighted a significant increase in consumer health consciousness. Additionally, animal welfare increasingly influences consumers’ purchasing decisions when buying meat and dairy products.

DataWeave data shows that the prices of organic, cage-free, and free-range eggs—such as those by brands like Happy Eggs and Marketside—have fallen less than those of non-organic, caged egg brands.

2. Increase Private-Label Offerings

Private labels typically offer retailers higher margins than national brands. These margins can shield consumers from sudden wholesale egg price swings, helping to preserve brand trust and consumer loyalty without sacrificing profitability.

Moreover, eggs are particularly suited to private labeling, given their uniform appearance and taste and the lack of product innovation opportunities.

Undoubtedly, this is why sales of private-label eggs dwarf sales of national egg brands in the United States. Statista reports that across three months in 2024, private label egg sales amounted to $1.55 billion U.S. dollars, while the combined sales of the top nine national egg brands totaled just $617.88 million U.S. dollars.

3. Price Intelligently

With the current and predicted fluctuations in egg prices over the foreseeable future, price competitiveness is paramount to margin management and customer loyalty.

This is especially true when lower prices are the primary factor influencing the average consumer’s choice of supermarket for daily essentials purchases.

AI-driven pricing intelligence tools like DataWeave give retailers valuable highly granular and reliable insights on competitor pricing and market dynamics. In today’s data-motivated environment, these insights are necessary for competitiveness and profitability.

Final Thoughts

Egg prices have fluctuated significantly due to the impact of avian flu. Despite recent price drops, future egg price increases are possible due to ongoing outbreaks. Retailers should adapt to unstable egg prices by increasing organic, free-range, cage-free, and private-label egg offerings while leveraging AI-driven pricing tools to maintain margins and customer loyalty.

Speak to us today to learn more!
July 18, 2024
Cinco de Mayo 2024 Pricing Insights: An Analysis of Discounts Amid Inflation
Cinco de Mayo is a vibrant celebration of Mexican-American and Hispanic heritage, marked by lively parades, festive tacos, and refreshing tequila across North America. For the service industry, brands, and retailers, this day offers a golden opportunity to roll out enticing promotions on beloved Mexican foods and beverages, drawing in large crowds and boosting sales.

Americans love to indulge in Mexican cuisine during Cinco de Mayo. Take avocados, for example: despite inflation, avocado sales soared to 52.3 million units this year, marking a 25% increase from last year, according to the Hass Avocado Board’s 2023 Holiday Report. Such festive events see a significant sales spike, largely driven by appealing discounts and special offers.

So, what discounts did retailers roll out this Cinco de Mayo?

At DataWeave, our cutting-edge data aggregation and analysis platform tracked and analyzed the prices and deals on Mexican food and alcohol products offered by leading retailers. Our in-depth analysis sheds light on their pricing competitiveness during Cinco de Mayo, revealing how pricing strategies differed across various subcategories and brands.

We conducted a similar analysis in 2022, allowing us to compare the prices of identical products this year versus last year. This comparison helps us understand the impact of inflation over the past two years on the prices offered today.

Our Methodology

For our analysis, we monitored the average discounts offered by major US retailers on over 2,000 food and beverage products during Cinco de Mayo, as well as in the days leading up to the event. Many retailers kick off their Cinco de Mayo promotions a week before, so we included the entire week leading up to May 5th in our analysis.

Key Details:
- Number of SKUs: 2000+
- Retailers Analyzed: Target, Amazon Fresh, Safeway, Walmart, Total Wines & More, Sam’s Club, Meijer, Kroger
- Categories: Food, Alcohol
- Analysis Period: April 28 – May 5
To truly demonstrate the value of Cinco de Mayo for shoppers, we concentrated on price reductions and additional discounts during the event. By comparing these with regular day discounts, we were able to highlight the genuine savings and benefits that Cinco de Mayo promotions offer to budget-conscious consumers.

Our Findings

Safeway led the pack with the highest average additional discount of 4.91%, covering 38.6% of their food inventory for Cinco de Mayo. Total Wine & More followed closely, offering an average discount of 3.46% across 70.8% of its tequila, whiskey, mezcal, and other spirit products during the Cinco de Mayo week.

In contrast, Target provided minimal additional discounts, averaging just 0.8% over a small fraction (11.6%) of its SKUs. Similarly, Kroger’s additional discounts were also 0.8%, but they were spread across over 60% of its tracked products. Walmart (1.4%) and Amazon Fresh (1.2%) offered relatively conservative discounts during the sale period.

During Cinco de Mayo, various brands rolled out attractive discounts to entice shoppers. Among beverage brands, The American Plains vodka led the way with the highest average discount of 20.80%. Coffee brands also joined the festivities with significant discounts: Death Wish Coffee at 14.30%, Dunkin’ at 11.10%, and Starbucks at 5.70%. Notably, Dunkin’ and Death Wish Coffee introduced complimentary beverages such as whiskey barrel-aged coffee and spiked coffee products to celebrate the event.

In the wine category, Erath stood out with a 10% additional discount. However, brands like Jose Cuervo and Franzia offered more modest discounts of 0.70% and 1.80%, respectively.

Food brands associated with traditional Mexican ingredients or products, such as tortillas, salsas, and spices, provided higher discounts compared to mainstream snack brands. For instance, McCormick (25%), El Monterey (13.3%), and La Tortilla Factory (16.7%)—known for ready-to-eat frozen foods, seasonings, and condiments—delivered the highest discounts. Other notable discounts included Jose Ole (12.5%), a frozen food brand, and Yucatan (8.3%), known for its guacamole.

Safeway’s private label brand, Signature Select, offered a 5.20% discount. Additionally, Safeway provided deep discounts on brands like Pace, Herdez, and Taco Bell, indicating an aggressive discounting strategy. In contrast, brands closely associated with Mexican or Tex-Mex cuisine, such as Old El Paso, Mission, Rosarita, and La Banderita, offered relatively modest discounts ranging from 0.5% to 3.3%.

The discount patterns varied between alcohol and food categories, with food brands generally offering higher discounts. This trend may be attributed to pricing being regulated in the alcohol industry. These differing discount levels highlight how brands navigated the balance between driving sales and maintaining profit margins during Cinco de Mayo, particularly in the context of inflation affecting costs.

Impact of Inflation on Cinco de Mayo Prices (2024 vs 2022)

To gauge the impact of inflation on popular Cinco de Mayo products, we analyzed the average prices at Walmart and Target between 2022 and 2024. These two retailers were chosen due to their prominence in the retail sector and the robustness of our sample data.

At Walmart, the Tex Mex category saw the highest average price increase, rising by 22.51%. Other notable subcategories with significant price hikes include Condiments (23.21%), Vegetables/Packaged Vegetables (21.22%), and Lasagne (14.10%). Categories like Dips & Spreads (13.77%), Pantry Staples (14.92%), and Salsa & Dips (8.23%) experienced relatively lower increases.

At Target, the Snacks subcategory had the steepest average price rise at 27.94%, followed by Meal Essentials (16.07%) and Deli Pre-Pack (8.82%). Categories such as Dairy (0.51%), Frozen Meals/Sides (7.11%), and Adult Beverages (7.41%) saw smaller price increases.

Brands associated with traditional Mexican or Tex-Mex cuisine faced higher price hikes. Examples include Old El Paso (24.59% at Walmart, 8.70% at Target), Tostitos (35.44% at Walmart, 11.41% at Target), Ortega (30.59% at Walmart, 19.69% at Target), and Rosarita (14.39% at Walmart).

In contrast, private label or store brands generally experienced lower price increases compared to national brands. For instance, Good & Gather (Target’s private label) saw a 9.55% increase, while Market Pantry (Walmart’s private label) had a 17.27% rise. This trend is understandable as retailers have more control over their costs with private label brands.

The data clearly indicates that both Walmart and Target have significantly raised prices across various categories and brands, reflecting the broader inflationary environment where the cost of goods and services has been steadily climbing.

Interestingly, we observed higher price increases at Walmart compared to Target. Although Walmart is renowned for its consumer-friendly pricing strategies, it too had to elevate grocery prices post-2022 to combat inflationary pressures. As consumers become more cost-conscious and reduce spending on discretionary items, Walmart and other retailers are now cutting prices across categories to align with shifting consumer behaviors.

Mastering Pricing Strategies During Sale Events

Our pricing analysis for Cinco de Mayo reveals compelling insights into the dynamics of retailer landscapes in the US. It highlights the enduring relevance of private label brands, even amidst fluctuating demand, showing the emergence of local, national, and small players vying for market share.

As retailers navigate inflationary pressures and evolving consumer behaviors, understanding these pricing dynamics becomes crucial for optimizing strategies and bolstering market competitiveness. This analysis offers actionable intelligence for retailers seeking to navigate the intricate terrain of sale event promotions while addressing shifting consumer preferences and economic challenges.

Access to reliable and timely pricing data equips retailers and brands with the tools needed to make informed decisions and drive profitable growth in an increasingly competitive environment. To learn more and gain guidance, reach out to us to speak to a DataWeave expert today!
May 22, 2024
How Monitoring and Analyzing End-User Prices can Help Retailers and Brands Gain a Competitive Edge
Retailers and brands are constantly engaged in a fierce battle over prices and discounts. Whether it’s major events like Amazon Prime Day, brand-led sales, or everyday price wars, they depend on pricing intelligence and digital shelf analytics to fine-tune their strategies. With a variety of offers such as sales, promotions, and bundles, determining the actual cost to the customer becomes a complex task. The price set by the brand, the retailer’s offer, and the final amount paid by the customer often vary significantly.

In their analysis, retailers and brands frequently focus on the listed price or the final sale price, overlooking a critical factor: the “end-user price.” This includes all discounts, taxes, and shipping costs, providing a more accurate picture of what customers are truly willing to pay at checkout.

Grasping this end-user price is vital for both retailers and brands. For retailers, it helps them stay competitive and refine their promotional strategies. For brands, it offers insights into competitive positioning, net revenue management, and shaping customer price perception.

However, emphasizing the end-user price is challenging, as it involves comprehending all the intricate elements of pricing.

How end-user pricing is calculated

The list price, also known as the manufacturer’s recommended retail price (MSRP), is the initial price set by the brand. This may not always be displayed on marketplaces, especially in categories like grocery. The selling price, on the other hand, is the amount at which a retailer offers the product, often reduced from the list price. The end-user price is the actual amount the customer pays at checkout, which includes taxes, promotions, and other factors that affect the final cost.

The process involves 3 key stages:

Step 1: Identifying and categorizing promotional offers

The first critical step in calculating end-user pricing is to identify and categorize the various promotional offers available for a given product that can reduce the final amount paid by the consumer. These promotions span a wide range of types:
- Bank Offers: Involving discounts or cash back incentives when paying with specific bank credit or debit cards. For instance, a customer may receive 10% cashback on their purchase by using a specific bank’s card.
- Bundled Deals: Combining multiple products or services at a discounted bundle price. A common example is a smartphone bundle including the phone itself, a protective case, and earphones at a reduced total cost.
- Promo Codes/Coupons: Customers can enter promo codes or coupons during checkout to unlock special discounted prices or percentage-off offers, like 20% off a hotel booking, or even a special brand discount personalized for their needs (think loyalty offers and in-app promotions).
- Shipping Offers: These include free shipping or reduced shipping fees for certain products or orders, such as free delivery on orders above a set amount.
- TPRs (Temporary Price Reductions): TPRs play a significant role in the strategies of most retailers. Brands and retailers use them to encourage shoppers to purchase more of a product or to try a new product they wouldn’t usually buy. A TPR involves reducing the price of a product by more than 5% from its regular shelf price.
By accurately identifying and classifying each type of promotion available, brands can then calculate the potential end-user pricing points.

Step 2: Accounting for location and fulfilment nuances (delivery, in-store pickup) that impact final pricing

Product pricing and promotional offers can vary based on the consumer’s location or ZIP code. Additionally, customers may opt for different fulfilment modes like delivery, shipping, or in-store pickup, which can further impact the final cost. Accurately calculating the end-user price necessitates considering these location-based pricing nuances as well as the chosen fulfilment method.

In the example below, the selling price is $4.32 for one retailer (on the left in the image) after a discount for online purchase. In another case with Meijer, the item total shows $17.91, but the consumer ends up paying $15.74 after taxes and fees are applied (on the right in the image).

Step 3: Applying each eligible promotion or offer to the selling price to determine potential end-user price points

With the various promotional offers and discounts categorized in the previous steps, retailers and brands can now apply each eligible promotion to the product’s selling price. This involves deducting percentages for bank cashback, implementing bundled pricing, applying coupon code discounts, and incorporating shipping promotions.

For retailers, this step allows them to calculate their true effective selling price to customers after all discounts and promotions. They can then compare this end-user price against competitors to ensure they remain competitively priced.

For brands, by systematically layering every applicable offer onto the baseline selling price, they can accurately calculate the multiple potential end-user price points a customer may pay at checkout for their products across different retailers and regions.

Why the end-user price matters

Optimizing pricing strategies using the end-user price can benefit retailers and brands in several ways:
- Price Competitiveness: By monitoring end-user pricing, retailers can adjust for discounts and promotional offers to attract customers, while brands can refine their pricing models to stay ahead in the market.
- Customer Acquisition and Loyalty: Offers, promotions, and discounts directly impact the final price paid by customers, playing a crucial role in attracting new customers and retaining existing ones. For example, Walmart’s competitive pricing in groceries boosts customer loyalty and repeat purchases.
- Consumer Perception: End-user pricing significantly shapes how consumers perceive both retailers and brands. Competitive pricing and promotional transparency enhance reputation and conversion rates. Amazon, for instance, is known for its competitive pricing and fast deliveries, which strengthen its consumer perception and satisfaction.
- Sales Volumes: The final checkout price influences affordability and perceived value, directly affecting sales volumes. Both retailers and brands benefit from understanding this, as it guides consumer purchasing decisions and drives revenue streams.
- Brand Perception: Consistent and transparent pricing enhances the perception of both the retailer and the brand. This not only strengthens the value proposition but also builds consumer trust and fosters long-term loyalty.
While the listed and selling prices are readily available, calculating the true end-user price is quite complex. It involves meticulous tracking and application of various types of promotions, offers, location-based pricing nuances, and fulfillment costs – an uphill task without robust technological solutions.

Track and Analyze end-user prices with DataWeave

DataWeave’s end-user price tracking capability empowers retailers and brands with the insights and tools necessary to comprehend the complexities of pricing dynamics. For retailers, it offers the ability to monitor end-user pricing across various products and categories compared to competitors, ensuring competitiveness after all discounts and enabling optimization of promotional strategies. Brands benefit from informed pricing decisions, optimized strategies across retail channels, and a strengthened position within their industries.

Our intuitive dashboard presents classified promotions and corresponding end-user prices across retailers, providing both retailers and brands with a transparent, comprehensive view of the end-user pricing landscape.

Within the detailed product view of DataWeave’s dashboard, the Price and Promotions panel showcases diverse promotions available across different retailers for each product, along with the potential end-user price post-promotions.

Harness the power of DataWeave’s sophisticated Pricing Intelligence and Digital Shelf Analytics to gain an accurate, real-time understanding of your end-user pricing dynamics. Make data-driven pricing decisions that resonate with customers and propel your brand toward sustained success.

Find out how DataWeave can empower your eCommerce pricing strategy – get in touch with us today or write to us at contact@dataweave.com!
May 15, 2024
Why Localized, Store-Specific Pricing and Availability Insights is Critical for Consumer Brands
Brands are becoming increasingly proficient in monitoring and refining their presence on online marketplaces, utilizing Digital Shelf Analytics to gather and analyze data on their online performance. These tools offer invaluable insights into enhancing visibility, adjusting pricing strategies, and improving content quality on eCommerce sites.

Yet, as the retail landscape shifts towards a more integrated omnichannel approach, it’s crucial for brands, particularly those in CPG, to apply similar strategies to their offline channels. For brands that count physical stores among their primary sales channels, gaining localized insights is key to boosting in-store sales performance.

Collecting shelf data from offline channels presents more challenges than online. Traditional methods, such as physical store visits, often fall short in reliability, timeliness, scale, and level of coverage.

However, the world of eCommerce provides a solution. As part of the effort to facilitate options like buy-online-pickup-in-store (BOPIS) for shoppers, major retailers make store-specific product details available online. Consumers often go online and select their nearest store to make purchases digitally before choosing a fulfillment option like picking up at the store or direct delivery. Aggregating this store-level information offers brands critical insights into pricing and inventory across a vast network of stores, enabling them to make informed decisions that improve pricing strategies and supply chain efficiency, thus minimizing stockouts in crucial markets.

Further, as consumers increasingly seek flexibility in how they receive their purchases—be it through in-store pickup, delivery, or shipping—brands need to adeptly monitor pricing and availability for these different fulfilment options. Such granular insight empowers brands to adapt swiftly and maintain a competitive edge in today’s dynamic retail environment.

Why does monitoring pricing and availability data across stores matter to brands?
- Hyperlocal Competitive Strategy: This allows brands to adjust their pricing strategies based on regional competition. By understanding the local market, brands can decide whether to position themselves as cost leaders or premium offerings. In particular, this is indispensable for Net Revenue Management (NRM) teams.
- Targeted Marketing Initiatives: Understanding regional price and availability enables brands to customize their marketing efforts for specific markets. By aligning their strategies with local demand trends and inventory levels, brands can more effectively engage their target audiences.
- Efficient Inventory Management: By keeping a close eye on store-level data, brands can better manage their stock, ensuring high-demand products are readily available while minimizing the risk of overstocking or running out of stock.
- Minimum Advertised Price (MAP) Monitoring: While brands cannot directly control retail pricing, staying updated on pricing trends helps them adjust their MAP to reflect the competitive landscape, consumer expectations, cost considerations, and regional differences. A strategic approach to MAP management supports brand competitiveness and profitability in a fluctuating market.
DataWeave’s Digital Shelf Analytics solutions equip brands with the necessary data and insights to do all of the above.

DataWeave’s Digital Shelf Analytics is location-aware

DataWeave’s Digital Shelf Analytics platform stands out with its sophisticated location-aware capabilities, enabling the aggregation and analysis of localized pricing, promotions, and availability data. Our platform defines locations using a range of identifiers, including latitudes and longitudes, ZIP codes, or specific stores, and can aggregate this data for particular states or regions.

The strength of the platform lies in its robust data collection and processing framework, which operates seamlessly across thousands of stores and regions. This system is designed to operate at configurable intervals—daily, weekly, or monthly—allowing brands to keep a vigilant eye on product availability, pricing strategies, and delivery timelines based on the selected fulfillment option.

Unlike many other providers, who may provide limited insights from a sample of stores, our solution delivers exhaustive analytics from every storefront. This comprehensive approach grants brands a strategic edge, facilitating efficient inventory tracking, precise pricing adjustments, and rapid responses to fluctuating market dynamics. It cultivates brand consistency and loyalty by enabling brands to adapt proactively to the changing landscape.

Aggregated store-level digital shelf insights via DataWeave

In the summarized view shown above, a brand can track how its various products are positioned across stores and retailers like Walmart, Amazon, Meijer, and others in the US.

Using DataWeave, brands can easily see important metrics like availability levels, prices, and other metrics across these stores gaining immediate visibility without having to physically audit them. the brand can track the same metrics for products across competitor brands and inform its own pricing, stock, and assortment decisions.

Store-level availability insights

We provide a comprehensive view of product availability, highlighting the distribution of out-of-stock (OOS) scenarios across various retailers and pinpointing the availability status throughout a brand’s network of stores. This capability enables swift identification of widespread availability issues, offering a bird’s-eye view of where shortages are most pronounced. By simply hovering over a specific location, detailed information about stock status and pricing for individual stores becomes accessible.

Such insights are crucial for brands to adapt their strategies, mitigate risks, and ensure they meet consumer needs despite the ever-changing retail ecosystem.

Store-level pricing insights

Retailers often adopt different pricing strategies to deal with margin pressure, local competition, and surplus stock. Grasping these pricing dynamics at a hyperlocal level enables brands to tailor their strategies effectively to maintain a competitive edge.

Our platform offers an in-depth look at how prices vary among retailers, across different stores, and throughout various regions. This analysis reveals the nuanced pricing tactics employed by retailers on a regional scale.

For example, brands might see that some retailers, like Kroger and Walmart in the chart below, maintain consistent pricing across their outlets, demonstrating a uniform pricing strategy. In contrast, others, such as Meijer and Shoprite, might adjust their prices to match local market conditions, indicating a more localized approach to pricing.

With DataWeave, brands can dive deeper into the pricing landscape of a specific retailer, examining a price map that provides detailed information on pricing at the store level upon hovering over a given location.

By presenting a historical analysis of average selling prices across different retailers, we equip brands with the insights needed to understand past pricing strategies and anticipate future trends, helping them to strategize more effectively in an ever-evolving market.

Digital Shelf Analytics that work for both eCommerce and brick-and-mortar store data

While established brands have made strides in gathering online pricing and availability data through Digital Shelf Analytics solutions, integrating comprehensive insights from both brick-and-mortar and eCommerce channels often remains a challenge.

DataWeave stands out for its capacity to collect data across diverse digital platforms, including desktop sites, mobile sites, and mobile applications. This capability ensures that omnichannel brands can have a holistic view of their pricing, promotional, and inventory strategies across all locations and digital landscapes.

Leveraging localized Digital Shelf Analytics to understand the intricacies of pricing and availability at the store level allows brands to fine-tune their approaches, swiftly adapt to local market shifts, and uphold a unified brand presence across the digital and offline spheres. This strategic agility places them in a favorable competitive position, enhancing customer satisfaction and trust, which are crucial for sustained success.

Know more about DataWeave’s Digital Shelf Analytics here.

Schedule a call with a specialist to see how it can work for your brand.
April 3, 2024
How AI-Powered Visual Highlighting Helps Brands Achieve Product Consistency Across eCommerce
As eCommerce increasingly becomes a prolific channel of sales for consumer brands, they find that maintaining a consistent and trustworthy brand image is a constant struggle. In an ecosystem filled with dozens of marketplaces and hundreds of third-party merchants, ensuring that customers see what aligns with a brand’s intended image is quite tricky. With many fakes and counterfeit products doing the rounds, brands may further struggle to get the right representation.

One way brands can track and identify inconsistencies in their brand representation across marketplaces is to use Digital Shelf Analytics solutions like DataWeave’s – specifically the Content Audit module.

This solution uses advanced AI models to identify image similarities and dissimilarities compared with the original brand image. Brands could then use their PIM platform or work with the retailer to replace inaccurate images.

But here’s the catch – AI can’t always accurately predict all the differences. Relying solely on scores given by these models poses a challenge in tracking the subtle differences between images. Often, image pairs with seemingly high match scores fail to catch important distinctions. Fake or counterfeit products and variations that slip past the AI’s scrutiny can lead to significant inaccuracies. Ultimately, it puts the reliability of the insights that brands depend on for crucial decisions at risk, impacting both top and bottom lines.

Dealing with this challenge means finding a balance between the number-based assessments of AI models and the human touch needed for accurate decision-making. However, giving auditors the ability to pinpoint variations precisely goes beyond simply sharing numerical values of the match scores with them. Visualizing model-generated scores is important as it provides human auditors with a tangible and intuitive understanding of the differences between two images. While numerical scores are comparable in the relative sense, they lack specificity. Visual interpretation empowers auditors to identify precisely where variations occur, aiding in efficient decision-making.

How AI-Powered Image Scoring Works

At DataWeave, our approach involves employing sophisticated computer vision models to conduct extensive image comparisons. Convolutional Neural Network (CNN) models such as Resnet-50 or YOLO, in conjunction with feature extraction models, analyze images quantitatively. This AI-powered image scoring process yields scores that indicate the level of similarity between images.

However, interpreting these scores and understanding the specific areas of difference can be challenging for human auditors. While computer vision models excel at processing vast amounts of data quickly, translating their output into actionable insights can be a stumbling block. A numerical score may not immediately convey the nature or extent of the differences between images

In the assessment of these images, all fall within the 70 to 80 range of scores (out of a maximum of 100). However, discerning the nature of differences—whether they are apparent or subtle—poses a challenge for the AI models and human auditors. For example, there are differences in the placement or type of images in the packaging, as well as packing text that are often in an extremely small font size. It is, of course, possible for human auditors to identify the differences in these images, but it’s a slow, error-prone, and tiring process, especially when auditors often have to check hundreds of image pairs each day.

So how do we ensure that we identify differences in images accurately? The answer lies in the process of visual highlighting.

How Visual Highlighting Works

Visual highlighting is a method that enhances our ability to comprehend differences in images by combining sophisticated algorithms with human understanding. Instead of relying solely on numerical scores, this approach introduces a visual layer, resembling a heatmap, guiding human auditors to specific areas where discrepancies are present.

Consider the scenario depicted in the images above: a computer vision model assigns a score of 70-85 for these images. While this score suggests relatively high similarity, it fails to uncover major differences between the images. Visual highlighting comes into play to overcome this limitation, precisely indicating regions where even subtle differences are seen.

Visual highlighting entails overlaying compared images and emphasizing areas of difference, achieved through techniques like color coding, outlining, or shading specific regions. The significance of the difference in a particular area determines the intensity of the visual highlight.

For instance, if there’s a change in the product’s color or a discrepancy in the packaging, these variations will be visually emphasized. This not only streamlines the auditing process but also enables human evaluators to make well-informed decisions quickly.

Benefits of Visual Highlighting
- Intuitive Understanding: Visual highlighting offers an intuitive method for interpreting and acting upon the outcomes of computer vision models. Instead of delving into numerical scores, auditors can concentrate on the highlighted areas, enhancing the efficiency and accuracy of the decision-making process.
- Accelerated Auditing: By bringing attention to specific regions of concern, visual highlighting speeds up the auditing process. Human evaluators can swiftly identify and address discrepancies without the need for exhaustive image analysis.
- Seamless Communication: Visual highlighting promotes clearer communication between automated systems and human auditors. Serving as a visual guide, it enhances collaboration, ensuring that the subtleties captured by computer vision models are effectively conveyed.
The Way Forward

As technology continues to evolve, the integration of visual highlighting methodologies is likely to become more sophisticated. Artificial intelligence and machine learning algorithms may play an even more prominent role in not only detecting differences but also in refining the visual highlighting process.

The collaboration between human auditors and AI ensures a comprehensive approach to maintaining brand integrity in the ever-expanding digital marketplace. By visually highlighting differences in images, brands can safeguard their visual identity, foster consumer trust, and deliver a consistent and reliable online shopping experience. In the intricate dance between technology and human intuition, visual highlighting emerges as a powerful tool, paving the way for brands to uphold their image with precision and efficiency.

To learn more, reach out to us today!

(This article was co-authored by Apurva Naik)
March 4, 2024
How DataWeave Enhances Transparency in Competitive Pricing Intelligence for Retailers
Retailers heavily depend on pricing intelligence solutions to consistently achieve and uphold their desired competitive pricing positions in the market. The effectiveness of these solutions, however, hinges on the quality of the underlying data, along with the coverage of product matches across websites.

As a retailer, gaining complete confidence in your pricing intelligence system requires a focus on the trinity of data quality:
- Accuracy: Accurate product matching ensures that the right set of competitor product(s) are correctly grouped together along with yours. It ensures that decisions taken by pricing managers to drive competitive pricing and the desired price image are based on reliable apples-to-apples product comparisons.
- Freshness: Timely data is paramount in navigating the dynamic market landscape. Up-to-date SKU data from competitors enables retailers to promptly adjust pricing strategies in response to market shifts, competitor promotions, or changes in customer demand.
- Product matching coverage: Comprehensive product matching coverage ensures that products are thoroughly matched with similar or identical competitor products. This involves accurately matching variations in size, weight, color, and other attributes. A higher coverage ensures that retailers seize all available opportunities for price improvement at any given time, directly impacting revenues and margins.
However, the reality is that untimely data and incomplete product matches have been persistent challenges for pricing teams, compromising their pricing actions. Inaccurate or incomplete data can lead to suboptimal decisions, missed opportunities, and reduced competitiveness in the market.

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

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

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

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

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

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

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

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

View Product Match Rates Across Websites

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

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

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

Track Data Freshness Easily

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

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

Proactively Manage Product Matches

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

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

Gain Unparalleled Visibility into your Data Quality

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

To learn more, reach out to us today!
January 22, 2024
Capturing and Analyzing Retail Mobile App Data for Digital Shelf Analytics: Are Brands Missing Out?
Consumer brands around the world increasingly recognize the vital role of tracking and optimizing their digital shelf KPIs, such as Content Quality, Share of Search, Availability, etc. These metrics play a crucial role in boosting eCommerce sales and securing a larger online market share. With the escalating requirements of brands, the sophistication of top Digital Shelf Analytics providers is also on the rise. Consequently, the adoption of digital shelf solutions has become an essential prerequisite for today’s leading brands.

As brands and vendors continue to delve further and deeper into the world of Digital Shelf Analytics, a significant and often overlooked aspect is the analysis of digital shelf data on mobile apps. The ability of solution providers to effectively track and analyze this mobile-specific data is crucial.

Why is this emphasis on mobile apps important?

Today, the battle for consumer attention unfolds not only on desktop web platforms but also within the palm of our hands – on mobile devices. As highlighted in a recent Insider Intelligence report, customers will buy more on mobile, exceeding 4 in 10 retail eCommerce dollars for the first time.

Moreover, thanks to the growth of delivery intermediaries like Instacart, DoorDash, Uber Eats, etc., shopping on mobile apps has received a tremendous organic boost. According to an eMarketer report, US grocery delivery intermediary sales are expected to reach $68.2 billion in 2025, from only $8.8 billion in 2019.

In essence, mobile is increasingly gaining share as the form factor of choice for consumers, especially in CPG. In fact, one of our customers, a leading multinational CPG company, revealed to us that it sees up to 70% of its online sales come through mobile apps. That’s a staggering number!

The surge in app usage reflects a fundamental change in consumer behavior, emphasizing the need for brands to adapt their digital shelf strategies accordingly.

Why Brands Need To Look at Apps and Desktop Data Differently

Conventionally, brands that leverage digital shelf analytics rely on data harnessed from desktop sites of online marketplaces. This is because capturing data reliably and accurately from mobile apps is inherently complex. Data aggregation systems designed to scrape data from web applications cannot easily be repurposed to capture data on mobile apps. It requires dedicated effort and exceptional tech prowess to pull off in a meaningful and consistent way.

In reality, it is extremely important for brands to track and optimize their mobile digital shelf. Several digital shelf metrics vary significantly between desktop sites and mobile apps. These differences are natural outcomes of differences in user behavior between the two form factors.

One of these metrics that has a huge impact on a brand’s performance on retail mobile apps is their search discoverability. Ecommerce teams are well aware of the adverse impact of the loss of even a few ranks on search results.

Anyone can easily test this. Searching something as simple as “running shoes” on the Amazon website and doing the same on its mobile app shows at least a few differences in product listings among the top 20-25 ranks. There are other variances too, such as the number of sponsored listings at the top, as well as the products being sponsored. These variations often result in significant differences in a brand’s Share of Search between desktop and mobile.

Share of Search is the share of a brand’s products among the top 20 ranked products in a category or subcategory, providing insight into a brand’s visibility on online marketplaces.

Picture a scenario in which a brand heavily depends on desktop digital shelf data, confidently assuming it holds a robust Share of Search based on reports from its Digital Shelf Analytics partner. However, unbeknownst to the team, the Share of Search on mobile is notably lower, causing a detrimental effect on sales.

To fully understand the scale of these differences, we decided to run a small experiment using our proprietary data analysis and aggregation platform. We restricted our analysis to just Amazon.com and Amazon’s mobile app. However, we did cover over 13,000 SKUs across several shopping categories to ensure the sample size is strong.

Below, we provide details of our key findings.

Share of Search on The Digital Shelf – App Versus Desktop

Our analysis focused on three popular consumer categories – Electronics, CPG, and Health & Beauty.

In the electronics category, brands like Apple, Motorola, and Samsung, known for their mobile phones, earbuds, headphones, and more, have a higher Share of Search on the Amazon mobile app compared to the desktop.

Meanwhile, Laptop brands like Dell, Acer, and Lenovo, as well as other leading brands like Google have a higher Share of Search on the desktop site compared to the app. This is the scenario that brands need to be careful about. When their Share of Search on mobile apps is lower, they might miss the chance to take corrective measures since they lack the necessary data from their provider.

In the CPG category, Ramen brand Samyang, with a lot of popularity on Tiktok and Instagram, shows a higher Share of Search on Amazon’s mobile app. Speciality brands like 365 By Whole Foods, pasta and Italian food brands La Moderna, Divinia, and Bauducco too have a significantly higher Share of Search on the app.

Cheese and dessert brands like Happy Belly, Atlanta Cheesecake Company, among others, have a lower Share of Search on the mobile app. Ramen brand Sapporo is also more easily discovered on Amazon’s desktop site. Here, we see a difference of more than 5% in the Share of Search of some brands, which is likely to have a huge impact on the brand’s mobile eCommerce sales levels and overall performance.

Lastly, in the Health & Beauty category, Shampoos and hair care brands like Olaplex, Dove, and Tresemme exhibited a higher Share of Search on the mobile app compared to the desktop.

On the other hand, body care brands like Neutrogena and Hawaiian Tropic, as well as Beardcare brand Viking Revolution displayed a higher Share of Search on Amazon’s desktop site.

Based on our data, it is clear that there are several examples of brands that do better in either one of Amazon’s desktop sites or mobile apps. In many cases, the difference is stark.

So What Must Brands Do?

Our findings emphasize the imperative for brands to move beyond a one-size-fits-all approach to digital shelf analytics. The striking variations in Share of Search between mobile apps and desktops conclusively demonstrate that relying solely on desktop data for digital shelf optimization is inadequate.

If brands see that they’re falling behind on the mobile digital shelf, there are a few things they can do to help boost their performance:
- If a brand’s Share of Search is lower on the mobile app, they can divert their retail spend to mobile in order to inorganically compensate for this difference. This way, any short-term impact due to lower discoverability is mitigated. This is also likely to result in optimized budget allocation and ROAS.
- Brands also need to ensure their content is optimized for the mobile form factor, with images that are easy to view on smaller screens, and tailored product titles that are shorter than on desktops, highlighting the most important product attributes from the consumer’s perspective. Not only will this help brands gain more clicks from mobile shoppers, but this will also gradually lead to a boost in their organic Share of Search on mobile.
- CPG brands, specifically, need to optimize their digital shelf for delivery intermediary apps (along with marketplaces). The grocery delivery ecosystem is booming with companies like DoorDash, Delivery Hero, Uber Eats, Swiggy, etc. leading the way. Using Digital Shelf Analytics to optimize performance on delivery apps is quite an involved process with a lot of bells and whistles to consider. Read our recently published whitepaper that specifically details how brands can successfully boost their visibility and conversions on delivery apps.
But first, brands need to identify and work with a Digital Shelf Analytics partner that is able to capture and analyze mobile app data, enabling tailored optimization approaches for all eCommerce platforms.

DataWeave leads the way here, providing the world’s most comprehensive and sophisticated digital shelf analytics solution, rising above all other providers to provide digital shelf insights for both web applications and mobile apps. Our data aggregation platform successfully navigates the intricacies of capturing public data accurately and reliably from mobile apps, thereby delivering a comprehensive cross-device view of digital shelf KPIs to our brand customers.

So reach out to us today to find out more about our digital shelf solutions for mobile apps!
January 19, 2024
The Indian E-Commerce Showdown: Unveiling the Price War Between Flipkart’s Big Billion Days and Amazon’s Great Indian Festival
India’s homegrown eCommerce giant Flipkart, now backed by Walmart, reported a record 1.4 Billion customer visits during the early access phase and throughout the seven days of its premier shopping event, the Big Billion Days, launched on 8th October 2023. Competing with Flipkart, Amazon’s Great Indian Festival sale event started on October 8th as well and saw a whopping 95 Million customer visits to the website within the first 48 hours of the event.

For consumers, the most pressing question was, “Who offered more attractive deals and lower prices during these sale events?”

To answer this question, we leveraged our proprietary data aggregation and analysis platform and analyzed the prices and discounts on Amazon and Flipkart across key product categories..

The details of our sample are mentioned below:
- Number of SKUs Analyzed: 30,000+
- Websites: Amazon.com and Flipkart.com
- Categories: Apparel, Home & Furniture, Electronics, Health & Beauty
- Dates: 7th Oct 2023 to 22nd Oct 2023
Key Findings

Based on our analysis, the Big Billion Days by Flipkart showcased relatively higher price reductions across categories compared to the Great Indian Festival sale by Amazon. The Apparel category on Flipkart saw the highest average discount at 50.6%. The Health & Beauty category had the lowest discount across Flipkart at 39.4% and Amazon at 33%.

Overall, Flipkart offered higher discounts in each product category. It is clear that the retailer invested heavily in leveraging its supplier partnerships with key brands or sellers to enable them to offer higher discounts, thereby attracting more customers.

Next, let’s take a closer look at each product category.

Apparel

While a majority of retailers expected demand for apparel and clothing to dip this festive season in India, eCommerce giants like Amazon and Flipkart are likely to recognize the strong consumer inclination towards apparel during this period.

In the detailed assessment of Apparel sub-categories, Women’s Dresses, Women’s Tops, Men’s Shirts, Men’s Shoes, and Women’s Innerwear emerged as the segments showcasing the most substantial discounts during the sale events. While Flipkart offered higher average discounts across all sub-categories, Amazon offered competitive discounts as well.

We observed significant differences in the average discounts across brands between Flipkart’s Big Billion Days and Amazon’s Great Indian Festival. Reinforcing the significant discounts on the Shoes subcategory, brands like Red Tape, Arrow, Adidas, Reebok, Nike, and more offered extensive discounts on both Flipkart and Amazon. Notably, Adidas and Reebok offered better deals on Amazon’s Great Indian Festival as compared to Flipkart.

One8 by Virat Kohli had a significantly lower discount on Amazon compared to Flipkart, indicating an exclusive partnership.

For brands, however, reducing prices is just one approach to entice shoppers. They must also guarantee their prominent presence and easy discoverability within Amazon and Flipkart search results. To gain insight into this, we monitored brands’ Share of Search across various frequently used search terms in addition to the discounts they provided. The Share of Search denotes the portion of a brand’s products within the top 20 search results for a specific search query.

Our data indicates that Jockey and Speedo gained in Share of Search on Flipkart, but reduced discoverability on Amazon. Van Heusen fell behind in search results on Flipkart but showed a higher Share of Search on Amazon.

Home & Furniture

With demand for home and furniture products picking up in October, right before the festive season, Amazon and Flipkart offered significant discounts in this category.

Discounts on both Amazon and Flipkart hovered around 50%. Across a few subcategories, Flipkart offered slightly lower discounts compared to Amazon. Only Luggage, Rugs, Sofas, and Entertainment Units saw lower markdowns on Flipkart during the Big Billion Days.

Dishwashers and Washer/ Dryers saw higher discounts on Amazon compared to Flipkart. The significant discounts on these products on Amazon possibly point to changing consumer preferences, as demand for these products is traditionally low in India, but seems to be growing.

When it comes to Home & Furniture brands, Nasher Miles, Safari, Aristocrat, VIP, and American Tourister, luggage brands mostly, offered higher discounts on Flipkart, followed closely by Amazon.

In terms of Share of Search, Skybags had high discoverability on both Flipkart and Amazon. The brand leveraged a strategy of offering big discounts this festive season as well as ensuring prominent placement in search results. Wildcraft lost out on its discoverability on Flipkart in contrast to its prominence on Amazon. Duroflex saw lower searchability on Amazon compared to Flipkart’s Big Billion Days.

Consumer Electronics

The Consumer Electronics and Appliances Manufacturers Association (CEAMA) expected an uptick in sales of consumer electronics products this festive season in India. With more consumers buying premium products using credit cards and EMIs, demand for expensive, high-end electronics was expected to increase.

Again, average discounts in this category hovered around 50% on Flipkart and Amazon.

Across electronics subcategories, Smartwatches, Earbuds, and Drones had the highest markdowns with Flipkart leading the pack during the Big Billion Days. Amazon offered relatively higher discounts at 44.9% on the TV subcategory, compared to Flipkart’s 40.6%.

Speakers, Laptops, Smartphones, and Tablets also saw lower markdowns on Amazon compared to Flipkart. Amazon was the official partner for the launch of many high-level smartphones and products in September-October, contributing to the higher markdowns in the subcategory.

Across brands, Lenovo’s discounts were the most differentiated between the two sites, with the brand offering higher discounts on Amazon (45.4%) compared to Flipkart (24.7%). Noise offered the highest discounts at 72.5% on Amazon and 52.8% on Flipkart. Brands like Boat and Zebronics, also saw lower discounts on Flipkart.

Mi and JBL offered deeper discounts on Flipkart’s Big Billion Days. Apple meanwhile stands out with only 11.83% discounts on Amazon, but the brand offered impressive 31.4% discounts on Flipkart.

Samsung dominated the Share of Search on Amazon at 15.7%, compared to only 2.6% on Flipkart. Apple and Lenovo also saw higher discoverability on Amazon. On Flipkart, JBL and Skullcandy stand out as brands with high search visibility.

Health & Beauty

The Health & Beauty category saw the lowest markdowns with only 39.4% discounts on Flipkart and 33% on Amazon.

In the subcategories analyzed, Electric Toothbrushes had relatively high markdowns across both sites. Staple and lower priced subcategories like Toothpaste had the lowest markdowns across both sale events, with Amazon offering only 17.4% average discounts.

Across brands, Beardo, a leading beard care brand, offered significantly higher discounts on Amazon compared to Flipkart. Most other well-known brands, including Nivea and Vaseline, saw higher discounts on Amazon compared to Flipkart. Only Tresmme and Dove were exceptions with higher discounts on Flipkart.

In terms of Share of Search, once again, Beardo was the most discoverable brand in this category. Brands like Dove, Pond’s, Swiss Beauty, and Tresemme saw a lower Share of Search on Flipkart compared to Amazon.

Navigating the Competitive Landscape: How To Thrive During Sale Events

Amazon and Flipkart’s strategic pricing during the Big Billion Days and the Great Indian Festival Sale reflects a balance of profitability, inventory, and competition. Competitive pricing insights empower retailers to make informed decisions, optimize strategies, and thrive during high-stakes sale events with timely and relevant insights at a massive scale.

To learn more about how you can leverage competitive pricing insights to stay ahead of the game during sale events, reach out to us today!
December 20, 2023