Competitive pricing intelligence is pivotal for retailers seeking to analyze their product pricing in relation to competitors. This practice is essential for ensuring that their product range maintains a competitive edge, meeting both customer expectations and market demands consistently.
Product matching serves as a foundational element within any competitive pricing intelligence solution. Products are frequently presented in varying formats across different websites, featuring distinct titles, images, and descriptions. Undertaking this process at a significant scale is highly intricate due to numerous factors. One such complication arises from the fact that products are often displayed with differing units of measurement on various websites.
The Challenge of Varying Units
In certain product categories, retailers often offer the same item in varying volumes, quantities, or weights. For instance, a clothing item might be available as a single piece or in packs of 2 or 3, while grocery brands commonly sell eggs in counts of 6, 12, or 24.
Consider this example: a quick glance might suggest that an 850g pack of Kellogg’s Corn Flakes priced at $5 is a better deal than a 980g pack of Nestle Cornflakes priced at $5.2. However, this assumption can be deceptive. In reality, the latter offers better value for your money, a fact that only becomes evident through price comparisons after standardizing the units.
This issue is particularly relevant due to the prevalence of “shrinkflation,” where brands adjust packaging sizes or quantities to offset inflation while keeping prices seemingly low. When quantities, pack sizes, weight, etc. reduce instead of prices increasing, it’s important that this change is considered while analyzing competitive pricing.
Normalizing Units of Measure
In order to effectively compare prices among different competitors, retailers must standardize the diverse units of measurement they encounter. This standardization (or normalization) is crucial because price comparisons should extend beyond individual product SKUs to accommodate variations in package sizes and quantities. It’s essential to normalize units, ranging from “each” (ea) for individual items to “dozen” (dz) for sets, and from “pounds” (lb), “kilograms” (kg), “liters” (ltr), to “gallons” (gal) for various product types.
For example, a predetermined base unit of measure, such as 100 grams for a specific product like cornflakes, serves as the reference point. The unit-normalized price for any cornflake product would then be the price per 100 grams. In the example provided, this reveals that Kellogg’s is priced at $0.59 per 100 grams, while Nestle is priced at $0.53 per 100 grams.
Various Categories of Unit Normalization
1. Weight Normalization
Retailers frequently feature products with weight measurements expressed in grams (g), kilograms (kg), pounds (lbs), or ounces (oz).
2. Quantity or Pack Size Normalization
Products are also often featured with varying pick sizes or quantities in each SKU.
3. Volume or Capacity Normalization
Products can also vary in volumes or capacities with units like liters (L) or fluid ounces (fl oz).
DataWeave’s Unit Normalized Pricing Intelligence Solution
DataWeave’s highly sophisticated product matching engine can match the same or similar products and normalize their units of measurement, leading to highly accurate and actionable competitive pricing insights. It standardizes different units of measurement, like weight, quantity, and volume, ensuring fair comparisons across similar and exact matched products.
Retailers have the flexibility to view pricing insights either with retailer units or normalized units. This capability empowers retailers and analysts to perform accurate, in-depth analyses of pricing information at a product level.
In some scenarios, analyzing unit normalized pricing reflects pricing trends and competitiveness more accurately than retail price alone. This is particularly true for categories like CPG, where products are sold in diverse units of measure. For instance, in the example shown here, we can view a comparison of price position trends for the category of Fruits and Vegetables based on both retail price and unit price.
The difference is striking: the original retail price based analysis shows a stagnation in price position, whereas unit normalized pricing analysis reflects a more dynamic pricing scenario.
With DataWeave, retailers can specify which units to compare, ensuring that comparisons are made accurately. For example, a retailer can specify that unit price comparisons apply only to 8, 12, or 16-ounce packs, as well as 1 or 3-pound packs, but not to 10 and 25-pound bags. This precision ensures that products are matched correctly, and prices are represented for appropriately normalized units, leading to more accurate pricing insights.
For consumer brands, the digital marketplace presents an unparalleled landscape of opportunities for engaging with consumers and expanding their market presence. Within this dynamic environment, Digital Shelf Analytics has emerged as a crucial pillar in a brand’s eCommerce strategy. This technology provides valuable insights into a brand’s organic and paid visibility on marketplaces, content quality, pricing strategies, promotional efforts, and product availability. These insights help brands gain a comprehensive understanding of their competitive positioning and overall market performance.
Nevertheless, many brands often grapple with the question of whether this understanding translates into tangible actions that drive real business impact and return on investment (ROI). This uncertainty stems from a lack of clarity about the direct correlation between digital shelf insights and key metrics such as enhanced sales conversions.
Nonetheless, there is compelling evidence that when these insights are effectively harnessed and strategic actions are taken, brands can realize significant, measurable benefits.
So, the question arises: does Digital Shelf Analytics genuinely deliver on its promises?
At DataWeave, we’ve partnered with numerous brands to fuel their eCommerce growth through the application of digital shelf analytics. In this article, we will delve into these insights, uncovering the concrete and quantifiable results that brands can achieve through their investments in digital shelf analytics.
Digital Shelf KPIs and Their Impact
Digital Shelf Analytics is a robust system that analyzes specific key performance indicators (KPIs) about the digital shelf, furnishing brands with precise recommendations to not only bolster these KPIs but also to monitor the enhancements over time. The following is a brief explanation of digital shelf KPis and their expected impact areas:
Product Availability: Ensuring Shoppers Never Hear “Out of Stock” Again
Timely insights on the availability of products ensures brands reduce replenishment times at scale, which can significantly impact sales, creating an unbreakable link between product availability and revenue. With Digital Shelf Analytics, procurement and replenishment teams can set up notifications to promptly identify low or out-of-stock items and take swift action. This can also be done for specific ZIP codes or individual stores. In addition, availability plays a crucial role in a brand’s Share of Search and search rankings, as online marketplaces often ensure only in-stock products are shown among the top ranks.
If a product isn’t visible, does it even exist? In fact, 70% of consumers never go beyond the first page of search results on major online marketplaces. Therefore, as a brand, the visibility of your products for relevant search keywords and their appearance on the first page can heavily determine your awareness metrics. This is where the concept of Share of Search comes into play. Think of it as securing prime shelf space in a physical store. Digital shelf insights and benchmarking with category leaders for Share of Search help ensure your products command relevant attention on the digital shelf.
Content Quality: Crafting the Perfect Product Story
Creating engaging product descriptions and visuals is akin to giving your products a megaphone in a crowded marketplace. By enhancing content quality, including product names, titles, descriptions, and images, brands can climb the search result rankings, leading to increased visibility and subsequently, more sales.
Ratings and Reviews: The Power of Social Proof
Public opinion holds immense sway. Research indicates that a single positive review can trigger a 10% surge in sales, while a multitude of favorable reviews can propel your product to a 44% higher trajectory. The correlation between ratings and sales is not surprising—each step up the rating ladder can translate to substantial revenue growth.
While it’s reasonable to anticipate a connection between these KPIs and downstream impact metrics such as impressions, clicks, and conversions, we were driven to explore this correlation through the lens of real-world data. To do so, we meticulously monitored the digital shelf KPIs for one of our clients and analyzed the improvements in these metrics.
It’s essential to acknowledge that not all observed impact areas can be solely attributed to enhancements in digital shelf KPIs. Still, it’s evident that a robust correlation exists. The following section presents an in-depth case study, shedding light on the results of this analysis.
A Success Story: Real-World Impact of Digital Shelf Analytics
Let’s dive into the journey of one of our clients – a prominent CPG brand specializing in the sale of baked goods and desserts. Through their experience, we will illustrate the transformative impact of our DataWeave Digital Shelf Analytics product suite.
Over a period of one year, from August 2022 to July 2023, the brand leveraged several key modules of Digital Shelf Analytics for Amazon, including Share of Search, Share of Category, Availability, Ratings and Reviews, and Content Audit. Each of these digital shelf KPIs played a vital role in shaping the brand’s performance across various stages of the buyer’s journey.
The buyer’s journey is typically delineated into three key stages:
Awareness: At this stage, shoppers peruse multiple product options presented on search and category listing pages, gaining an initial understanding of the available choices.
Consideration: Here, shoppers narrow down their selections and evaluate a handful of products, moving closer to a purchase decision.
Conversion: In this final stage, shoppers make their ultimate product choice and proceed to complete the purchase.
Let’s now examine the data to understand how digital shelf KPIs helped drive tangible ROI on Amazon for the brand across the stages of the buyer journey.
Stage 1: Raising Awareness
Enhancing Share of Search and Share of Category can help brands boost product visibility and raise brand awareness. The following chart demonstrates the steady, incremental improvements in our client’s Share of Search and Share of Category (in the top 20 ranks of each listing page) throughout the analyzed period. These enhancements were achieved through various measures, including product sponsorship, content enhancement, price optimization, promotional initiatives, and more.
This amplified Share of Search and Share of Category directly translates into improved product discoverability, as evident from the surge in impressions depicted in the chart below.
Stage 2: All Things Considered
In the consideration stage, shoppers make their product selections by clicking on items that meet their criteria, which may include factors like average rating, number of ratings, price, product title, and images. For brands, this underscores the importance of crafting meticulously detailed product content and accumulating a substantial number of ratings.
The subsequent chart illustrates the year-long trend in both average ratings and the number of ratings, both of which have displayed steady improvement over time.
The enhancements in the number of ratings and the average rating have a direct and positive impact on product consideration. This, in turn, has led to a noticeable year-over-year increase in page views, as indicated in the chart below.
These improvements are likely to have also been influenced by the overall enhancement of content quality, which is detailed separately in the section below.
Stage 3: Driving Decisions
As buyers progress to the next stage, they reach the pivotal point of making a purchase decision. This decision is influenced by multiple factors, including product availability, content quality, and the quality of reviews, reflecting customer sentiment.
Our client effectively harnessed our Availability insights, significantly reducing the likelihood of potential out-of-stock scenarios and enhancing replenishment rates, as highlighted in the chart below. The same chart also indicates improvements in content quality, measured by the degree to which the content on Amazon aligns with the brand’s ideal content standards.
Below, you’ll find the year-over-year growth in conversion rates for the brand on Amazon. This metric stands as the ultimate measure of business impact, directly translating into increased revenue for brands.
As the data uncovers, growth in key digital shelf KPIs cumulatively had a strong correlation with impressions, page views, and conversion rates.
It is also important to note that the effect of each KPI cannot be viewed in isolation, since they are often interdependent. For example, improvement in content and availability could boost Share of Search. Accurate content could also influence more positive customer feedback. Brands need to consider optimizing digital shelf KPIs holistically to create sustained business impact.
Impact on eCommerce Sales
After the implementation of digital shelf analytics, the results spoke for themselves. Sales consistently outperformed the previous year’s records month after month. As shown in the chart below, the diligent application of DataWeave’s recommendations paved the way for an impressive 8.5% year-over-year increase in sales, leaving an indelible mark on the brand’s eCommerce success.
From boosting product visibility to catapulting conversion rates, Digital Shelf Analytics serves as the key to unlocking unparalleled online success.
While the success story detailed above does not establish a direct causation between Digital Shelf Analytics and sales revenue, there is undoubtedly a strong correlation. It’s evident that digital shelf KPIs play a pivotal role in optimizing a brand’s eCommerce performance across all stages of the buyer journey. Hence, for brands, it is vital that they collaborate with the right partner and harness digital shelf insights to fine-tune their eCommerce strategies and tactics.
That said, the eCommerce landscape is in a constant state of flux, and there is still much to learn about how each digital shelf KPI influences brand performance in the online realm. With more data and an increasing number of brands embracing Digital Shelf Analytics, it’s only a matter of time before a direct causation is firmly established.
Reach out to us today to know more about how your brand can leverage Digital Shelf Analytics to drive higher sales and market share in eCommerce.
Consider this scenario: A retailer establishes its fuel prices using pricing data that’s a few days old, only to subsequently discover that a nearby competitor is offering substantially lower prices. The result? Lost customers, decreased foot traffic, and diminished sales. This serves as a stark reality that retailers must confront and address today.
In the fiercely competitive realm of retail, where every decision holds weight, maintaining a competitive edge is paramount. The fuel category, frequently underestimated, has the potential to significantly impact a retailer’s revenue stream. This challenge is not unique; retailers worldwide, particularly in North America, grapple with a common hurdle: mastering the intricate art of real-time fuel pricing.
The Quest For Reliable, Real-Time Fuel Pricing Data
For retailers, traditional methods for procuring and analyzing fuel price data have proven to be both expensive and error-prone, often relying on manual data collection or third-party data providers. These outdated approaches yield frustrating delays, inaccuracies, and missed opportunities. When it comes to obtaining timely fuel pricing intelligence, the majority of fuel retailers grapple with three central challenges:
Low Accuracy: Ensuring that fuel pricing information remains up-to-date, dependable, and actionable, even when sourced from complex web-based platforms.
Less Coverage: Acquiring comprehensive data that encompasses all of North America, spanning across retailers, convenience stores, fuel stations, and beyond.
High Cost: Effectively managing the substantial costs associated with acquiring and processing this vital information.
DataWeave’s Fuel Pricing Intelligence Solution
Comprehensive, accurate, and real-time fuel pricing intelligence can play a huge role in the profitability of retailers throughout North America. DataWeave takes the forefront in delivering this transformative Data-as-a-Service (DaaS) solution to some of the most prominent retailers in the region, including the top 20 fuel retail behemoths.
With a rich and extensive history spanning over a decade in the realm of competitive intelligence, DataWeave boasts an impressive track record of empowering well-informed decision-making in retail. We leverage state-of-the-art technology to bring an unparalleled level of accuracy, timeliness, and coverage to fuel pricing intelligence.
The following are some compelling advantages offered by our solution:
Accurate and Real-Time First Party Data
We deliver retailers an unparalleled advantage through real-time, first-party fuel price data. Our data originates directly from the retailer’s own channels, encompassing websites and mobile apps, rendering it the industry’s foremost and most reliable source.
Imagine having access to fuel pricing information that updates as frequently as every 30 minutes. This rapid update cadence guarantees that you, as a retailer, constantly possess the latest pricing insights at your fingertips, empowering you to respond swiftly to market fluctuations and competitor manoeuvres. Our comprehensive data spans a wide spectrum of fuel types, including:
Gasoline: Be it regular, mid-grade, super, premium, ethanol-free, ethanol blends, methanol blends, or reformulated gasoline, we have got you covered.
Diesel: Our data encompasses biodiesel, biodiesel off-road, biodiesel blends, biodiesel ultra-low sulfur (ULS), diesel ultra-low sulfur (ULS), diesel off-road, standard diesel, and premium diesel.
Armed with our real-time, first-party data, you can make pricing decisions with unwavering confidence, secure in the knowledge that you possess access to the most current, authoritative, and extensive fuel pricing intelligence in North America.
The data points we capture directly from relevant web sources include: gas station postal code, store name and code, location, city, state, ZIP code, fuel type, competitor name, regular price, member price (if available), time and date of data capture, and more.
Click here if you wish to access a sample report of our fuel pricing data.
Unrivaled Geographical Coverage
Our extensive coverage of fuel data spans over 30,000 ZIP codes and encompasses the top 100 retailers across the western, mid-western, and eastern regions of the United States.
Retailers benefit from the flexibility to configure and tailor the solution to their precise needs, whether it involves adding more locations or selectively acquiring specific segments of the data. This far-reaching coverage guarantees that retailers, whether situated in bustling urban centers or remote areas, can readily access the essential data required to maintain their competitive edge.
Moreover, if you currently source your fuel pricing data from alternative providers, our solution seamlessly integrates, amplifies, and complements your existing array of data sources, ensuring a harmonious and unified approach to data acquisition.
Optimization of Dynamic Pricing Strategies
In the world of retail, the importance of timing cannot be overstated. Even a mere difference of a few cents can translate into millions of dollars in revenue impact. With DataWeave, retailers gain the capability to make data-driven decisions that provide them with a competitive edge around the clock, every single day.
Our platform empowers you to unearth margin gaps by pinpointing opportunities to raise prices while maintaining your competitive pricing position. It also identifies instances where you may be substantially overpriced, prompting necessary price adjustments to ensure competitiveness within the market. All these valuable insights are available at a hyperlocal level, facilitating pricing efficiency and optimization across your various regions of coverage. Equipped with this real-time data, you can swiftly adapt to ever-changing market conditions.
Furthermore, our comprehensive competitive data seamlessly integrates into your existing pricing systems through APIs, facilitating quick and informed pricing actions based on robust data.
Reliable and Customer-First Tech Platform
Our platform boasts a remarkable level of sophistication when it comes to data aggregation, normalization, visualization, and integration capabilities. It stands as a massively scalable system with the capacity to aggregate billions of data points daily, spanning thousands of web sources. This includes the intricate handling of sources like mobile apps and websites known for frequently altering their site structures, among others.
What truly sets us apart is our proficiency in addressing these challenges through a blend of human expertise and large-scale machine learning. Additionally, our commitment to delivering unmatched service extends to round-the-clock, 24/7 support. This comprehensive approach makes our fuel pricing intelligence solution not only effective but also cost-efficient in meeting your fuel data requirements.
We also provide a variety of options for you to consume our data, which includes receiving our reports via email, SFTP, S3 buckets, data lakes like Snowflake, and APIs.
Enhance your Fuel Pricing Strategies with DataWeave
In the ever-competitive world of retail, staying ahead is not just a goal; it’s a necessity. The fuel pricing landscape, often overlooked, holds immense power to impact a retailer’s profitability. DataWeave’s real-time, comprehensive, and accurate fuel pricing intelligence solution is the key to securing this advantage. Retailers and convenience stores now have a powerful platform at their disposal, offering unparalleled precision, comprehensive coverage, and the agility needed to navigate this landscape.
Join the ranks of industry leaders who have already harnessed the potential of DataWeave. Reach out to us today to redefine your approach to fuel pricing and propel your business to new heights!
In the evolving retail landscape, success often hinges on a singular focal point: pricing. A recent Statista survey revealed that 70% of US online users prioritize competitive pricing in their digital shopping choices. In this cutthroat arena, where surpassing rivals is paramount, a deep comprehension of pricing nuances is no longer just an edge, but a necessity.
Retailers are increasingly adopting pricing intelligence solutions that meticulously dissect competitor pricing data in comparison to their own, down to the SKU level. This analysis empowers their pricing teams with the insights they need to price their products competitively on a day-to-day basis.
However, in a landscape where a staggering 50 million price changes occur daily, reliance on a reactive pricing intelligence solution, though effective in many ways, often falls short. To develop a strategic and predictive pricing engine, retailers also need the ability to track historical pricing relative to market conditions, competitor actions, seasonality, promptness of competitor pricing actions, and more. This would be particularly useful for senior retail pricing and business unit leaders as they look to gain a strategic perspective on their competitive pricing health. However, even today’s leading providers of retail pricing intelligence solutions lack in this area. This results in a relatively myopic view of competitive pricing even in large retail organizations.
Introducing DataWeave’s PricingPulse
DataWeave’s PricingPulse helps retail leaders better understand their competitive pricing strategies in comparison to relevant market dynamics over time. The capability bridges the gap between day-to-day competitive pricing operations and long-term strategic pricing analysis and actions, enabling senior retail pricing leaders to untangle the complexities of their pricing strategies. Delivered as a dashboard, the view offers an elevated vantage point for industry-wide pricing dynamics, empowering retailers with the foresight needed to navigate market shifts, predict vulnerabilities, and capitalize on new opportunities.
PricingPulse is provided to all DataWeave retail customers as an add-on to our Pricing Intelligence solution.
The insights offered by PricingPulse enable retailers to answer pivotal questions about competitor pricing behaviors, price leadership across categories, timing of price changes, and the effectiveness of capitalizing on price improvement opportunities. Some of the questions that PricingPulse offers answers to include:
How frequently are my competitors changing prices and for which products?
How does my price leadership vary across key product categories?
Which day of the week or month do my competitors change their pricing most and least frequently?
How well do I seize on price improvement opportunities over time?
Strategic Pricing Views Via PricingPulse
In the following section, we share a few views available to retail leaders via our PricingPulse dashboard. For a complete list of insights available on the dashboard, request a demo today.
Competitive Price Leadership Across Retailers and Categories
This view provides retailers with an overview of the price leaders across various product categories and how it changes with time. More often than not, retailers would aim to gain price leadership in certain categories, while maintaining healthy margins in others.
Retailers can also gauge their consistency and effectiveness in maintaining a competitive edge for key categories over time. They can fortify areas of strength and identify opportunity areas to optimize their pricing.
In addition, the dashboard tracks a retailer’s price index across categories, a measure that determines its price competitiveness.
The price index is determined by dividing the retailer’s price by the lowest price offered by any of its competitors. A ratio lesser than 1 indicates that the retailer is the lowest priced in the market. This measure is also presented for competitors, providing insights into competitors that are most attractively priced in the market. A timeline trend of this metric helps track how price leadership among retailers changes over time.
Price Change Trends
This view provides a summary of the level of price changes by a retailer and its competitors over a period of time, which includes the average magnitude of price changes as well as the proportion of the retailer’s assortment that underwent these price changes.
In addition, the number of price changes each month are provided for each retailer. This is further broken down into the total number of price changes during each day of the week.
These insights help retailers determine which competitors are most and least active in their pricing activities, how aggressive the pricing actions are, and if there are any specific price change patterns followed in terms of the days of the week or month.
Price Improvement Opportunities and Actions
The dashboard actively reports on price improvement opportunities, which could include either a price increase opportunity or a price decrease opportunity, for a retailer and its competitors across categories over time. A price increase opportunity occurs when a product is significantly under priced (by more than 2%) and a price decrease opportunity occurs when a product is significantly overpriced (by more than 2%).
Further, the retailer gains insight into how many price improvement opportunities were actually acted on within 15 days of the opportunity presenting itself. This “action rate” helps retailers quantify how well they seize on price improvement opportunities, which eventually result in higher sales and margins. The dashboard also reports on the average number of days it took for a retailer to act on a price improvement opportunity, thereby quantifying the responsiveness and agility of pricing teams.
This is especially useful for pricing leaders to “audit” or evaluate the performance of their pricing teams. When similar insights are viewed for a set of competitors as well, retailers can better understand the level of sophistication of their competitors’ pricing operations.
Ready to Elevate Your Pricing Game?
The launch of DataWeave’s PricingPulse marks a significant advancement in the realm of pricing solutions for retail leaders. As the retail landscape undergoes continuous transformation, the significance of precise pricing strategies cannot be overstated. PricingPulse is the first and only pricing view in the industry to bridge the gap between tactical pricing decisions and comprehensive strategic analysis.
In a world where agility and foresight are crucial, PricingPulse equips retail leaders with the ability to predict competitor actions, optimize pricing strategies, and stay ahead of the competition.
If you are a senior pricing leader or retail business unit head, reach out to us today to either sign up or learn more!
Inflation, like an invisible force, silently shapes the dynamics of economies, gradually eroding the purchasing power of consumers and leaving its imprint on various industries. High costs, hiring lags, and stagnating earnings pose severe challenges to businesses. One industry segment that intimately feels the impact of inflation is grocery, where price increases can be extremely concerning for the average consumer.
Over the last 12-plus months, the US has experienced a notable rise in inflation, stirring up concerns and influencing the way we shop for everyday essentials. Rising costs of raw materials, transportation, and labor have all played a role in driving up prices. Additionally, disruptions in global supply chains and fluctuations in currency exchange rates have further exacerbated the situation, creating a complex web of interdependencies.
To understand the magnitude of this phenomenon across leading e-retailers, we delved into an in-depth analysis of four major retail giants: Walmart, Amazon, Target, and Kroger.
Each of these retailers possesses a unique business model and competitive strategy, as well as faces unique challenges. This leads to distinct approaches to managing inflationary pressures. Walmart for instance, expects operating income growth to outpace sales growth in 2023. Given the persistence of high prices and the potential for further macro pressures, the retailer is taking a cautious outlook. In 2022, Amazon’s eCommerce business swung to a net loss of $2.7 billion, compared to a profit of $33.4 billion the previous year.
Amid these challenging circumstances, understanding the grocery pricing trends and strategies becomes imperative for retailers, both online and in stores to adapt and thrive in the current economic landscape. By examining their pricing trends, we can gain valuable insights into how these companies navigate the turbulent waters of the grocery industry against the backdrop of inflation.
Our Research Methodology
The data collected for our analysis encompassed a diverse range of products, from pantry staples like flour and rice to perishable goods like dairy and produce – a basket of around 600 SKUs matched across Amazon, Kroger, Target and Walmart, between January 2022 to February 2023.
Further, we separately focused on the prices of a smaller subset of 30+ high-volume daily staples that are likely to yield higher sales and margins for these retailers.
Average Selling Price of a Broad Set of Grocery Items
Our analysis reveals that Walmart consistently offers the lowest prices, with an average of 8% below its closest competitor, Target, despite an annual price increase of about 5%. Walmart seems to prioritize a “stability and predictability” strategy over margin optimization. The retailer’s 8% growth last quarter indicates that this strategy is bearing fruit. However, it’s important to note that this approach may have its drawbacks as Walmart’s margins come under pressure.
Average selling price trend across a basket of 500+ SKUs across Target, Walmart, Kroger, Amazon in the grocery category from Jan ’22 to Feb ’23.
In order to weather inflationary pressures, Walmart may adopt a cautious approach to growth while also focusing on securing margins. Reports suggest that the retailer has been pushing back against consumer packaged goods (CPG) manufacturers following a series of price hikes to counter inflationary cost pressures in early 2023. One of the reasons behind Walmart’s growth and increased sales can be attributed to ‘non-traditional’ higher-income households now seeking deals and discounts at Walmart as their spending power declines.
Interestingly, Amazon emerges as the highest-priced retailer, followed by Kroger, which increased its prices by 10% throughout the year. Consumer perception commonly associates Amazon with the lowest prices, but the data tells a different story. In fact, Amazon has been charging 12% to 18% higher prices than Walmart for groceries and is still maintaining its success.
While the company’s online sales declined by 4%, it saw a significant 9% increase in revenue from third-party seller services, such as warehousing, packaging, and delivery, in 2022. Amazon’s strong logistics and same-day delivery services give it a competitive advantage over other retailers, contributing to its revenue growth and margins. Interestingly, this presents an opportunity for Walmart and other retailers to increase prices while maintaining their strong competitive price positions.
Kroger, on the other hand, seems to be aiming for a premium price perception, consistently raising prices almost every month. Kroger’s pricing strategy appears to be closer to Amazon’s.
Average Selling Price for High-Volume Daily Staples
Pricing strategies often change for different categories of products. To better understand this, we focused our analysis further on a small subset of 30+ high-volume staples across retailers. These include baked goods, popular beverages, canned food, frozen meals, dairy, cereals, detergents, and other similar items.
Average selling price trend of 30+ high-volume daily staples across Target, Walmart, Kroger, Amazon in the grocery category from Jan ’22 to Feb ’23.
Walmart, possibly overestimating the impact of inflation, has continued to keep its prices the lowest, potentially aiming to increase margins through volume.
The level of price disparity across retailers is expectedly lower here, with Amazon and Kroger closely tracking Walmart’s average prices.
Target’s pricing strategy stands out as it consistently emerges as the highest-priced retailer for daily staples, despite being one of the lower-priced retailers for a broader basket of grocery items. This suggests that Target’s underlying technology may not be as optimized to address market dynamics compared to other leading retailers. In our opinion, Target may want to strengthen its efforts to track pricing more intensely for this sub-category.
A Data-fuelled Approach is the Need of the Hour
In the challenging economic landscape, retailers and grocery stores are under pressure to maintain their revenues and margins. Adopting a comprehensive and dynamic pricing strategy is crucial. Understanding which product categories are experiencing price increases among competitors can help retailers make informed decisions on pricing at both the category and product level.
Retailers should consider their balancing margin performance with consumers’ willingness to pay, rather than implementing broad price increases that may harm customer trust. Price increases can be challenging for both customers and merchants. Retailers who employ a data-driven and insight-based approach are more likely to succeed.
Keep an eye on the DataWeave blog for analysis on pricing, discounting, stock availability, discoverability, and more, across retailers and brands from other industry segments as well.
