7 minute read
Key Takeaways
- The lowest price isn’t always the right price. The article explicitly argues that competing primarily on lower prices can trigger promotional wars and erode profit margins.
- Not every product deserves the same pricing attention. The article shows how identifying Key Value Items (KVIs) and Key Value Categories (KVCs) helps retailers focus pricing strategies on products and categories that disproportionately influence customer behavior.
- Dynamic markets demand dynamic pricing. The article’s central argument is that retailers need to adjust pricing quickly as market demand and competitive conditions change.
- AI and machine learning help retailers manage pricing at speed and scale. The article explains that these technologies can analyze large amounts of data, detect patterns and price changes, and produce pricing recommendations faster than traditional approaches.
It’s no secret that Amazon is dominating the e-commerce market. Within a span of a few years, they managed to out-sell and out-perform former giants like Toys “R” Us, Barnes & Noble, and even Macy’s—many of which were previously considered untouchable before Amazon came through and turned their respectable markets upside-down.
Arguably, several factors can be attributed to Amazon’s success in e-commerce; attributes such as excellent customer service, the appeal of a one-stop shopping experience, product diversification and simply being at the right place at the right time are often mentioned by those seeking to emulate Amazon’s success online. However, an important aspect of Amazon’s ability to dominate the e-commerce market remains underappreciated and is often completely overlooked. Amazon has created a pricing strategy designed to excel in the modern, rapidly-changing online retail market before other companies thought to do so, and it is in every online retailer’s best interest to have a good understanding of their methods.
Dynamic Pricing for a Dynamic Market
Dynamic pricing refers to products, typically items sold online, with prices that change rapidly and sometimes drastically based on their respective markets. Rather than being overwhelmed by this fast-paced pricing dilemma, e-commerce stores like Amazon have used dynamic pricing to their advantage by adjusting their prices at the same rapid pace of market demand. By doing so, they remain one step ahead of their competition and nearly always have the most compelling offers faster than other retailers.
One important fact to note is that the “right” price is not always the lowest price. Many e-commerce companies have failed to observe this fact, and as a result end up in brutal promotional wars with competitors, losing precious profit margins in the process. Amazon, however, knows this fact all too well, and also considers this in their approach by utilizing KVI pricing and other strategies in their dynamic pricing methods.
How to Identify Key Value Items (KVIs) and Key Value Categories (KVCs)
Identifying and managing KVCs and KVIs can make the difference between a customer buying no products at all versus a customer filling their cart with a multitude of items when shopping online. Key value categories, or KVCs, are notable categories of products within a store. Similarly, key value items (KVIs) are individual products that are considerably more important than other, less popular items in a store. Items in a retail store can be “key” for a multitude of reasons:
- Perceived value drivers: items that remain popular with customers for a long period of time
- Assortment perception drivers: product(s) that can persuade customers to buy other related items within a store
- Traffic drivers: high-demand products, particularly important for product categories that have high-volume, short-term demand, such as clothing items and accessories
- Basket drivers: products that are often bought in conjunction with other items, such as potting soil and flower seeds
Offline retailers already have a decent notion of KVIs and utilize them by offering promotional deals and optimizing their placement on store shelves by keeping them at eye-level. Online retailers like Amazon also consider KVIs in their pricing strategy via promotional deals combined with tools such as their recommended products engine to catch a customer’s eye whilst shopping. How many times do you think customers have bought additional items because “customers who have bought this product also like” another? This is a great example of how KVI pricing can change the purchasing habits of customers drastically.
Price Management in Modern Markets
Identifying KVIs and KVCs is a great step forward in remaining competitive online as a retailer. However, considering such data is only one small piece of the pricing puzzle if retailers want to learn from Amazon’s success. Recognizing factors such as dynamic pricing and KVI pricing is of little use unless proper action is taken to implement effective strategies. Price management has undergone a renaissance of sorts within the online retail industry due to dynamic pricing and technological advances. Companies that do not acknowledge the changes of the industry and adapt their price management strategies accordingly will find themselves far behind companies like Amazon in e-commerce, or worse, failing altogether like Toys “R” Us.
Dynamic pricing requires dynamic price management. Retailers are dealing with an exceptional price management crisis; there is more data than ever to process, and far less time to process it. Amazon is known for changing prices on products several times a day according to market demands. At such a rapid pace, pricing teams cannot create an array of excel sheets to record data, analyze pricing data and come to a timely decision as they did years prior.
Amazon paved the way for e-commerce companies in terms of price management by implementing new technologies into the price optimization process, such as machine learning, years before others thought to do so. By equipping their pricing teams with technologies like AI, Amazon manages to stay ahead of their competitors who struggle to adapt to dynamic pricing. Advanced algorithms are able to analyze data, detect patterns and price changes and produce effective price recommendations at a fraction of the speed of traditional price optimization strategies.
Price Management and Price Optimization Technologies
Amazon may have been ahead of its time in terms of implementing modern technologies into its pricing strategy. One important factor that allowed them to innovate so quickly and effectively was the fact that they have their own pricing teams and methods to try out the latest technology has to offer. Fortunately for smaller retailers, however, price management and price optimization technologies are not exclusively available to companies as large as Amazon anymore. Large strides have been made in the past few years regarding price management software and price optimization using machine learning.
Whether other large retailers wish to catch up with companies like Amazon, or mid-range retailers hope to optimize their pricing strategies despite having fewer resources to do so, the technology required for effective, dynamic pricing is more available and more affordable than ever. Change can be difficult, but for companies seeking to experience the full “Amazon effect” and thrive in the online retail sector, price management and price optimization technologies are irreplaceable assets.
Learn more about pricing and price management:
- Learn how to gain support for pricing recommendations
- Read about Instacart’s AI pricing controversy
- Are AI pricing algorithms a risk?
Frequently Asked Questions About Amazon’s Pricing Strategy
What is Amazon’s pricing strategy?
Amazon’s pricing strategy uses dynamic pricing to adjust product prices as market conditions, demand and competitive factors change. The company also considers the importance of specific products and categories when making pricing decisions, rather than simply trying to offer the lowest price on every item.
What is dynamic pricing in e-commerce?
Dynamic pricing in e-commerce is a pricing strategy in which product prices change in response to market conditions. Online retailers can use dynamic pricing to respond more quickly to changes in demand and competition instead of relying on fixed prices or slower manual pricing processes.
What are Key Value Items (KVIs) in retail pricing?
Key Value Items (KVIs) are products that have greater importance to customers or a retailer’s overall performance than other items. A product may be considered a KVI because it drives traffic, influences customers’ perception of value or assortment, or encourages purchases of additional products.
What are Key Value Categories (KVCs)?
Key Value Categories (KVCs) are product categories that have particular importance to customers and the retailer. Identifying KVCs can help retailers determine where pricing decisions may have a greater influence on customer perceptions and purchasing behavior.
Does dynamic pricing always mean lowering prices?
No. Dynamic pricing does not always mean offering the lowest price. Competing primarily through price reductions can lead to promotional wars and shrinking profit margins. A dynamic pricing strategy instead considers market conditions and determines when and how prices should change.
How does Amazon use AI and machine learning for pricing?
Amazon uses technologies such as AI and machine learning to support price management and optimization. These technologies can analyze large amounts of pricing data, detect patterns and price changes, and generate pricing recommendations faster than traditional manual processes.
Why is price optimization technology important for e-commerce retailers?
Price optimization technology helps e-commerce retailers analyze large amounts of pricing and market data quickly enough to respond to dynamic markets. As prices and market conditions change more frequently, technology can help pricing teams make decisions without relying solely on manual analysis and spreadsheets.
Nikolay Savin
Nikolay Savin, Head of Product Competera, built the price optimization software for e-commerce and brick & mortar to achieve better results through the merge of data, machine learning, and retail best practices.
