How Retailers Should and Shouldn’t React to Competitors’ Price Changes

By Nikolay Savin

Shoppers cite the price of a product to be the primary reason to choose purchasing it from a particular retailer. In fact, as many as 60 percent of consumers opt for a seller with the optimal price. In most cases, consumers compare prices offered by retailers for so-called key value items(KVIs). They value such products the most and expect the lowest prices for them. That’s why price changes for KVIs at one retailer affect the sales of the same products at their competitors. It goes like clockwork: if your rival slashes prices, your sales go down, and vice versa.

There are two tasks you need to accomplish to succeed in this scenario. The first is to identify your KVIs which customers are after. Then you have to understand if you compete for the lowest prices for these items or can offer them at a higher price as shoppers will come to you anyway. The second option works for those retailers that have become trusted product experts in a particular area. For example, pet supplies. Pet goods stores usually have higher prices for items which are sold cheaper at supermarkets. It's possible since customers also look for advice and/or proven product knowledge at such pet stores that they choose them over supermarkets, which sell everything.

Going back to step No. 1: How one can identify KVIs? There are three ways to do that. The first one is to rely on the intuition of your pricing managers. They usually know from experience which products are sold more often than others and the sales of which are affected by competitors’ price changes. The second way is to study sales checks. As a rule, there are products which are common to find in checks and which usually are accompanied by items from other categories, enabling you to see a certain pattern. However, in both cases you wouldn’t know whether customers buy these items from you because you offer the lowest price or because they trust you. To figure that out, your pricing managers would require the power of data to establish the relationship between your prices, the prices of your competitors, and your sales.

Price calculations call for a constant flow of pricing data. “And significant computational power (like the power of machine learning algorithms) to analyze it,” comments Vladimir Kuchkanov, pricing solutions architect at retail price optimization company Competera. “The combination of massive data, powerful analytics and actionable insights lets retail businesses hit three birds with one stone: identify KVIs; define real competitors — not every retailer selling the same KVIs which you offer is your competitor; and set optimal prices as compared to rivals while maximizing revenue. Enhancing your teams with machine learning is the only way to do all that with the necessary speed and precision, which accounts for stunning results. From my experience, the adoption of algorithm-powered price management software can ensure up to 16 percent revenue growth.”

To recap, retailers need to take three steps to react to competitors’ price changes in the most beneficial way. These include timely pricing data collection, data analysis, and insight-driven decision making. Doing everything manually would be an option for small retailers with a small assortment under management. However, it's an unyielding task for companies managing thousands of SKUs, with some 1,500 of them being KVIs. Calculating prices for such an impressive number of products calls for enormous computational power. That’s where machine learning jumps in to help you entice customers and maximize revenue at the same time.

Nikolay Savin is the head of product at Competera, a price optimization software for retailers.