ANALYTICS
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SECTION TWO
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What is a Customer-Centric
Retail Pricing Zone?
As an analytics professional, my perspective on shopping
is different from other consumers. For instance, I think
I'm paying too little for the breakfast cereal that I buy from my primary grocer. The store is losing margin because it's concentrating too much on market competition in its immediate area instead of paying attention to how best customers like me go about their shopping.
Every large-scale retailer has a framework that dictates how it sets pricing in different stores, and a big retailer might have hundreds of “pricing zones.” Those zones are likely driven by competitive price shopping, making the framework very market-centric versus consumer-centric. Geography often drives how most retail pricing zones are defined.
With customer-specific data, it’s possible to escape that market-centric pricing system. The new opportunity is to create pricing zones based on data analysis of customer purchase patterns in order to maximize profitability — even in the face of stiff price competition.
To better understand the nature of customer-centric pricing zones, picture a customer who prefers a premium brand of ground coffee both at home and at the office. She may buy that coffee at your store near her home, at your store near the office or at a larger store frequented during bigger shopping trips. Her shopping zone doesn’t radiate in concentric circles from her home. Instead, it weaves across multiple traditional zones, where prices may vary. Therefore, she might find two different prices for that same pound of coffee.
Those visible price differences represent a series of missed opportunities that can be addressed by aligning pricing based upon the shopping behavior of your customers — particularly your best customers. Identifying the stores that don't belong in the same customer-centric zones with one another and assigning them to more appropriate pricing zones offers a number of advantages:
- The ability to optimize pricing. In some cases, you may be pricing items and entire categories too low, losing margin. In others, you may be pricing them too high, losing customers. For example, I live in the suburbs, but I shop in the city. The store in which I shop in the city prices its items to compete with nearby stores. This makes the breakfast cereal I purchase cheaper at the city store as opposed to the same item at stores near my home. If my grocer’s marketing team were to assign my store in the city to a compatible zone with higher prices, they could improve margin and sales volume. And, in fact, optimizing price zones in this way allows retailers to alleviate pressures to compete only on the low prices offered by competitors.
- Avoiding customer confusion and disconnects. Customers crossing geographic price zones might notice the price difference with the same product. Encountering the higher of the two prices they’re aware of, those customers may leave that store and you lose not only a single-item sale, but also an entire trip. Those customers might also divert their shopping to the cheaper location, returning less margin and perhaps less frequency. They may even be lured to the big-box retailer across the street seeking better deals.
- Optimized ad zones. The same philosophy applies to promotions, sales and advertising. Customer-centric pricing zones allow you to maintain consistency of the message and offer. Promotional fliers, for example, are basically weekly price changes. Mapping customer pricing zones allows you to calibrate your ad zones to optimize pricing and reduce potential disconnects.
- More efficient testing of price elasticity. To understand the elasticity of prices, you must test actual price changes. Interpreting results of such elasticity tests can take time, particularly when testing high-ticket, seasonal or low-frequency-purchase items.
Grouping stores that top shoppers are most likely to visit allows you to accelerate earnings. When changing the price of occasional or seasonal purchases, you present multiple opportunities for customers to see the price change. It also can result in cleaner tests. If you test prices across a customer-centric zone rather than a geographic zone, the chances of customers crossing from the control stores into the test stores—and vice versa—is greatly reduced.
What are the first steps in building customer pricing zones? To optimize pricing zones around customer-shopping patterns, first isolate both your top shoppers based on sales and your top customers based on profitability. Once that is done, each shopper can be assigned a “home store” based on frequency and recency of visits. If there’s a tie, recency will dictate the home store. Then, for each home store, you can run analytics to identify which of the other stores in the current pricing zone those best customers shop most consistently and most inconsistently. Such a view enables you to target inefficient geographic pricing zones for one of two levels of action:
- Realign the outliers. When you find a small number of stores with cross-shop patterns that are out of line with most of the other stores in their pricing zone, move those stores to another zone. This allows you to align pricing with a more compatible customer-centric zone.
- Rebuild zones entirely. If a zone features a number of outliers, consider employing clustering techniques to build a new set of zones from the ground up. A zone might be split into two zones, or more, depending on how much variance you see.
Despite the many advantages of customer-centric pricing zones, many companies seem almost allergic to this type of non-traditional analysis, in many cases because they believe that it’s complex and difficult. With today’s technology, it’s easy, and will get easier.
By overlooking specific customer shopping patterns across your retail network, you’re leaving millions of dollars on the table — right next to my underpriced box of breakfast cereal.
Adrian Sosa is Vice President of Analytics for LoyaltyOne, a global leader in delivering loyalty and marketing programs and implementing customer experience management. He can be reached at asosa@loyalty.com.
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