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The day is coming when retailers will have to optimize prices at the individual customer level, on the fly and in full view of everyone.
Every corner of retail faces the same imperative. It isn’t just the food retail industry where the new rules about pricing will apply. The concept of the long-term economic value of individual customers will matter in every area of retail—from hairpins sold at Claire’s to sofas sold at Pottery Barn—and so will the rigors of pricing analytics.
Some types of retailers may not need to—or may not be able to—apply individualized pricing as broadly as other types of retailers. But in the long run, individualized pricing, at the moment when customers are buying, will become measurably more important in every type of retail business.
To do it effectively, retailers will need to know more about customers’ spending patterns and their potential profitability. And they’ll have to gather information on other retailers their customers are buying from.
Retailers used to set prices for the products in their stores by first understanding the value a product offered a customer. The store would also take into account the product’s price at nearby competitors. An analytically advanced store might seek to understand the product’s true costs, so that winning the customer’s business wouldn’t mean sacrificing profits. A store might even adjust a price to serve some bundling strategy, in the manner of a loss leader.
For decades, some subset of these steps has informed the best retailers’ pricing strategies, including Wal-Mart’s “everyday low price.” By thinking through these points, a retailer could theoretically feel confident about all the prices on its shelves. The prices satisfied an equation. They also had the advantage of being simple: every customer got the same deal.
Nowadays, it isn’t just nearby physical stores that retailers have to match prices against. It’s also a spectrum of digital rivals operating on the Web and through mobile commerce. The idea of a perfect price within a category—one that makes sense on the shelf, no matter which customer is looking at it and where the store may be located—is fading.
In its place is an understanding that to price effectively, retailers will have to move to a dynamic approach based on each product’s economic value and each customer’s buying needs. And they must deploy their analytics at that granular level.
Why is pricing analytics relatively undeveloped in retail? Four reasons:
Low quality of data and reliability of predictions needed from all over the business—including the supply chain, marketing and sales.
Extensive external data that influences prices—namely the economy, competitor actions, actions in competitors’ ecosystems, manufacturers’ discounts and trade promotions.
Different channels for which pricing needs to make sense—brick and mortar stores, e-commerce and, increasingly, mobile commerce. These environments are in a constant state of flux, making it hard to trust the results of any price tests.
Retailers’ reluctance to increase profits—their share prices may be more tied into same-store sales comparisons. For retailers in this position, pricing analytics still matter, but they should be used to drive top-line growth instead of profits.
To accomplish the more advanced work needed for personalized, dynamic pricing, retailers will need a decidedly different mindset. In this piece, we offer our perspective on how retail pricing will evolve, identify the changes retailers must make to thrive in this shifting landscape and explore the role that analytics will play.
How can retailers prepare themselves to thrive in a future dominated by personalized, dynamic pricing? We offer the following suggestions.
December 28, 2011
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