Saturday, April 6, 2013

Chapter Summary: Joseph Turow's "The Customized Store"

In the "The Customized Store" chapter of his book Niche Envy, Joseph Turow describes different ways in which businesses use databases of information about their customers to improve their bottom lines. Turow argues: "With new information technologies, new analytical techniques, and a changing commercial environment, stores are thinking about and treating customers in new ways. Like the new media regime, this new regime is built on data mining, segmentation, targeted tracking, interactivity, mass customization, and the cultivation of relationships" (p. 126). In some ways, he says, these attempts to compile information about customers is a high-tech replication of the small-town retail tradition of a shopkeepers knowing--and catering to--the tastes and needs of their customers.

Turow begins by setting up Wal-Mart as a major driver of database-driven retail strategies, even as Wal-Mart itself does little in compiling information about its customers (outside of its Sam's Club wholesale stores). Instead, Wal-Mart's analysis is at the cart level, seeing what people buy together, as well as with aggressively working with the store's suppliers to ensure that their products meet customer demand. The company amasses huge amounts of data of what people are purchasing via the stores' checkout scanners and uses the data to make decisions on what to carry in certain communities and how much of it to stock, as well as what to charge.

Since Wal-Mart has successfully set itself up as the lowest priced option for shoppers, competitors have had to look for more market-segmented options to attract and retain customers. Turow argues: "An important competitive advantage in the Wal-Mart age, then, is to know and reward profitable customers better than Wal-Mart or any other competitors can" (p. 132). And one way to do so is by analyzing purchasing data for patterns that can be exploited. Turow identifies two strategies adopted by businesses in this regard that are "changing the American shopping experience": First, to "develop profiles of 'best' or at least 'good' customers so as to focus on wooing them," and, second, to "encourage purchases through a better understanding of customers' buying habits" (p. 132).

Turow then gives several examples of firms and industries adopting these new customer data-driven strategies. He describes how banks group their customers into several different groups based on wealth and demographics (e.g. urban, retired, etc.) and then target programs not only to attract customers to certain products, but to push some customers away from certain services. For example, since using a teller costs the banks money, one bank he examined put in place disincentives for low-income customers to seek customer service in a branch (mainly by limiting the number of no-fee withdrawals each month). Similarly, Turow describes how 73 percent of Bloomingdale's sales come from 20 percent of the store's customers--about 15,000 of them--and how those elite customers shop on average more than 30 times a year. As such, the retailer uses a customer relationship manager database system called Klondike (since it helps mine for gold) to "create a customized relationship between the customers and sales associates over the phone and inside the store" (p. 139). Like with the banks, whenever a Bloomingdale's employee interacts with a customer, the customer's category is available in the computer system so the experience can be customized.

Next, Turow discusses the supermarket Shop-Rite's program of using loyalty cards to collect the purchasing habits of the company's customers and then divide the customers into niches based on the results. The store is thus able to tailor offers directly to the niches. The system employed by CVS is even more in-depth, he says.

Turow then suggests that the radio-frequency identification (RFID) tags used by companies like Wal-Mart to track shipments and inventory could be put to use to track the behavior of customers to amass even more data on their habits. He says that this suggestion is more than just theory: Wal-Mart has already teamed with Procter and Gamble to put RFID tags in Max Factor lipstick containers. Turow says it is not just RFID tags, but "retailers are looking for multiple ways to get good customers into their databases and to think of their store in ways that, analytics suggest, reflect each customer's lifestyle" (p. 144). Often, the goal is to get customers to participate voluntarily, either through a rewards card or a company branded credit card. Based on the data, the company can not only identify "good" customers to whom they can send special offers, but also "bad" customers who they can seek to block through changed store policies. For example, he notes how Best Buy discovered that about 100 million of its 500 million customers cost the chain money, because they only buy loss leader and other discounted items, even finding legal ways to get discounts on discounts. In response, Best Buy changed certain policies to make it more difficult for the "bad" customers to access these discounts. Similarly, Dorothy Lane Markets discontinued its weekly discount flyer that attracted "bad" customers in favor of rewards for "good" customers in the hopes they would increase their spending.

Finally, Turow says the practice of "clienteling"--lavishing extra attention on the best customers--has become standard in department stores, but supermarkets and electronics retailers have a challenge in not knowing when these customers will be coming to their stores. So the challenge is to get customers to identify themselves upon entering. He explains how Albertson's and Stop & Shop try to do that by having customers swipe their frequent-shopper cards through portable terminals that allow them to buy things by scanning them, as well as getting information and marketing offers.

Turow's chapter doesn't really make an strong argument in the academic sense. Instead, he provides a series of mini case studies on how retailers are using customer data accumulation techniques to better target and serve their customers (and, on occasion, to identify and dissuade customers who are not contributing to the company's bottom line). The stories of the individual companies are useful in understanding how 21st century technology is changing how stores market their wares to their customers in a more focused way.

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