(Direct Newsline) Food staples such as bread and milk are often placed at opposite ends of a supermarket. This requires customers to walk across the store—past a wide range of temptations—to fill their baskets with necessities.
People buying electronics, however, are less likely to traipse the floor of a retail outlet looking for what they want. For Best Buy, the trick was finding which products would trigger additional purchases, and then laying out its stores so those items are right in the middle.
The answer? The chain is using analytics to influence product placement and promotions, and follow-up communications to customers.
When Best Buy created a visual representation of product affinity, it found that people who purchased computer hardware and a joystick usually bought video games as well. The firm stores nine years of transactional information on its database, and is able to analyze consecutive as well as concurrent purchases.
Best Buy relies on Peacock, a transaction analysis program from Fair Isaac, to uncover and visually map correlated products. The firm has broken its customer base into cohorts, and made determinations (based on a variety of demographic information) as to a given customer’s next likely purchase.
In addition to influencing retail layout, Peacock has enabled the company to design package bundles, according to Jane Johnson, Fair Isaac’s vice president of retail markets.
For instance, when a male consumer fitting Best Buy’s “Barry” profile buys a home theater, he is probably going to toss a full installation program—all the bells and whistles—into his shipping basket. Best Buy approaches him by touting its upscale, or European, appliance offerings.
“Buzz”, however, is more of a one-off technology buyer. He may have a Best Buy credit card, but he is more worried about getting his plasma TV home than buying a full installation package. To woo him, the company must emphasize the “coolness” factor.”
What’s next? Best Buy’ hopes plans to use Peacock for “trigger event” campaigns; making its research findings available for comment by general managers, and analyzing how online shoppers differ from brick-and-mortar shoppers.
This article is based on a presentation at the National Center for Database Marketing Conference in Orlando.
