Best Buy’s customer-centric transformation is helping to produce some impressive results. For its fiscal first quarter ended May 27, the company reported net earnings of $234 million, representing a 38 percent earnings gain. No wonder so many analysts are upgrading Best Buy to "buy".
But while much has been written about the big picture initiatives—in particular, the reconfiguration of stores to local neighborhood demographics, leading to an 8.4% increase in same-store sales (compared to 2.3% for traditional stores)—scant attention has been paid to the critical role of customer analytics in enabling the transformation.
In this article, published yesterday in Brandweek, I attempt to rectify that shortcoming, by focusing on the analytics component. Unfortunately, my original 2000 words were savagely cut down to 700 words due to space constraints (e.g., a stupid cartoon in the print edition), so I’m not sure my efforts were terribly successful.
In any case, what amazes me about Best Buy is how well the company captures data from every transaction and interaction—from phone calls and mouse clicks to delivery and rebate check addresses—and then deploys sophisticated match-and-merge algorithms to identify over three-quarters of its customers, or more than a 100 million individuals. Also amazing are its behavioral modeling techniques for scoring customers in terms of their interests, lifestyles and passions.
Is the customer in the home theater space? Is he in the music, gaming or digital imaging space? Is he productivity- and business-minded? Having discerned this information, Best Buy can anticipate—and actively drive—his next likely purchases. Of course, some purchase sequences are obvious—the fact, for example, that a “Buzz customer” buys MP3 accessories and MP3s thirty days after he buys an MP3 player. But what about the fact that a “Buzz customer” is also five times more likely to buy a digital camera thirty days after he buys an MP3 player?
Best Buy looks at thousands of nonobvious transactional correlations (thanks, in part, to our Peacock technology) to drive highly relevant messages and offers. The goal is to combine the creative messaging and tonality best suited to each customer with very specific offers, based on their behavior, and to then package and deliver it in a format that is consistent with the brand.
An important aspect of modeling is determining customer value. To that end, Best Buy has developed a customer lifetime value model that may be the most sophisticated of its kind. In addition to measuring transaction-level profitability, it factors in a host of customer behaviors that would tend to either increase or decrease the value of the relationship. Are customers heavy rebate redeemers? Are they heavy users of the sales channel? Are they heavy returners? Looking through these various lenses, Best Buy gains not only a clearer view of customer value, but also insight into how to change customer behavior.
Besides customer value, Best Buy looks at factors like “promotional sensitivity” (Which customers are price conscious and promotion-driven?), “channel preferences” (Which customers prefer to interact online versus in-store?), and “ability to buy” (Which customers have disposable income?). One factor of emerging importance is “technology adoption” (Which customers are likely to buy new technology ahead of the mainstream?). No surprise, given the nature of the business.
Best Buy is shifting an increasing amount of resources away from mass marketing and toward precision marketing. It’s also moving away from broad-based price and promotion tactics—e.g., sending every customer a coupon for 10% off—and toward customer-triggered incentive programs. Best Buy believes that, given enough trigger responses and customization, consumers will find their own individual paths through the company’s communication streams. So far, the strategy seems to be working.
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