More marketers go “Moneyball” to seek a retail edge

When general manager Billy Beane used data to turn his low budget baseball team into a winner, writer Michael Lewis described his strategy in the bestselling book Moneyball. Today, industries of all sorts, including fashion, are employing Moneyball techniques to seek a competitive advantage.

Clothing maker Guess, for instance, has a business intelligence unit that parses data from the company’s online and physical stores in order to share strategies with Guess’s sales force and store managers.

Bruce Yen, director of business intelligence at Guess, explained to an audience at Gigaom’s Structure Data event in New York Thursday that his goal is to use data to improve “omni-channel retailing” and eventually create real-time recommendation system for clothes. There are limits, however.

In response to a suggestion that “quants had taken over marketing,” Yen cautioned that pure data analysts can’t be the only ones making decisions.

According to Yen and fellow speaker Colin Mahony, who is a VP at database maker HP Vertica, leaders don’t have to possess advanced data skills themselves. They pointed out to moderator Nick Beim, a partner at Venrock, that the baseball manager Beane wasn’t a quant, but he recognized the importance of using data as a way to win.

For now, a growing number of companies are already using A/B testing and other analytic techniques but, in the future, the way they distribute the information will change. Mahony and Yen predicted that companies’ intelligence brain trusts, which are now centralized silos, will increasingly send their people in and out of other business units.

Mahony also observed that the scale of data that companies parse is going to grow exponentially in the next decades, and that units like zetabytes and brontobytes will become common place.

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