Multi-channel retailer Eddie Bauer increased sales when it segmented its customer base by how they shop, not what they buy, Michael Boyd, director of customer relationship management for Eddie Bauer, tells Internet Retailer. “Our merchandise assortment is so much more narrow that we might only be promoting three men`s sweaters at one time. We don’t need a complex algorithm to recommend one of the three sweaters,” Boyd says.
To come up with segments based on shopping style, Eddie Bauer conducted an exploratory data mining and analysis exercise, looking at behavioral data that defined shopping preferences. It considered such factors as what percentage of a shopper’s total purchases were made on mark-down, what colors a given customer buys, and what time of day a customer is most likely to do a transaction. All provided clues linked to larger predictive patterns. Eddie Bauer also mined its database of attitudinal research looking for more ways to classify customers in terms of how they approached shopping.
Two segments emerged from the data. One, dubbed Too Busy to Shop, doesn’t particularly enjoy shopping for apparel, is willing to pay more for a speedy shopping experience, and likes to buy outfit solutions rather than apparel pieces. The Professional Shopper, on the other hand, loves to shop, is more price-aware and prides herself on the ability to assemble a look from a variety of different sources.
The company tested three versions of an e-mail, including a version targeting too busy to shop, one targeting the professional shopper and a control group. Tests on and off target resulted in sales 7% to 8% higher when customers got communications targeted for their type. When they received communications targeting the group they didn’t belong to, the message actually depressed sales, making them even less likely to buy than the control group.
“We’ve changed our focus to using all of the data we have to draw only one conclusion: which type of shopper is this?” Boyd says.