Internet Retailer — Retailers boost sales with increasingly sophisticated recommendations that are tailored to individual shoppers

As soon as a shopper lands at BuildABear.com, the site’s recommendation engine technology has a sense of who the shopper is. It knows how she landed on the site, what device she’s viewing the site on, where she’s located, whether she’s visited the site before and, if she has, what she has looked at and bought. With each click through the site, the engine presents her with suggestions based on its insights into the shopper and what similar consumers typically buy, says Bryan Sawyer, the retailer’s e-commerce director.

While the retailer had used a product recommendation engine for years, it was only in June, when it began working with RichRelevance Inc.‘s recommendation technology to dig deeper into individual shopper’s characteristics that the retailer began seeing significant results from its suggestions, Sawyer says. Since then Build-A-Bear Workshop Inc. has posted strong “double-digit” sales growth online thanks largely to BuildABear.com doing a better job upselling and cross-selling merchandise, he says. And since June the retailer’s web site has outperformed its stores in terms of the ratio of shoes sold per stuffed animal sold, a key metric the retailer regularly tracks.

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