July 18, 2011, 2:16 PM

Altrec makes e-commerce personalization even more personal

The outdoor gear retailer bases recommendations on a consumer’s current site visit.

Zak Stambor

Managing Editor

Lead Photo

Web-only retailer Altrec.com Inc. considers the relevance of the content it displays to each shopper a way to differentiate itself from other retailers of outdoor apparel and accessories, says John Hnanicek, chief information officer and vice president, merchandising.

That’s why the retailer bases the product recommendations it displays on Altrec.com on what a shopper does during his current visit to the e-retail site—and not on past behavior or purchases.  Working with personalization technology vendor Baynote Inc., Altrec uses cookies to gather 24 metrics, such as the amount of time a shopper spends on a page and whether he scrolls down the page, to pick up strong or weak signals of interest. “If he hits a back button a second after arriving at a product page, obviously that’s a weak signal,” says Carlos Carvajal, Baynote vice president of marketing. “But if he spends a lot of time on a set of similar products we can determine that he’s very interested in a particular product.”

Layering that individual consumer’s behaviors on top of how thousands of previous shoppers acted enables Altrec to recommend to him the products bought by consumers who acted in similar fashion. The approach works, Hnanicek says. A/B tests show that the conversion rate is 4.5 times higher than the manually entered recommendations the retailer previously offered. And the average order value stands about 15% higher.

Key to that success is correctly pinpointing the current shopper’s interests and which group of previous consumers, or persona, he matches up with, says Hnanicek. He says making that determination based on current behavior avoids disconnects that can occur when e-retailers base recommendations on past purchases. For instance, a few months ago Hnanicek bought a children’s DVD for his niece. The purchase was extremely atypical. Yet nearly every time he arrived at that retail site for the next two months the site suggested he might be interested in other children’s DVDs.

“Our suggestions are based on a consumer’s intent or interest rather than looking in a rear-view mirror,” he says. “Relying on the wisdom of the invisible crowd works.” An added benefit to the approach is that it avoids any complications that could occur if the site based its recommendations on a cookie that tracked a consumer’s past behaviors. In that scenario, if a consumer deleted the retailer’s cookie, the site’s ability to offer relevant recommendations would be lost, he says. A recent study by web measurement firm comScore Inc. estimates 28.5% of online consumers delete their cookies each month.

Altrec is No. 408 in the Internet Retailer Top 500 Guide.

Comments | 1 Response

  • There are times when "crowd wisdom" works for personalization, for example when a visitor arrives from a Google referrer, they want to see what other people who also arrived the same way bought. But you can't rely purely on "invisible crowd wisdom" for personalization technology - it's in the name: personalized, as in personal to the individual. Altrec won't be seeing anywhere near the revenue increase that some of our customers are seeing. Using a mixture of 32 interchangable algorithms, plus advanced unlimited visitor/product attribute filters, our transparent framework allows retailers to build a personalization strategy around their business. I note the point that 28.5% of online consumers delete cookies each month - with well thought-out processes including retrospective merging, "new" visitor profiles can be joined to existing profiles. There is absolutely no downside to using cookies at all.

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