tailoring which products the site shows to these so-called “cold start” users—those for whom Stylefeeder has no preference information.
“We track what we do know about them, and the first, most dense, and richest thing is where they are in the world,” says Nauda. “I geolocate their IP address, which usually gets me down to the Zip code—not just which city, but which part of the city. Look at Woburn, Massachusetts, for example. Our user base there seems to be younger girls, like teens, who are shopping from home and go for more youthful brands like BCBGirls. Whereas our users in downtown Boston are older and more professional and would like maybe a Kate Spade shoe that’s much more expensive and suitable for an office. We track those metrics—what they click on and whether they return—and we use that to tailor results for other people who are hitting us from a cold start.”
It’s a powerful technique. Says Jacob: “In densely populated areas where we have a bunch of preference information, like New York and L.A. and San Francisco and Chicago, we’re able to double the click-through rates” for cold-start visitors. (Meaning that twice as many people click on Stylefeeder’s product images and are taken to e-retail sites where they can purchase them. Stylefeeder’s business model is to earn commission revenue on any purchases that result, as I detailed in a pair of posts back in April.)
As an accidental result of collecting all this regional preference information, Stylefeeder is gaining an increasingly deep, fine-grained, and immediate viewof shopping trends. In the past, the company hasn’t exposed much of this information to public view—in fact, the charts Jacob and Nauda shared with Xconomy are among the first bits of Stylefeeder intel to see the light of day. But Jacob says the startup is starting to think about how to make the information more available to e-commerce players who might find it valuable.
“We’ve known all along that retailers would be really interested in getting ahead of some of these trends,” says Jacob. “There are some people pushing us to package it up and sell it as a tool for people to play with, Alexa-style,” referring to Amazon’s Web traffic analysis subsidiary. “Just because of how we’ve been focusing on monetization, we haven’t done much yet. But the guts of the system exist already.”
So stand by to see whether Stylefeeder branches out into database marketing services. But meanwhile, what does all the city-specific shopping data really mean? Do Stylefeeder’s numbers reveal anything about the deeper sociological or economic trends affecting shoppers?
Nauda thinks they may. He emphasizes that his opinions are speculative, not scientific. “But just starting with Seattle, I think our data is indicative of something to do with the fall of the solid ‘Americana’ brands,” Nauda says. “Timberland, Converse, Levi’s–these are your standard American brands, whereas the stuff that’s rising is more designer-oriented–DKNY and Kate Spade. It’s telling, because the outdoorsy brands like Timberland are what you would normally associate with Seattle, but it’s the other brands that are on the rise.”
This week’s boost in click-through rankings for moderate-to-expensive brands like Victoria’s Secret, DKNY, and Kate Spade could also be signs of “a slight opening up of the economy,” Nauda says.
Stylefeeder will probably never be able to explain why waffle makers are hot in Boston, or why shoppers are gunning for Kalashnikov air soft BB guns in San Diego. But for e-retailers and their marketing consultants, the why may not be as important as the what. “There are, in fact, real patterns underlying what we see,” Jacob says. (There has to be some reality to the regional brand preferences, or Stylefeeder wouldn’t be seeing a doubling in click-through rates when it shows visitors items that are popular in their regions.) “There are 2.5 million monthly unique [visitors] hitting the site, so there’s enough volume that this data matters,” says Jacob. Now the question is—to whom?
