Ever wondered where to grab lunch? Or which DVD set to buy? Or even what to wear on -- gasp! -- a first date? “Just ask Hunch ,” says Flickr cofounder Caterina Fake , whose latest startup helps users make decisions by comparing what it knows about them to what it knows about others like them. The year-old site, which has attracted more than 1.5 million users and roughly $12 million in funding , assembles each user’s “taste profile” by asking him or her a series of questions. FastCompany.com gave Fake the same treatment. --Dan Macsai
Fast Company: After Yahoo acquired Flickr in 2005, you spent roughly four years working there. Why did you leave to found Hunch?
Caterina Fake: It’s not like I woke up one morning, got into the tub, and shouted “Eureka!” While I was at Yahoo, there was an absolutely laser-like focus on beating Google at search. But my background is in social software, social networks, and user-generated content. So I started working on social search, which I thought at the time was the most important, interesting, and significant piece of what Yahoo was focused on. That got me thinking about a site that could learn about an individual, and as a result be able to make great recommendations of things that person might like. Eventually, I left to cofound Hunch [alongside Hugo Lio ].
FC: How does the site work?
CF: First, we ask people a lot of questions about themselves -- demographics, political views, aesthetics, personality, all those kinds of things. And we try to make them fun and engaging.
FC: No wonder I was asked about alien abductions.
CF: [laughs] Right. We don’t have any psychological biases, and we haven’t hired any social scientists or anything. All of the questions are user-generated.
FC: What happens next?
CF: Then, we look at all the data for correlations. And some are quite funny and surprising . Turns out that people who broke their legs as kids are much more likely to like Madden football games than those who didn’t. Entrepreneurs are significantly more likely than non-entrepreneurs to have used a fake ID when they were underage. And people who wear cufflinks several times a month are much more likely to be thrown out of bars for rowdy behavior.
FC: How do you take stuff like that and use it to recommend, say, a hotel?
CF: Once we’ve developed a taste profile for you, our algorithms can start extrapolating. Obviously, the cufflink-wearer who’s getting thrown out of a bar for rowdy behavior is someone who likes to party. So we can infer that they’d be more likely to want a hotel that’s downtown and has an active nightlife. The algorithms work for all sorts of things: which college you should attend, which cookbook you should buy, where you should retire. And it’s all coming from the correlations. We don’t impose any of our own opinions.
FC: That sounds similar to the social graph, which defines people through their network of online contacts.
CF: It is, but our ultimate vision is to create a taste graph, which we believe is more significant. My mother may be the person with whom I have the closest correspondence -- so she’s closest to me on the social graph -- but the shoes we’re going to buy or the hotels we’re going to stay in are not necessarily commensurate.
FC: Tell me the last thing you Hunched -- assuming that’s the right verb.
CF: [laughs] Yeah, it works. Honestly, I just got back from lunch with a friend in the neighborhood, and I used Hunch to find a restaurant.
FC: And how’d it work out? Did you like the food?
CF: We actually ended up at a restaurant adjacent to the restaurant. After we met, my friend said, “You know, I’m more in the mood for…”
FC: Uh oh.
CF: No, seriously, I use Hunch all the time. The other day, I was looking for a laptop bag, and bought the one recommended by Hunch. And I promise you, it worked out great.