Hunch wants you to give it some ideas
Hunch.com helps users search for answers -- but first, it performs a detailed search on the users themselves.
Launching today after a year in development, Hunch aims to supply users with computer-generated advice on thousands of lifestyle and consumer questions: What kind of dog should I buy? What should I get dad for Father’s Day? Which book by George Orwell would I like?
Most important, though, Hunch is not a search engine. Rather than scouring the open Web for information, as Google, Microsoft’s new Bing and scores of others do, or collating written opinions, as Amazon.com does, Hunch computes answers by comparing what it knows about you to what it knows about people like you.
“Ultimately, what we’re doing is providing a kind of shortcut through human expert systems,” said Hunch founder Caterina Fake, who also started Flickr.com, the popular photo-sharing site that was acquired by Yahoo in 2005.
By first inviting users to answer as many as 1,500 questions about themselves -- an addictive kind of personality test that involves such diverse questions as political orientation, relationship status and whether you believe in UFOs and keep your closet organized -- Hunch looks to assemble a demographic profile whose depth could rival anything in the commercial universe.
The New York company also believes that users stand to benefit from this kind of large-scale data farming -- not just from getting better answers, but also from discovering the many microdemographics to which they belong. Hunch also says it will not sell user data to marketers.
“Without any strong consumer protection laws with respect to privacy,” he said, problems can arise in unforeseen situations, such as what happens to your data “if a company you can’t trust buys a company you can trust.”
Companies that steward large amounts of consumer information must survive on their reputations, said Ari Schwartz, chief operating officer of the Center for Democracy and Technology.
“Privacy is a part of trust,” he said, adding that users are getting better at identifying which sites are trustworthy. “If they do burn their users on privacy, it’s going to hurt them.”
Fake agrees, noting that the user-first values she built into Flickr helped the site succeed in becoming a global community of photography lovers.
“The most important thing you can do with users is be honest and trustworthy -- and don’t use the data in any way they wouldn’t want.”
After Hunch has boiled you down into a nicely organized set of preference data, it’s your turn to make a specific request. Say you’re interested in finding the perfect kind of dog for you: The site then asks you a series of five to 10 specific questions to narrow your hypothetical dog by size, temperament, price and so forth.
The result of all that work is the set of dogs that Hunch thinks fit your preferences, purse and personality. Now you know whether you’re destined to own a border collie, a vizsla or a plain old mutt.
But before you run down to the animal shelter, remember that this is just the best guess of a nascent system. Hunch’s real power, said Fake, will come after it has aggregated data from a huge number of users, the better to decide which buckets and sub-buckets each user should fit into.
“The measure of a really good piece of social software is whether it gets better or not as people use it,” she said. Because Hunch has been in a limited preview to the company’s inner circle, its user base is lacking diversity.
“For things like video games and blogs, we’re in pretty good shape right now,” she said. “We’re probably less good at guessing what kinds of handbags women in Illinois like.”
Fake said that based on user feedback, Hunch is getting it right about 80% of the time, but that she’d like to pump that number up to 90% or 95%.
The 10-person company, which has raised $2 million in venture capital from Bessemer Venture Partners and General Catalyst Partners, is not yet concentrating on turning a profit. But eventually it will use the rich user profiles it generates to sell highly targeted advertising.
As Fake figures it: What better time to sell a product to a consumer than the moment after they’ve decided exactly what they want?