Most people would like to believe that making a decision is a rational process that involves careful thought and deliberation. But it is more often a by-product of pure chance, a fluke, or even a headache imposed by a friend or family member. But now, another quasi-mystical force of nature is available for consultation when the agony of choice hits—the recommendation website.
One has the option of two new websites that offer this service. Each has a broadly different approach to a familiar quandary: How do we help someone make a decision, or give a timely recommendation?
Get educated: Sites such as Hunch get smarter the more you use them
Likaholix (www.likaholix.com) is the breezier of the two, a fun, easy, almost Twitter-like network for discovering likes and shared interests with a community of users. Founded by two ex-Googlers, the site is currently in open beta, which is a stage where they invite the public to sign up and try out the features.
Likaholix asks you for your interests and “likes” (in movies, music, books, games, you name it), and delivers personalized recommendations based on what other users liked, and nudges you together with people who have similar tastes. Search, click, “like” and repeat. The more you use it, the better it gets at delivering recommendations.
The Internet, of course, loves “liking” things. You can “like” almost anything on social networking site Facebook, for example, from your friend’s new photos to status updates. A little thumbs up appears next to said item, very similar to your personalized badge of approval. “Like” a blog post in Google Reader, and a tiny smiley face adorns the post. Even Twitter allows you to declare your undying love for certain tweets with its “favourite” button. But the innocuous act of liking something isn’t merely a cute social feature, but the fuel that drives complex algorithms under the hood of sites such as Likaholix. It’s the collective likes of its users that Likaholix processes to find out what else you might fancy.
Hunch (www.hunch.com) is the other website, founded on a very interesting premise. The site asks an almost endless series of innocuous questions, such as “Do you like bumper cars? Do you live in a city?”, to “train” the system. It then takes a hunch about any decision one needs to take. These could range from the serious, such as “Should I change jobs right now?”, to trivial, such as “Should I eat pancakes today?”
It’s a fresh take on search, one that delivers personalized, smart information that an objective search engine cannot. “Hunch isn’t directly competitive with search, but we are compatible with search,” says Caterina Fake, co-founder of Hunch. “Once you’ve found the topic you’re interested in, Hunch asks you 10 questions or fewer and gives you a result it wouldn’t give someone else. It gets smarter the more you use it, as it gets to know you better,” she says. Recommendation sites have been around for a while, especially with personalized online radio services such as Last.fm. But they’re now moving out of specificities into broader terrain, and both Likaholix and Hunch offer interesting alternatives to opaque, objective search engines such as Google or Microsoft’s Bing. By customizing answers and recommendations to individuals, and adding a fun social aspect on top, they’re gradually making the search for information less of a chore.
And if you can’t decide which of the two to use — why not toss a coin?