Letting the Web Pick Gifts for Your Friends

Let the gift-giving grief begin.

Every year around this time, holiday shoppers fret and fuss over what to get their friends and family, scouring websites and store shelves in a frantic search for the most fitting favors of the season.

But this year, a few new Web tools offer to be a Santa's helper, whispering gift ideas in your ear.

Using profile information pulled from Facebook, these websites try to match your friends' preferences and interests with products you can buy online.

"Every e-commerce site has this problem of gifting, and it's a significant chunk of e-commerce," said Chris Dixon, CEO of Hunch.com, a recommendation engine that recently launched a social gift finder tool with Gifts.com.

But now that social networks, like Facebook and Twitter, have helped turn the Internet from just a "Web of cookies and computers" into a Web of people, he said, companies like his can add a layer of tools that analyze people and their preferences to personalize the Internet – and their purchases.

Hunch.com, for example, asks users a series of questions to develop a "taste profile" for them, which it then uses to help make recommendations about anything from books and movies to restaurants and gadgets.

Its latest project, in partnership with Gifts.com, combines Facebook profile data with its own taste-based algorithms to help shoppers find potential gift ideas for friends and family.

Once you allow the site to import information from your Facebook account, it looks for what your Facebook friends have "liked" or identified as interests.

It then builds a list of possible gifts for each friend, which you can refine by answering questions based on what you know about them.

The gift finder covers the basic demographic questions regarding, for example, gender and age. But it also goes a few steps further, asking about the person's favorite Olympic sports, political affiliation and even their thoughts on alien abduction.

Those questions might seem odd, but Dixon said they are especially predictive of people's tastes.

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