Movie recommendation engines from Netflix and Amazon assume a solitary movie viewing experience, but start-up Foundd allows up to five friends to combine their movie preferences to find common viewing ground across multiple catalogs.
Users rate movies during a short “getting to know you” quiz and then connect to friends via Facebook or Twitter.
“Netflix has put a lot of effort into predicting how much I’ll like every one of their movies,” says Foundd CEO Lasse Clausen. “But as a user, I don’t really care whether I’ll dislike a movie with 2.3 or with 2.35 stars, that doesn’t help me find a good movie. Foundd focuses on giving more accurate predictions over a smaller number of movies and those that the user will really like.”
“A ton of companies are working on recommendations around video and movies,” notes TechCrunch. “But the idea to match up personalized recommendations within a small group is still somewhat novel. And handy.”
Clausen hopes that in the future Foundd’s algorithm will include games, books, Internet video and apps. Multiple platforms would allow for a more nuanced and complete rating and recommendation system.
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