Today, the web is all about figuring out what you want: an article to read, a video to watch, music to listen to, products to buy, restaurants to visit, things to do. With great power (to search) comes great responsibility (to choose):
“We are now living in an era where information is everywhere and it is everything. There really is just too much information and everyone is screaming at you from every possible medium to try their service or buy their product. We need a way to parse through the noise and find what works for us; to weed out the reviews and recommendations that don’t work for us,” explains Mouthee cofounder David Pritzker.
Mouthee, an iOS app, is helping you choose by housing all your friends’ recommendations about restaurants, movies, music, books, and hotels. You can browse by category, ask a friend for a “rec,” or write your own gushing review.
And it’s pretty useful – for example, movie recs include movie previews, duration, release data, and a link to buy on iTunes, while restaurants link to OpenTable for making reservations. Unlike some other apps, you can also write negative recommendations.
So Mouthee is taking the “friends” approach to recommendations. It’s based on the belief that our friends know us best, and it mimics word-of-mouth – “Hey, what movie should I see on Friday?” Unsurprisingly, this is also Facebook’s approach with its recommendations box; if you visit external sites like WSJ.com, you can see which content your friends “like” the most. Or, you could just post a status update asking for advice.
The other approach uses robots (algorithms) to figure out who you are and make recommendations based on users similar to you. For example, Hunch builds a taste graph that other apps can use to predict your preferences for restaurants, things to do, movies, and music. Lunch encourages you to join communities and browse the opinions of people similar to you. (Lunch also branches out into topics like politics, parenting, and green living – with the broader goal of finding common ground among diverse people and creating dialogue.)
But Pritzker downplays this option: “We don’t really believe strongly that a ‘bot’ or algorithm is as successful at knowing your taste as your friend is.” Still, Mouthee will be incorporating some aspect of the “people similar to you” model in the future.
Google is also hedging its bets, with search and advertising based on your Google+ connections as well as your location and interests. Maybe a hybrid approach is actually the way to go.
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