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IDEA #36 – Social Audio / Video Recommendations

Problem: I’m out and want to rent a movie, or buy a movie / CD / book — I’d like recommendations from friends or people with similar tastes as mine.

Solution: Dial a phone number (VXML) or send a text message (SMS) and receive recommendations (or selections from your own wishlist) for books, movies, or music — whatever you’re looking to purchase / rent. If calling, you’ll hear audio recommendations by your friends / network, or others that have similar tastes to you.

Essentially you could create a business that starts compiling an archive of audio reviews — a user could somehow import their Netflix account info, and/or Amazon.com account info, and/or Last.fm account info … and then start creating (short – 30 secs?) audio reviews/recommendations of their favorites (or least favorites).

This could come in handy when:

  • You’re at Blockbuster and want to rent a movie. You want a comedy — based on your profile you filled-out online, we’ll recommend some great comedies that are out. Or we’ll tell you comedies on your wishlist. Or we’ll tell you comedies that your friends / network have recommended — and we might even play an audio message by the person, so you can hear what they have to say about the movie.
  • You’re at the airport and need a book. Ditto as above.
  • You’re at the mall and want to buy a new CD. Ditto as above.

Video Reviews: This could also morph into video reviews — same concept, except users would primarily use this on the web (since it’s all video).

Get Users Reviewing Instantly: We could make either of these concepts very simple — a quick / easy interface that gets them recording reviews immediately. Similar to a HotOrNot interface, the user is presented with a movie or CD or book, rates it and gives a quick audio or video review of it. If the user imports their account info from Netflix / Amazon / Last.fm — then we can immediately provide the user with movies/music/books that they have seen/heard/read.

Social Networking: Then we start tying users together and provide recommendations to them — showing them recommendations by friends / family / those they admire, but also neighbors (people that they don’t know, but whom have similar tastes; Last.fm does this).