Content Discovery Still Sucks

We’ve spent years entering intricate details about ourselves into various places on the web and yet we still can’t get a truly great recommendation out of a machine.

Don’t get me wrong, recommendation engines have come a long way, but it still feels like a scatter-gun approach. We’re bombarded with ‘recommendations’ and left to sift through the pile until we can find the one thing we haven’t already got or are actually interested in.

  • Spotify and Last.fm know pretty much every song I’ve ever listened to. 
  • Amazon knows what books I read. 
  • iTunes and Netflix know the films I like to watch. 
  • Digg knows which articles I read, and which I skip over. (Yes, I’m a Digg Reader fan) 
  • My iPhone knows the places I go and how long I’m there. 
  • Facebook and Twitter know the people I like to talk to, and the ones I don’t. 

We have all this data about us out there on the web but it’s all being stored in (mostly) proprietary silos that makes it really difficult to do anything useful with.

Imagine what would happen if all of this data came together.

We could build recommendation engines that could move past the content and start to build context. In the least creepiest way possible, they could begin to understand who we are and use that information to make our lives a little better.

This is something that’s really been bugging me lately. 
We have the technology, we have the data. 
Lets do this.

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