What would YouTube want with a recommendation engine?
Techcrunch recently reported that Google (as the owner of YouTube) is looking at the purchase of Twitter-based movie recommendation site Fflick. Judging by the Fflick site today, this is more than just idle rumor:
What are the implications for YouTube?
On the one hand it signals a more concerted effort from the beefy video sharing site to play nicer with the other social networks in the playground (or at least hold hands with Twitter whilst working out a relationship with arch-rival Facebook). It could mean we see the kind of functionality in YouTube present on other video networks like Livestream: a display of all the Twitter backchannel related to a piece of content. For instance:
See the running commentary down the right? This is more 'chat' than 'comments' with tight integration with Facebook/Twitter.
On the other hand, it also opens up the possibility of YouTube to start mining user data to offer recommendations. How useful is this on a video site? Just look at the Netflix story. The popular US video rental service has made a big deal of its ability to guess what movie you want to add to your rental wishlist. It bases its recommendations on what you've seen in the past, how you rated it, what others like you have seen (and a bunch of other variables even including the day of the week on which you're viewing the site!) Netflix prizes this technology enough to have made it a central part of the site navigation and even paid a team from AT&T $1 M for coming up with a winnning algorithm in 2009.
YouTube has a much bigger collection of content, a wealth of behavioural data through its huge viewing figures. It generally knows less about its visitors than Netflix does as the site doesn't require you to login to engage. Potentially, that's where the Twitter piece comes in to play: you give up some of this information about yourself each time you tweet. Fflick provides the service to tie the tweet back to the video. Fflick also provides the service to pick through your Tweets and use these to determine what content you might like to see next.
This kind of application of predictive analytics is hot right now in the social media space. Foursquare is believed to be using predictive analytics to keep Facebook at bay in the loca
Social media is making us increasingly impatient and we are starting to demand more from our interfaces. Add to that the growing market for hand-held devices that offer precious little space for content, let alone navigation, and you have a compelling case for services using whatever technology they can to pinpoint what you probably want to do next, and serve that up. If they don't engage, the next video-sharing site is only a short URL away.