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Don’t you hate it when you hire a DVD and it’s just not your kind of movie.

Social networks such Criticker and Filmtrust are helping and it’s no surprise that a company who’s very business is about renting movies is trying to improve the “success rate” of hire versus like ratio.

Netflix have announced a contest where the prize is $1 million, to the person or team that can create a better system for improving their movie predictions system.

I love their contest and they describe it here.

Netflix is all about connecting people to the movies they love. To help customers find those movies, we’ve developed our world-class movie recommendation system: Cinematch. Now there are a lot of interesting alternative approaches to how Cinematch works that we haven’t tried. We’re curious whether any of these can beat Cinematch by making better predictions.

So, we thought we’d make a contest out of finding the answer. It’s ‘easy’, really. We provide you with a lot of anonymous rating data, and a prediction accuracy bar that is 10% better than what Cinematch can do on the same training data set. If you develop a system that we judge most beats that bar on the qualifying test set we provide, you get serious money and the bragging rights. But (and you knew there would be a catch, right?) only if you share your method with us and describe to the world how you did it and why it works. To keep things interesting, in addition to the Grand Prize, we’re also offering a USD 50,000 Progress Prize each year the contest runs. It goes to the team whose system we judge shows the most improvement over the previous year’s best accuracy bar on the same qualifying test set. No improvement, no prize.

They even have a leader board to ensure transparency of the competition, and the 2007 winner was recently announced providing a 8.43% improvement on Cinematch.

Perspective: It’s great to see companies outsource innovation in this way, and rewarding the successful innovators. There are many ways to tap into the wisdom of consumers to help with solving challenges like this, it’s just that most brands / companies aren’t prepared to let consumers in.