If you’ve ever wondered what would happen if the top two teams in the Netflix Prize competition united and put their predictive analytics skills to work together, you’ll soon find out. Big data service provider Opera Solutions acquired Austrian predictive analytics specialist Commendo on Tuesday, putting members of the top two teams under the same roof and giving Opera a new recommendation engine to serve its clients engaged in e-commerce.
The purchase isn’t too surprising. On the heels of its $84 million equity financing round in September, Opera Founder and CEO Arnab Gupta told me he was looking to go shopping for technology and for brainpower. Commendo, which sells a consumer recommendation engine called Recommendo, seems to fit both desires.
Aside from its obvious utility in e-commerce, the Commendo acquisition could help Opera establish a business around the video-streaming model it has developed internally. That model relies heavily on accurate recommendations among users with similar interests, as well as a peer-to-peer architecture, in its mission to improve both the volume and delivery of streaming video services. Commendo’s brains and the intellectual property underlying Recommendo could prove valuable in creating a custom recommendation engine for such a service.
During the Netflix Prize competition in 2009, Commendo employees participated as part of the winning team, named BellKor’s Pragmatic Chaos, while Opera employees were part of runner-up team The Ensemble. The goal was to improve the accuracy of Netflix’s recommendation algorithm by 10 percent, which both teams did. They actually finished in a statistical tie at 10.06 percent, but BellKor’s Pragmatic Chaos submitted its final algorithm 20 minutes earlier than did The Ensemble.
Watch the video below to see my on-stage discussion with Opera’s Gupta at our Structure: Data event last week.
Image courtesy of Flickr user Bitterjug.