Could Advertising Optimization Algorithms Be Crowdsourced?

This article in Wired is a good read about Netflix’s competition to improve it’s movie recommendation engine.

I found it interesting for a few reasons. First, as a Netflix user I’ve always felt their movie suggestions for me have not been very good. I usually understand why they recommended what they did, but it’s never stuff I have much of an interest in watching.

Second, it’s amazing that the teams working on the competition who are competing for a $1 million prize are actually collaborating with each other and are more into accomplishing the goal then winning the money. That’s great to see.

Third, the dynamics of math algorithms versus human psychology is something that I’m curious to see play out. Will the psychologist outperform the math powerhouses?

This also leads to an interesting question for me. The advertising industry is now full of algorithms, and continues to move further in that direction. Could an advertising company do a similar thing and offer a huge monetary prize to have their optimization or prediction algorithms improved? I absolutely think they could. Netflix is positive that they’ll get over $1 million in value for improvements to their recommendation engine, not to mention all the publicity it’s generated. A larger advertising player could easily extract more than $1 million in value from improved algorithms.

Seems like a no brainer.