But several crucial techniques garnered from the contest have been folded into the company's in-house movie recommendation software, Cinematch, and customer retention rates have improved slightly.
There is some pedigree here, too: Chicisimo's co-founder, Gabriel Aldamiz-echadarria, had previously been a VP and member of the board at Strands, which develops personalization and recommendation software that powers social sites like these.
With the rise of e-commerce, this sort of recommendation software is a hot field, both inside companies and in academia.
Hunch will keep its operations in New York and continue to experiment with developing recommendation software while it begins integrating some of its tools into eBay's site.
Once a site knows something about a visitor's interests and buying tendencies, it can use recommendation software to lead him to the cash register.
Last fall, Netflix awarded $1 million to a team of statisticians and computer scientists who won a three-year contest to analyze the movie rental history of 500,000 subscribers and improve the predictive accuracy of Netflix's recommendation software by at least 10 percent.
And auctions could get even smarter: Net Perceptions, a software company, has already developed "recommendation software" that looks at what a buyer has bid on (successfully or unsuccessfully) in the past.
For example, contestants in Netflix's competition to improve its recommendation software received a training data set containing the movie preferences of more than 480,000 customers who had, as they say in the trade, been "de-identified".
The three-year competition for the first Netflix Prize, which began in 2006, offered $1 million to the first group that could improve the predictive accuracy of the company's movie recommendation software by at least 10 percent.
Then it created a sales recommendation software engine that proved that online retailers could sell as much as fulfill.
