Ann Summers says it will use data gathered from its ecommerce shop to create more cross-category promotions in its stores, similar to Marks & Spencer’s Marketing Week Engage Award-winning Dine In For £10 offer.
Technology researchers are being offered a $1m prize to solve a complex condundrum faced by retailers – how to choose the best online product recommendations to show shoppers.
By Darren Vengroff, Chief Scientist, RichRelevance
When done right, relevant product recommendations can deliver a 5 – 30 percent lift in conversion and sustain or even increase these levels over the long term. Darren Vengroff offers three best practices that can help retailers deliver on the promise of personalised product recommendations.
Two big new prize contests just getting under way take a page from the innovative, exciting competition run by Netflix. In a nail-biting finish in the fall of 2009, the movie rental service paid $1 million to a global team of data mavens, who just edged out another group, in most improving its online film recommendations.
The Netflix contest was celebrated as a triumph for the company and as a catalyst for bringing new techniques to data analysis. But in 2010, Netflix was forced to cancel a planned second prize because of privacy concerns. Two researchers showed that the supposedly anonymous data from the first contest could be used to identify customers. That eventually brought an inquiry from the Federal Trade Commission and a lawsuit. So Netflix shelved its plans for a second contest.
The online retailer is pulling a Netflix, dangling the promise of a rich reward–not to mention some serious bragging rights–to the team that increases customer purchases.
Anyone who comes up with a 10% more effective method for recommending products to shoppers at Overstock.com will win $1 million. Overstock and its recommendation technology vendor, RichRelevance, are collaborating on the contest, modeled after a $1 million challenge by video rental e-retailer Netflix.
Overstock.com is offering a prize of up to $1 million to computer researchers who come up with a way to improve how the online retailer automatically recommends products to customers.
Facebook and Twitter have become powerful marketing tools for many brands. But where there are tremendous opportunities, there can also be serious risks.