**After careful review of all submitted Entries to the RecLab Prize on Overstock.com Contest, the Peer Review Committee has determined that no Entry met the effectiveness at generating lift and novelty of design to be selected for the Semi-Final Stage. Thank you to all the participating teams. At this time the RecLab Prize has concluded.**
Online product recommendations are among the shopping tools most widely used by consumers who need to easily find relevant and enticing products from the millions available online. Overstock.com has worked with RichRelevance since 2009 to present shoppers with dynamic recommendations that grow smarter over time and accurately reflect more than 60 different ways that people shop on the site (by price, by brand, by category).
Now Overstock.com is partnering with RichRelevance to open up this real-world business challenge to the academic community, challenging academic researchers to advance the state of the art in personalized product recommendations by crafting an algorithm that delivers a 10% or greater lift over existing product recommendations on Overstock.com. If no team achieves a 10% lift, then smaller prizes will be awarded. A brief overview of the contest follows.
- Maximum Prize: $1,000,000The winning team will receive a cash prize of $100,000 USD multiplied by the percentage that the entrant’s algorithm performed over RichRelevance’s algorithm—up to a maximum amount of $1,000,000. For example, if the winner produced 3.34% more revenue per session than RichRelevance’s algorithm, the winner will receive $330,000.
- Institution Prize: up to $250,000Should the winning team be affiliated with an educational institution, up to 25% of the prize amount (funded separately from the Team Winner’s Prize) can be allocated to the educational institution(s).
- You have to register to enter.
- Individuals may enter individually or as part of a team. Regardless of the number of team members, each team must designate a team leader. Individuals may be members of multiple Teams; however, Teams with an identical set of members are not permitted.
- The contest is also open to teams affiliated with academic institutions. In order for an educational institution to be eligible to receive the Institution Prize, at least one member of a Team must be actively enrolled in or employed by an educational institution(s) at the time of entry. They also need to have obtained any and all necessary consent to participate in the competition and designate the educational institution(s) in their registration. Multiple institutions can be listed as long as the Team Leader designates which institution(s) will receive the Institution Prize and in what proportion, if the Team wins. To be eligible for the Institution Prize, educational institutions must be accredited by an accrediting agency recognized by the U.S. Secretary of Education or, for foreign educational institutions only, by an accrediting agency approved by the national government of the country where such institution is located.
- The RecLab Prize is now concluded.
- To compete in the competition, your submission must be one of ten top Semi-Finalists chosen by a peer review committee appointed by Overstock.com and RichRelevance.
- If any of the Semi-Finalists produce 1% more revenue per session than existing algorithms, then the top three submissions (as measured by revenue per session) will be run on 10% of sessions each for an additional three weeks. The best performing of these algorithms, as judged by increase in revenue per session over the existing algorithms, will be eligible for a prize of up to $1,000,000.