This supplemental case follows up on the Netflix Prize Contest described in Netflix: Designing the Netflix Prize (A). In the A case, Netflix CEO Reed Hastings must decide how to organize a crowdsourcing contest to improve the algorithms for Netflix's movie recommendation software. The B case follows the contest from the building of the platform in 2006 to the awarding of the highest prize in 2009. The B cause also considers the aftermath of the contest, and the issues of successfully implementing a winning idea from a contest.

In 2006, Reed Hastings, CEO of Netflix, was looking for a way to solve Netflix's customer churn problem. Netflix used Cinematch, its proprietary movie recommendation software, to promote individually determined best-fit movies to customers. Hastings determined that a 10% improvement to the Cinematch algorithm would decrease customer churn and increase annual revenue by up to $89 million. However, traditional options for improving the algorithm, such as hiring and training new employees, were time intensive and costly. Hastings decided to improve Netflix's software by crowdsourcing, and began planning the Netflix Prize, an open contest searching for a 10% improvement on Cinematch. The case examines the dilemmas Hastings faced as he planned the contest, such as whether to use an existing crowdsourcing platform or create his own, what company information to expose, how to protect customer privacy while making internal datasets public, how to allocate IP, and how to manage the crowd.