Netflix is employing 300 people to maintain and improve its content recommendations, and spends $150 million according to the company’s Chief Product Officer Neil Hunt. He told an ACM conference that even improving recommendations a little bit could lead to dramatically increased revenue due to smaller churn.
Hunt explained Netflix has a very limited window to convince a customer to watch something. The typical user only looks at the Netflix app one or two minutes, he said, and may browse 20 to 50 titles before either choosing something to watch or giving up entirely and doing something else.
That’s why Netflix is trying to find the best possible content for everyone, which can include diving deep into niche and even fringe content. He said he believed ‘embracing the long tail’ with its recommendations also helps to maximise the opportunity for long time content producers, he said, arguing that this could lead to a democratisation of content distribution.
French regulators had asked to examine Netflix recommendation algorithms for fear they had an ingrained American bias.