Since quite a few of us are loyal Netflix subscribers, thought some of you might find this interesting. In the Atlantic, Alexis Madrigal lets his Nerd Flag fly:
If you use Netflix, you’ve probably wondered about the specific genres that it suggests to you. Some of them just seem so specific that it’s absurd. Emotional Fight-the-System Documentaries? Period Pieces About Royalty Based on Real Life? Foreign Satanic Stories from the 1980s?
If Netflix can show such tiny slices of cinema to any given user, and they have 40 million users, how vast did their set of “personalized genres” need to be to describe the entire Hollywood universe?
This idle wonder turned to rabid fascination when I realized that I could capture each and every microgenre that Netflix’s algorithm has ever created.
Through a combination of elbow grease and spam-level repetition, we discovered that Netflix possesses not several hundred genres, or even several thousand, but 76,897 unique ways to describe types of movies…
Netflix cooperated with my quest to understand what they internally call “altgenres,” and made VP of product innovation Todd Yellin, the man who conceived of the system, available for an in-depth interview…
If we reverse engineered Yellin’s system, it was Yellin himself who imagined a much more ambitious reverse-engineering process. Using large teams of people specially trained to watch movies, Netflix deconstructed Hollywood. They paid people to watch films and tag them with all kinds of metadata. This process is so sophisticated and precise that taggers receive a 36-page training document that teaches them how to rate movies on their sexually suggestive content, goriness, romance levels, and even narrative elements like plot conclusiveness.
They capture dozens of different movie attributes. They even rate the moral status of characters. When these tags are combined with millions of users viewing habits, they become Netflix’s competitive advantage. The company’s main goal as a business is to gain and retain subscribers. And the genres that it displays to people are a key part of that strategy. “Members connect with these [genre] rows so well that we measure an increase in member retention by placing the most tailored rows higher on the page instead of lower,” the company revealed in a 2012 blog post. The better Netflix shows that it knows you, the likelier you are to stick around.
And now, they have a terrific advantage in their efforts to produce their own content: Netflix has created a database of American cinematic predilections. The data can’t tell them how to make a TV show, but it can tell them what they should be making. When they create a show like House of Cards, they aren’t guessing at what people want…
I’ve been a customer since March 2003, and I can verify that the ‘suggestions’ system has vastly improved over that period. Because the intersection between Studio Ghibli and BBC police mysteries is not ‘Scooby-Doo’, thank you very much!