What emerged from the work is this conclusion: Netflix has meticulously analyzed and tagged every movie and TV show imaginable. They possess a stockpile of data about Hollywood entertainment that is absolutely unprecedented.
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.
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.
What a huge undertaking, and a demonstration of Amazon-like patience for a company like Netflix—slowly, quietly, build a long-view competitive advantage in technology and process that becomes impossible for others to copy, and that eventually enables a whole new range of products that are themselves hard to compete with.
This sort of rich metadata is what I’d expect IMDB to have, but a categorization exercise of so much subjective material benefits from the guidance of a single hand, while self-policing committees take much too long.