Netflix is using Big Data to project the potential of its original programming, reports David Carr in The New York Times (2/25/13). Specifically, Netflix knew that House of Cards, a series “directed by David Fincher, starring Kevin Spacey and based on a popular British series” would be a hit. Because of data gleaned from its “27 million subscribers in the nation and 33 million worldwide … it already knew that a healthy share had streamed the work of Mr. Fincher … and films featuring Mr. Spacey had always done well, as had the British version of House of Cards.”
Using data to analyze potential is nothing new among film and television producers, but “Netflix has mind-boggling access to consumer sentiment in real time.” As Netflix chief communications officer Jonathan Friedland explains: “Because we have a direct relationship with consumers, we know what people like to watch and that helps us understand how big the interest is going to be for a given show.” Netflix also used data to target its promotional trailers, with Kevin Spacey fans seeing trailers featuring him, for example, and film buffs seeing trailers highlighting David Fincher.
Skeptics, such as John Landgraf of FX Networks, say using algorithms to pick hits has its limits. “Data can only tell you what people have liked before, not what they don’t know they are going to like in the future,” he says. “A good high-end programmer’s job is to find the white spaces in our collective psyche that aren’t filled by an existing television show.” However, Rick Smolan, author of The Human Face of Big Data, thinks using algorithms to pick hits beats “wandering out and shooting a shotgun in the night sky, hoping (to) hit something.”