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This story has been corrected since it was originally published.
I hit the pause button roughly one-third of the way through the first episode of “House of Cards,” the political drama premiering on Netflix Feb. 1. By doing so, I created what is known in the world of Big Data as an “event” — a discrete action that could be logged, recorded and analyzed. Every single day, Netflix, by far the largest provider of commercial streaming video programming in the United States, registers hundreds of millions of such events. As a consequence, the company knows more about our viewing habits than many of us realize. Netflix doesn’t know merely what we’re watching, but when, where and with what kind of device we’re watching. It keeps a record of every time we pause the action — or rewind, or fast-forward — and how many of us abandon a show entirely after watching for a few minutes.
Netflix might not know exactly why I personally hit the pause button — I was checking on my sick son, home from school with the flu — but if enough people pause or rewind or fast-forward at the same place during the same show, the data crunchers can start to make some inferences. Perhaps the action slowed down too much to hold viewer interest — bored now! — or maybe the plot became too convoluted. Or maybe that sex scene was just so hot it had to be watched again. If enough of us never end up restarting the show after taking a break, the inference could be even stronger: maybe the show just sucked.
In 2012, for the first time ever, Americans watched more movies legally delivered via the Internet than on physical formats like Blu-Ray discs or DVDs. The shift signified more than a simple switch in formats; it also marked a major difference in how much information the providers of online programming can gather about our viewing habits. Netflix is at the forefront of this sea change, a pioneer straddling the intersection where Big Data and entertainment media intersect. With “House of Cards,” we’re getting our first real glimpse at what this new world will look like.
For at least a year, Netflix has been explicit about its plans to exploit its Big Data capabilities to influence its programming choices. “House of Cards” is one of the first major test cases of this Big Data-driven creative strategy. For almost a year, Netflix executives have told us that their detailed knowledge of Netflix subscriber viewing preferences clinched their decision to license a remake of the popular and critically well regarded 1990 BBC miniseries. Netflix’s data indicated that the same subscribers who loved the original BBC production also gobbled down movies starring
Kevin Spacey or directed by David Fincher. Therefore, concluded Netflix executives, a remake of the BBC drama with Spacey and Fincher attached was a no-brainer, to the point that the company committed $100 million for two 13-episode seasons.
“We know what people watch on Netflix and we’re able with a high degree of confidence to understand how big a likely audience is for a given show based on people’s viewing habits,” Netflix communications director Jonathan Friedland told Wired in November. “We want to continue to have something for everybody. But as time goes on, we get better at selecting what that something for everybody is that gets high engagement.”
The strategy has advantages that go beyond the assumption of built-in popularity. Netflix also believes it can save big on marketing costs because Netflix’s recommendation engine will do all the heavy lifting. Already, Netflix claims that 75 percent of its subscribers are influenced by what Netflix suggests to subscribers that they will like.
“We don’t have to spend millions to get people to tune into this,” Steve Swasey, Netflix’s V.P. of corporate communications, told GigaOm last March. “Through our algorithms we can determine who might be interested in Kevin Spacey or political drama and say to them, ‘You might want to watch this.’”
And maybe we will. Early reviews for “House of Cards” are promising. It will be fascinating to find out how many people gorge themselves on all 13 episodes this upcoming weekend. (Netflix data shows that’s how we like to consume our TV series now — in great gulps and marathons — so that’s how it will give them to us.) But one does end up wondering: What will the Big Data approach mean for the creative process? If Netflix perfects the job of giving us exactly what we want, when and how will we be exposed to things that are new and different, the movies and TV shows we would never imagine we might like unless given the chance? Can the auteur survive in an age when computer algorithms are the ultimate focus group? And just how many political dramas starring Kevin Spacey can we stand, anyway?
The scope of the data collected by Netflix from its 29 million streaming video subscribers is staggering. Every search you make, every positive or negative rating you give to what you just watched, is piped in along with ratings data from third-party providers like Nielsen. Location data, device data, social media references, bookmarks. Every time a viewer logs on he or she needs to be authenticated. Every movie or TV show also has its own associated licensing data. The logistics involved with handling every bit of information generated by Netflix viewers — and making sense of it — are pure geek wizardry.