Where Big Data Meets Entertainment

Andrew Leonard takes a look at how Netflix is ordering its content and is troubled by a few things. Firstly, by the bizarrely detailed analysis of viewers media consumption habits:

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.

Netflix doesn't just know that you are more likely to be watching a thriller on Saturday night than on Monday afternoon, but it also knows what you are more likely to be watching on your tablet as compared to your phone or laptop; or what people in a particular ZIP code like to watch on their tablets on a Sunday afternoon. Netflix even tracks how many people start tuning out when the credits start to roll.

A bit creepy, but not all that surprising, right? What's strange is what they're doing with all of that information - they're using it to reduce the risk of the content they produce:

For at least a year, Netflix has been explicit about its plans to exploit its Big Data capabilities to influence its programming choices. ... 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 ["House of Cards"]. 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.”

But what does this mean for the future? Leonard suspects - quite accurately, IMO, that it could result in very questionable artistic decisions:

The interesting and potentially troubling question is how a reliance on Big Data might funnel craftsmanship in particular directions. What happens when directors approach the editing room armed with the knowledge that a certain subset of subscribers are opposed to jump cuts or get off on gruesome torture scenes or just want to see blow jobs. Is that all we’ll be offered? We've seen what happens when news publications specialize in just delivering online content that maximizes page views. It isn't always the most edifying spectacle. Do we really want creative decisions about how a show looks and feels to be made according to an algorithm counting how many times we've bailed out of other shows?

I sure don't want to see any sort of optimization of the art that's produced for me. I'm not a voracious consumer of television and movies, but I love being surprised by the unpredictable nature of a District 9 or Children of Men. I don't mind if it means I need to wade through a load of crap to get there - after all, it takes seeing the bad to make the good really shine.