Netflix, Big Data, and House of Cards

House of Cards

Like many I spent this past Superb Owl weekend watching the political thriller House of Cards rather than Beyonce or Football. The Netflix remake of the BBC adaptation of the Michael Dobbs novel is fantastic, and as it turns out, tailored to me, my friends, and our interests.

Netflix is a company driven by big data. Their service is dependent upon customization and recommendations so as to keep us watching shows that are usually old and somewhat stale.

House of Cards, while somewhat old, is actually entirely new, at least when it comes to television production. As noted by Andrew Leonard writing for Salon:

“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.

This approach to planning and purchasing entertainment content, if successful, will spread rapidly. Yet big data is not something that can be started just by turning on the taps. Netflix has taken a long time and a lot of data to even begin to understand their audience. For example last year it was revealed they collect (at least) the following:

  • More than 25 million users
  • About 30 million plays per day (and it tracks every time you rewind, fast forward and pause a movie)
  • More than 2 billion hours of streaming video watched during the last three months of 2011 alone
  • About 4 million ratings per day
  • About 3 million searches per day
  • Geo-location data
  • Device information
  • Time of day and week (it now can verify that users watch more TV shows during the week and more movies during the weekend)
  • Metadata from third parties such as Nielsen
  • Social media data from Facebook and Twitter

That's obviously a ton of data, that they've at least once offered million dollar prizes to help sort efficiently. It also allows them to bid on and acquire scripts and content with insights that others may not have, even giving them the confidence to take greater financial risks:

While networks traditionally order a show based on whether it likes a pilot, Netflix ordered two full seasons (26 episodes) of House of Cards without seeing a single scene. It reportedly bid more than $100 million to secure first rights to the show, outbidding HBO and AMC because it is utterly convinced the show will be a big hit.

Interestingly enough this data driven content generation seems to also allow for greater creative autonomy:

But the show may have never been made had it not been for the artistic license Netflix gave the production company Media Rights Capital. Dobbs was wary of licensing the story for fear of relinquishing control and seeing his story sullied or sold out by the whims of traditional network or studio executives. But Netflix gave the production company wide latitude to do as it pleased.

I do however have to wonder if Media Rights Capital and the talent involved had access to the Netflix analytic and audience data? Probably not, but I could see in the future a special producers dashboard that at least gave them access.

They do enjoy the freedom of not being part of the broadcast cartels and the narrative that is based around commercial interruption. Netflix is also fostering a new kind of viewing culture that combined with big data may make it easier for a new show to become a hit faster and immerse fans in compelling storytelling.

That’s one of the wins for the format that Netflix offers. If this were a traditional television series, I would have had to wait a week between the first and second episodes, and that would’ve colored my feelings about it rather differently. Being able to watch the next installment immediately after the first made me retroactively like the premiere more; I got to the pay-off more quickly, and to a second episode with more momentum and less awkward exposition.

Also a plus for Netflix: The episodes of the show can be whatever length they need to be, and not edited down (or filled out) to fit a time slot predetermined by broadcast schedules or commercial breaks. It’s not something that is immediately perceptible, but as time goes on you start to notice it; nothing feels rushed, or stretched out of natural shape, and the story flows more naturally.

Comments

David Brooks in the NY Times:

If you asked me to describe the rising philosophy of the day, I’d say it is data-ism. We now have the ability to gather huge amounts of data. This ability seems to carry with it certain cultural assumptions — that everything that can be measured should be measured; that data is a transparent and reliable lens that allows us to filter out emotionalism and ideology; that data will help us do remarkable things — like foretell the future.

http://www.nytimes.com/2013/02/05/opinion/brooks-the-philosophy-of-data....

"We’re more fooled by noise than ever before, and it’s because of a nasty phenomenon called “big data.” With big data, researchers have brought cherry-picking to an industrial level.

Modernity provides too many variables, but too little data per variable. So the spurious relationships grow much, much faster than real information.

In other words: Big data may mean more information, but it also means more false information."

http://www.wired.com/opinion/2013/02/big-data-means-big-errors-people/

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