MONEYBALL: NETFLIX & BIG DATA

By Michael Avon, CEO & Founder - January 25, 2016

How Netflix uses big data

In the middle of a massive selloff on Wall Street, Netflix released a blockbuster earnings report early last week, blowing away analysts earnings estimates with 23% year-over-year revenue growth in Q4 of 2015. Even more impressive, Netflix added more than 5.5 million net new subscribers during the quarter, far more than Wall Street expected. So what is driving Netflix's business success at a time when many traditional media companies have been struggling?

One answer is Netflix's embrace of big data and analytics as a key part of its business. When Netflix decides which movies or TV shows it wants to license from studios, the company relies on actual consumer data, and a lot of it, as opposed to relying solely on the gut feel of a team of programmers. Netflix knows with a high degree of certainty that specific groups, or audiences, of its user base like to watch specific types of dramas or action movies. It knows which stars seem to resonate with specific audiences and which genres and titles tend to work best with those audiences at certain times of the year. This enables Netflix to be more precise and more efficient when it decides what content to license. And that is critical for a business that must offer enough content to convince tens of millions of people to keep paying their monthly fees, while ensuring that licensing and development costs remain low enough to turn a profit.

Even more impressive is Netflix's use of data analytics in developing new, original content. For example, when the U.S. rights to the British political thriller House of Cards were available, Netflix was able to use its vast array of consumer data to determine the number of subscribers who were likely to watch an Americanized version of the political drama. It could then see that many of those likely viewers also enjoyed movies directed by David Fincher, such as The Social Network. Many of those same people were also self-identified Kevin Spacey fans based on their viewing patterns. Netflix knew what type of TV shows and movies engaged those audiences and which types of content tended to bore them.

So by the time Netflix had invested millions of dollars to acquire the rights to House of Cards and develop a U.S. version, with Fincher as Executive Producer and Spacey the star, it already had a pretty good idea that the show would resonate with its subscribers. Beyond that, the Company knew to whom it should promote the new show and had a pretty good idea what content in trailers or descriptions of the show would best resonate with specific types of subscribers. The end result helped change the face of television in the United States, and added to Netflix's incredible business performance.

Now none of this is to say that a machine or algorithm could produce a show as good as House of Cards or, alone, predict its success. Of course, the fact that an amazing director and an incredibly talented cast came together with a great concept and a well-written script had a lot to do with the show's success. And, without a doubt, there is still a significant amount of gut feel necessary to pick and produce successful shows and movies. The fact that Netflix could use data and analytics, though, to measure and predict what would resonate with its subscribers removed a tremendous amount of risk from the very high cost investment of green-lighting a new show. And the fact that Netflix could use data to market the show to its own user base, precisely targeting the people most likely to engage with the new show, meant that the marketing dollars to launch the new show were far more efficiently and effectively spent than is often the case in Hollywood.

Netflix isn't the only studio using big data to shape the content we view. Amazon, for example, is using the same data analytics capabilities it uses in its retail businesses to help it better create and market premium content to its Prime Video subscribers. Even many traditional studios are using more sophisticated analytics to develop and market movies and some TV shows. The wave of big data analytics is absolutely beginning to come to Hollywood.

We are, though, only in the early innings of this data-driven approach to content production, marketing and distribution. I expect to see a continued acceleration of the use of data analytics and technology in the content creation and distribution world in the coming months and years as more media companies, traditional and cutting edge, embrace the use of big data. Hollywood, after all, is the place that took an esoteric book about the use of big data and advanced analytics in Major League Baseball and turned it into a highly entertaining, Oscar-nominated movie, Moneyball.

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