House Of Creativity: Netflix Casts Big Data In Transformation Role

In many creative industries, the leading companies will be the ones—like Netflix—that invest heavily in collecting high quantity and quality data, use that data to inform creative processes across the company, and make big, data-driven bets.

House Of Creativity: Netflix Casts Big Data In Transformation Role

In 2012, Netflix found itself in an existential crisis. Its very favorable content licensing deal with Starz ended. Even a $300 million offer to continue licensing Starz’s catalog, 10 times the 2008 price, was not enough, and the deal fell through. Hulu, a Netflix killer that included the catalogs of Disney, Time Warner, and 21st Century Fox, was proving to be a formidable competitor. Finally, Netflix was reeling from a debacle that led to an 80% drop in the stock’s value.

Netflix needed to do something. Its chief content officer, Ted Sarandos, became a vocal proponent for a bold, new direction: Netflix should become an original content creator, he argued. But this big idea begged a big question: How could Netflix, an internet company, compete in a creative field that others with deeper pockets had spent decades specializing in?

Yet here we are four years later. Netflix did double down on original content. To date, it has won more than 90 awards and 400-plus nominations for its original content. In 2016, it had more Emmy nominations than NBC. It is now an existential threat for cable operators. And the momentum is not slowing down: Netflix’s 2016 Q4 earnings show it having its biggest quarterly gain in subscribers in the company’s history.

How did this happen?

Big Data Leads To Big Creativity

What Netflix did dispels a common myth that data is the enemy of creativity. Instead, it shows how data might just lead us into a creative renaissance.

In 2013, Netflix gave $100 million to a creative team to produce two 13-episode seasons of a remake of the 1990s BBC miniseries “House of Cards.” That kind of investment was unheard of in a world where the typical approach was to order a single pilot episode or one season of a series at most.

What seemed like a risky bet was, in fact, a move informed by big data. Netflix already knew that a big group of its users loved the original BBC show, and that those same users, on average, also loved anything starring Kevin Spacey or directed by David Fincher. The intersection of all three interests made it a no-brainer to go full-steam ahead with the production. Powering insights like this is a team of 300 Netflix employees focused on big data.

Another highly acclaimed Netflix show, “Orange Is The New Black,” was also a result of Netflix’s big data analysis: Research showed that Netflix users loved dark comedies as well as female lead characters.

It’s not just the Netflix content team who benefited from big data; its marketing team did, too. Marketing to the right Netflix users was immensely cheaper and more effective with Netflix’s powerful recommendation engine. In fact, last year Netflix was recognized as the Marketer Of The Year by the advertising industry’s main association—despite the fact it does very little marketing of its shows outside of its own interface. Steve Swasey, Netflix’s VP of corporate communications, revealed to GigaOm: “We don’t have to spend millions to get people to tune into this … 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.’”

In other words, marketing, another creative discipline, is empowered by big data.

Here are the three reasons why data and creativity are a perfect marriage:

1. Better data leads to better creative products: In an equally meteoric rise, Tesla started from scratch in 2003, and in 2014, its Model S was rated the best overall car of the year by Consumer Reports. Perhaps this is not a coincidence given that Tesla’s creatives and engineers have access to mountains of data that all Tesla cars send back to the company automatically. This created a foundation for creative design and software updates that other car companies didn’t have.

2. Better data leads to better targeting, which helps creative products affect their audiences more deeply: Take Spotify’s recent “Thanks 2016, It’s Been Weird” campaign, which consists of huge, eye-catching billboards whose localized content is drawn from user data. A New York billboard calls out the listener who played the “Hamilton” soundtrack more than 5,000 times, while a U.K. billboard talks about the thousands of Brits who played “It’s the End of the World As We Know It” the day of the Brexit vote. Because these ads are based on local trends, they hit home.

3. Big data makes big creative bets a lot less risky: Recently, companies have gained access to a new pool of high-quality data that is fundamentally changing how they make creative bets. Data from experiments tells companies what customers actually do, while older approaches with serious flaws, such as surveys and focus groups, only tell companies how customers might act. This more accurate data emboldens companies that adopt mass experimentation to make big bets that other companies with less accurate data would never make.

It’s not a coincidence that Netflix performs over 1,000 experiments per year. It’s also not a coincidence that the most successful tech companies in the world, such as Amazon, Facebook, Google, and Intuit, also do the same.

In many creative industries, the leading companies will be the ones—like Netflix—that invest heavily in collecting high quantity and quality data, use that data to inform creative processes across the company, and make big, data-driven bets.