How does Netflix keep getting it right?

In 2013, Netflix came out with Orange is the New Black, one of the first original series to be debuted on an online streaming network. It was an immediate success, and ushered in years of Netflix continuously “getting it right”: House of Cards, Arrested Development, Unbreakable Kimmy Schmidt, numerous Marvel shows, Sense8 – and, most recently, Stranger Things.

What’s fascinating is that there seems to be pattern of streaming video networks coming out with great original shows while cable TV shows are declining in quality and originality. When Stranger Things came out in early July of 2016, Netflix had another hit, and I heard many people saying in awe, “How does Netflix keep getting it right?”

It turns out there’s a secret to their success: Big Data.

When Netflix comes out with a successful original series, it’s not a fluke or a stroke of good luck. It’s a carefully calculated move that was predetermined by months of data analysis. With most of those listed shows, Netflix invested close to $100 million, way more than the shows that float under the radar, because they had reasons to believe the shows would be a success. Netflix has been circumventing gambling and good faith with analysis – bypassing creativity with data.

Netflix is no stranger to analyzing what its subscribers enjoy watching. They first employed this algorithm to give users suggestions. One way that they do this is by studying movie ratings. Say that there are n users on Netflix who have rated m movies on a scale from 1 to 5. This information then gets put into a matrix, where each column is a user and each row is a movie. If a new user comes along and rates 1 movie, Netflix can predict their future ratings by looking at the ratings of people who rated that movie similarly. There are a lot of obstacles to navigate in this method, but the results are the suggestions that pop up on your Netflix home page.

With creating original content, Netflix has taken this method to the next step. Not only do they look at ratings, but “at what time you watch action, horror and humour, which scenes make you forward the video and which ones make you do a rewind, at which point you pause a video or stop it altogether and whether you watch Netflix on your TV, laptop or your phone” – all in order to determine what aspects of which shows are most popular. They will use the analysis of this data judge a possible new show, and even use further analysis to aid in the choosing of production value, starring actors, and directors.

Netflix’s use of Big Data poses many questions about ethics of data usage. I think the main one is this: Can statistics replace creativity? Is using data in this way creating a “reliance” on big data that might overshadow some of the more enjoyable parts of the arts? Despite all these questions, it’s hard to complain when a show like Stranger Things comes out, and immediately everyone is screaming their recommendation online and people are watching the entire season in one day. It seems like audiences are happier, sequels are fewer, and the risk is lower. But at what cost? Is risk and knowledge part of the entertainment game?

With big data and data analysis, we’re often asking ourselves how we can continue to expand use the skills to our advantage. Netflix is a data user that no one saw coming, and yet the company has probably reaped more benefits than most. And while Netflix is getting it right, it’s interesting to think about how their success is effecting the necessity of creativity in the entertainment industry.



Works Cited

Tiwari, Ritika. “How Netflix Is Using Big Data To Create Better, Successful Shows.” N.p., 24 Mar. 2016. Web. <>.

VanHemert, Kyle. “The Secret Sauce Behind Netflix’s Hit, “House Of Cards”: Big Data.” N.p., 19 Feb. 2013. Web. <>.