A few years ago, I remember scrolling through Netflix and finding a few movies that looked slightly interesting. Now, I have about 5-6 movies on my “to-watch” list at all times. Netflix, the online movie and TV subscription service, currently has over 50 million subscribers globally. In 2006 they had 10 million subscribers. It’s clear that Netflix has grown to be one of the top web apps to date. The question is how they did it – did they improve their movie selection, or did they improve their movie selection suggestions?
We can assume that Netflix did both. However, the more important development was the suggestions. Alexis Madrigal spent several weeks with a group of coworkers pulling apart Netflix’s magic. According to their results presented in the article “How Netflix Reverse Engineered Hollywood”, Netflix has 76,897 unique ways to describe movies. It all boils down to tags; Netflix has analyzed and tagged every movie and TV show in every possible way imaginable. “When these tags are combined with millions of users viewing habits, they become Netflix’s competitive advantage. The company’s main goal as a business is to gain and retain subscribers. And the genres that it displays to people are a key part of that strategy”.
There is only one other similar intelligence approach in existence. “Netflix has built a system that really only has one analog in the tech world: Facebook’s NewsFeed”. Both Netflix and Facebook’s NewsFeed operate under the users viewing and liking habits – depending on how you interact with Netflix or Facebook, their algorithms spit out other certain movies or links you might be interested in. But what happens if you mess with this algorithm and like everything?
Mat Honan did. In “I liked Everything I saw on Facebook for Two Days. Here’s What It Did to Me” featured on Wired, Honan explains that after his Like binge, his Facebook NewsFeed became extremely liberal and extremely conservative. None of his friends popped up anymore; it was all advertisements and articles. “As I went to bed that first night and scrolled through my NewsFeed, the updates I a saw were (in order): Huffington Post, Upworthy, Huffington Post, Upworthy, a Levi’s ad, Space.com, Huffington Post, Upworthy, The Verge, Huffington Post, Space.com, Upworthy, Space.com.”
So I did the same thing, but with Netflix and only for 20 minutes. I went to “Personalize” and 5-starred and clicked “interested” for every movie that popped up. On Netflix’s splash page I did the same thing. The difference between Honan and my result’s was that Netflix recycled the movies I already 5-starred. They had no other movies to suggest, no other reserves to pull from. Facebook, on the other hand, has the entire internet to suggest to you. Which ends with a clogged NewsFeed full of stuff that in the end, Honan didn’t like anyways.
Algorithms do an amazing job of feeding consumers stuff that they’d be interested in. But they can be screwed with, and that’s because in the end, they’re robots trying to cater to humans.