MoviePass and the Netflix Business Model


I’ve always loved watching movies, especially in the theater. There’s nothing like seeing a film on the big screen with a full surround-sound system. It’s an experience you can’t quite reproduce at home. But I never went to see movies in the theater as much as I would’ve liked to because it was too expensive. In New York and Los Angeles, it’s $15+ for a ticket—and don’t even get me started on the food and drink prices. So last year, when MoviePass lowered their service to $9.99 a month, I immediately signed up. With it, you can see one movie every day, potentially thirty movies a month, all for $9.99—less than the price of one ticket. It was a no-brainer for someone like me.

Since signing up, I’ve seen more movies in the theater than ever—at least two a week, sometimes more. But it makes you wonder how this could be profitable for MoviePass. They still have to pay the movie theaters in full for every ticket sold through their service. Which means they are losing money each time one of their users buys a ticket. So how could they possibly stay in business?

Well, MoviePass knows they are going to lose money in the short term, (a short term that may last several years, maybe even a decade) but they’re in it for the long haul. They have a master plan.

The first thing to realize is MoviePass is not really a movie ticket company; they are a data company. In that sense, they’re more like Google, Facebook, Spotify, or Netflix than AMC, Fandango, Paramount, or Warner Brothers. They plan to collect user data to sell to vested third parties. In MoviePass’s case, that third party may be advertisers or movie studios wanting to improve their box office returns.

As it is now, the only data movie studios have are the box office results—simply the number of tickets sold. They don’t know who bought which ticket or why audiences chose to go see one movie and not another. You could say, “Because the movie was good.” Except there are plenty of critically acclaimed movies that don’t succeed at the box office. Then you could say, “Well, critics have different tastes than general audiences.” But then how do you know which movies general audiences will like? You can only go by history and try to emulate successful films from the past. The studios are currently doing this, which is why you see so many sequels, remakes, and reboots.

Except that formula doesn’t always work. You try to copy Men in Black ($250-million box office), and you get R.I.P.D. ($30-million). Or even Transformers 2 ($400-million) vs. Transformers 5 ($130-million). There are diminishing returns to delivering the same thing over and over again.

So the studios then look more granularly at why one movie was more successful than another. Things like casting, number of action scenes, locations, amount of jokes, etc. They try and they try, but they can’t seem to reliably find the right formula. The studios continue to make movies that they think will be hits but end up flops. Why?

The thing is, people don’t want to watch the same thing over and over again, otherwise they would literally watch the same thing over and over again. Instead, they go to the movies to see something new, because they want to see something new. Not too new that it’s something completely foreign—they want something familiar, but fresh and original.

So how do you know what that movie will be? That’s the big question.

You could say, “Movies are art, so it’s impossible to predict.” But Netflix would disagree. They have figured out how to make hit show after hit show. How do they do it? With data and algorithms.

Netflix knows who watches what and when, how quickly, if they stop watching a show or movie and exactly at which point. They can find correlations in that data to figure out what people like—what keeps them watching a show/movie. They use that data to build recommendation algorithms to suggest which shows and movies a user might like next based on the shows and movies they’ve watched in the past. These suggestions may be off at first, but they get better and better over time with the more data (movies and shows watched by a user) Netflix has.

Once Netflix had a near flawless recommendation algorithm, they used that algorithm to create new shows, using exactly the ingredients their data suggested. This may seem too mathematical for something that’s supposed to be artistic, but it’s obviously working. Netflix keeps producing hit after hit.

However, Netflix only has streaming data. MoviePass hopes to bring that same data-driven business model to the live movie theater experience. Through their app, they are collecting much more intricate data than the movie studios can, who only know how many people bought tickets. Studios don’t have data on who the people who bought the tickets were. Or how often they go to the movies. Or which movies they like and why.

MoviePass will know all that—who buys which tickets for which movies—and they will find correlations between that data. If they can create the right algorithm to compute the correlations between successful movies, then they will know the elements needed to create a box office hit. Once you have years worth of data of an individual’s movie preferences, you will be able to predict precisely which upcoming movies they will and won’t see. If you know that, you’re guaranteed box office success.

In the future, all studio movies will be made by algorithms. Not directly—humans will still write, direct, and act in them (for now). But the humans will be adhering closely to the guidelines and elements the algorithm recommends. Netflix is already doing this. They give creative freedom to their writers and directors, but within certain agreed parameters—parameters dictated by their data and algorithms. This is not encouraging to someone like me (a creative writer). I get frustrated by movies that are too formulaic, but most consumers don’t have such refined taste as to be able to notice or care.

MoviePass’s main objective right now is to gather consumer data. Their only goal is to own as much of the market for selling movie tickets as they can. That’s why they price their service so low. They want as many subscribers as possible. The more users you have, the more data you have. The more data you have, the more profitable you will be.

We are in the age of big data. Data is the most valuable commodity in the world. The companies that capitalize on their user’s personal data (Google, Amazon, Facebook) are the most successful. Just look at Amazon. They dominate the market for selling just about any physical product. They did this by offering the lowest prices for everything, losing massive amounts of money in the process, but by doing so, they also put their competitors out of business. Once the competition was gone and Amazon had massive amounts of user data, they could capitalize on that and start turning profits. By knowing everything their customers have bought in the past, Amazon is able to sell products they know their customers will buy in the future. Now Jeff Bezos is the richest man in the world.

The business model for data companies is to make massive amounts of money in the long term by first losing massive amounts of money in the short term. You have to spend money to make money, as they say. Spotify did this in the online music industry. Netflix did it in the online movie/television industry. Now, MoviePass is doing the same thing in the offline movie industry. In their case, the data is: based on the movies a consumer bought tickets for in the past, what movie will they buy a ticket for in the future. Then, MoviePass can sell that data to movie studios, or as Netflix is currently doing, make the movies themselves.

MoviePass is losing tons of money right now by paying every ticket price in full, but that’s all a part of their plan. If they stay afloat long enough, eventually they will have priceless data. The more personal data you collect, the more you know your customers’ preferences, the more successfully you can sell products to them. You’ll have a massive edge over the competition. You could sell consumers everything they want because you’d know what they want before they want it. With enough data and the right algorithms, profits come automatically and exponentiallyVenture capitalists are banking on this, which is why they are investing millions of dollars in MoviePass now, hoping it will turn into billions of dollars later.

Once MoviePass has enough personal data, pinpointing their individual users’ precise taste in movies, they will know how any movie will perform at the box office before it’s released. If you know that, you’d only make successful movies. Then, MoviePass will become “the Amazon of movies.” Or that’s their plan, at least. Of course, Amazon is also trying to become the Amazon of movies. And Netflix may get more involved with theatrical releases, as well. Plus, there’s Google (YouTube) to contend with, Apple, Hulu, and the studios themselves may become more data-driven in the future.

Then there’s another elephant in the room: the fact that, no matter the price, people simply don’t want to go out to the movies anymore when they can simply stay home and turn on Netflix. In the future, the in-home viewing experience will only get better until it actually does emulate the big-screen theater experience. That may be MoviePass’s biggest obstacle.

MoviePass has a master plan, but that doesn’t necessarily mean they will succeed. They could run out of venture capital before they start to turn a profit. History is littered with bankrupt companies who attempted to be “the Amazon of _____.” Will MoviePass ultimately make it? Only time will tell. The fact that they keep altering their terms of service for the worse is not a good sign. But I’ll enjoy going to the movie theater for practically free while I can.

4 thoughts on “MoviePass and the Netflix Business Model

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