Netflix is notoriously tight-lipped about the data people most want to know about the service and its subscribers. Most specifically, they avoid releasing anything concrete about how many people are actually watching their original productions. It’s a nice bit of curtain-drawing that lets them soak up all the cultural heft that comes from being THE THING everyone is talking about without ever having to publicly worry that they are speaking to anyone beyond digital-obsessed social media junkies who relish the opportunity to write anything in the Stranger Things font.
(You could make a case that they are slowly weaponizing the process of targeting exactly those kinds of people, although you’d have to account for the Adam Sandler conundrum, so probably best to just say that their strategy is a big, big tent.)
They make up for this lack of information with semi-constant dumps of other kinds of information, usually about some funny quirk of how people actually use the service: hey, people usually watch two episodes of a series in one sitting. Hey, people tend to watch Breaking Bad faster than they watch Gilmore Girls. Hey, two-thirds of users with cats have tried to train them to click the “Continue Watching” button.
For the average viewer, I suspect these tidbits of info are – if not completely pointless – on close personal terms with pointless. I guess if you have a lot of personal worth invested in your style of Netflix watching, they make sense, although I suspect we’re at least a couple of years away from Buzzfeed quizzes predicting what kind of Netflixer you are or people using phrases like “Four-episodes-a-sitting enthusiast” on their online dating profiles. (Good god, I can already hear the Christmas party conversations ringing through my ears like the wails of the damned.)
As info dumps go, though, they are interesting for their underlying assumptions and implications, which tend to either lay bare the semi-terrifying degree to which Netflix has entwined itself into our daily lives or suggest the ways in which they will be doing that even more effectively in the near future. Certainly that’s the case with its latest bit of info, that people tend to take a break between binging series with a movie or two, and that these movies tend to be pretty predictable based on whatever series they just finished watching.
That, in and of itself, is, again, weird that a (presumably) statistically relevant number of people watch The Princess Bride after gorging on Unbreakable Kimmy Schmidt, but as a viewer I don’t really know what you do with that information, other than maybe congratulate yourself on being the kind of devil-may-care renegade who watches The Martian after gorging on Unbreakable Kimmy Schmidt. Keep flying that freak flag high, brother.
What is more interesting is the fact that the average lag time between finishing one series and then committing to a whole entire other series is three days. It takes most people an entire long weekend before committing themselves to like 20-plus more hours of television, and they can’t even not watch something in the interim – they feel the need to fill that gap with a movie, a little snack between trips to the all-you-can-eat buffet.
Ted Sarandos, Chief Content Officer of Netflix, confirmed that this was typical of the Netflix experience. “We find that you’re either a very casual user, or it’s a part of your daily life,” he said over the phone. “And for most of our members, it’s a part of their daily life.” He also explained that the typical Netflix user spent about 70 per cent of their time watching TV, and 30 per cent watching movies, a number that holds pretty constant across countries and varied libraries. So, basically, whatever actual show its subscribers are watching, Netflix is basically replacing the TV experience, but with a few more hooks to keep you around for when your stories are finished.
The barb on those hooks, or more specifically how those are about to grow, is the other interesting implication of this information. At present, Netflix’s recommendation system is a little broad. It seems to have a basic idea of the type of content you like, and it will give you a couple of those in between suggesting that, despite months of not even so much as slowing your scroll speed as you zip past it, this might finally be the time you decide to watch The Ranch, or maybe one of its dozens of comedy specials. (I do love to laugh, so kudos there, I guess.)
You can improve it by rating stuff or, of course, watching more, but being able to sort out this kind of time or event-specific preference is vastly more valuable than anything you might actively tell them. You may call yourself a coffee addict, for instance, but presumably you’re more interested in it at breakfast than when you’re on the way home from the bar. Now, Netflix just knows you like coffee, and will offer it to you whenever you ask them for a drink. Soon, they’ll be able to tell that what you really want now is some water – which will make both going to them and clicking on one of their shows all the more attractive.
“Statistically, when you’ve finished a series, the next thing you’ll probably want to watch is a series,” explains Sarandos. “But, at that moment, you probably want to watch a movie. We want these algorithms to get more and more refined and more and more sophisticated, so that it recognizes moods.”
“Over time, it will evolve and be even more sophisticated. So maybe it will consider what time of day you’re watching, what kind of device you’re watching on,” he adds. “You probably do want to watch something different if you’re on an iPad at eight in the morning than if you’re watching television at eight at night. This is all kind of an iteration of the sophisticated merchandising and recommendation.”
Related
- Netflix is now offering the ability to download movies and shows for offline viewing
- Why does Netflix always have near-perfect movie recommendations, and then one odd ball?
This isn’t entirely new in the whole online streaming world, at least if you broaden the horizons a bit. Songza, for instance, was a music service that essentially forced you to pick what you wanted to listen to based on your “mood” – none of that messy “thinking about and specifically choosing something.” It’s a feature, if not quite as prominent, on almost all music services now, and it has popped up now and again on video streaming, too – the recently departed shomi’s graduated genre service was an attempt at this kind of thing.
The trick here is that Netflix will likely keep this all in the background. “What we’re trying to do is work on the personalization experience to put choosing in the background and loving at the front of mind,” as Sarandos explained it. Rather than asking you, it will attempt to understand what you’re in the mood for, give it to you, and it will never even occur to you that you were guided to continue watching, without even so much as a three-day break.
It all sounds a little Black Mirror-y, of course, but that is basically just the promise of so much of this deep-dive tech data: giving you what you want before you even know you want it. And speaking of wanting, if you understand that Black Mirror reference, you may want to check out Inception — statistically speaking, it’s what you probably want to watch next anyway.
Full List of TV + Movie Pairings – Canada
| Series | Movie Pairings |
| Bates Motel | 22 Jump Street, Dirty Grandpa |
| Better Call Saul | Catch Me If You Can, Captain Phillips |
| Black Mirror | Inception, Hot Girls Wanted |
| Bloodline | The Big Short, Bridge of Spies |
| BoJack Horseman | Tony Robbins: I Am Not Your Guru, Ali Wong: Baby Cobra |
| Breaking Bad | Django Unchained, Pulp Fiction |
| Dexter | Neighbors, Spy |
| Fuller House | Inside Out, How to Lose a Guy in 10 Days |
| Gilmore Girls | Mean Girls, Clueless |
| Gossip Girl | Mean Girls, Sex and the City: The Movie |
| Grace & Frankie | August: Osage County, Tammy |
| Grey’s Anatomy | Sleeping with Other People, Couples Retreat |
| House of Cards | Ant Man, Beasts of No Nation |
| How To Get Away With Murder | Still Alice, About Time |
| Making A Murderer | Aileen: Life and Death of a Serial Killer, The Seven Five |
| Marvel’s Daredevil | The Punisher, The Matrix Reloaded |
| Marvel’s Jessica Jones | V for Vendetta, The Hunger Games |
| Marvel’s Luke Cage | Deadpool, 13TH |
| Master of None | Aziz Ansari Live at Madison Square Garden, That Awkward Moment |
| Narcos | Scarface, Cartel Land, Narco Cultura |
| Orange is the New Black | The Fundamentals of Caring, Horrible Bosses 2 |
| Pretty Little Liars | Hush, The Mortal Instruments: City of Bones |
| Scream | Ride Along, Friends with Benefits |
| Sense8 | Ex Machina, Tron: Legacy |
| Stranger Things | Ghostbusters, Star Wars: The Force Awakens |
| Suits | Now You See Me, Ocean’s Twelve |
| The Ranch | The Ridiculous 6, RED |
| The Walking Dead | The Martian, The Do-Over |
| Unbreakable Kimmy Schmidt | 13 Going on 30, The Princess Bride |
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