NETFLIX, THE MATCHMAKER
Streaming giant happily applies secret-sauce algorithm to help subscribers discover their next addictive show,
NEW YORK— Netflix wants subscribers to know it’s looking out for them.
For instance, the average Netflix subscriber might never guess that its dark superhero drama Jessica Jones might strike similar chords as the zany hijinks of Unbreakable Kimmy Schmidt. Netflix is happy to help you make the connection.
Much of the attention showered on this streaming-video giant in recent years has dwelled on its insatiable appetite for original content and for creators who produce it.
“We want to appeal to as many different people as possible and appeal to the many moods that each person has,” says vice-president of product innovation Todd Yellin. “The more diverse our content, the more likely that someone, at their moment of truth about what they’re going to watch, will choose to go to Netflix.”
But this service’s multibilliondollar annual outlay for new programming necessitates another challenge: helping each program get discovered by the subscribers most likely to enjoy it. Four out of five of the shows watched on Netflix were found by its subscribers thanks to recommendations offered them, Netflix says.
Those suggested new favourites are much more customized for each subscriber than might be evident from a glance at the Netflix home page.
Most every row of program sugges- tions (even generic-seeming categories such as “Comedies” and “Dramas”) is tailored for each subscriber, Yellin says.
And how the rows are arranged vertically on the home page is a function of the subscriber’s preferences.
“You might have ‘Comedies’ as your fifth row,” Yellin says, “and for another person, it might be 25th. And someone else might not get a comedy row at all.”
So your Netflix is different from everybody else’s. But where do these tips come from?
“It’s very important that the titles most relevant to each person bubble up to the top of the catalogue,” Yellin says. “And we want those relevant titles to be diverse. We don’t want to make the amateur mistake of getting caught in an echo chamber, such as: Just because you watched one horror title, slapping in front of you nothing but more horror titles.”
Yellin likens the process of providing bespoke TV for each customer to a three-way collaboration.
First, a legion of Netflix “taggers” screens every program, tagging different elements that compose it. This data is crunched and continuously refined by the company’s secret-sauce algorithm. Then, viewer habits gathered by Netflix from its 100 million accounts worldwide add more grist to the mill.
Thus, can Netflix take a “gateway” program and point the person watching it to other unexpected or unknown fare with presumably similar appeal. Consider Ozark, which viewers might be led to from any of several directions, Yellin explains.
Ozark is a recently released original drama series starring Jason Bateman as a money-laundering family man who’s seriously jammed up with the Mexican drug cartel he works for.
“We’ve found that people who tend to watch Blacklist and House of Cards tend to like Ozark,” Yellin says. “But another kind of person who will find he likes Ozark is a fan of Narcos and El Chapo and other drug-cartel-oriented dramas and documentaries.”
But, wait, there’s yet another “taste community” rallying to Ozark, Yellin says: fans of the 2015 film The Big Short, which deals with Wall Street dirty tricks, have been found to respond to the money monkeyshines that animate Ozark.
“It’s not like we could have guessed this ahead of time,” Yellin says. “We just track which shows tend to cluster together. Who would have thought that Jessica Jones and Kimmy Schmidt would cluster together?” As well as — no kidding — Making a Murderer and a John Mulaney standup concert.