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Delivery, Discovery and Data

Inside the Design of the 'Saturday Night Live' App

As NBC’s iconic Saturday Night Live approached its 40th anniversary earlier this year, the idea of creating an app came up. But, says Michael Martin, senior vice president, Product, Technology & Operations, at NBC Entertainment Digital, they had to think long and hard about whether to proceed. “Consumers are much more discerning and careful as to whether they want to go through the steps of downloading an app and taking up phone storage,” he says. “The bar is pretty high nowadays.” Discoverability is also an issue. Experts estimate there are more than 3 million apps for Apple and Android.

Martin and his group decided that to be successful, an app would have to fulfill two criteria: It would have to perform a utility really well and communicate that utility easily, and the assets had to be unique enough to merit an app. Forty years of SNL has produced 800 episodes with roughly 6,000 individual comedy sketches. But the library had already been available digitally for some time, and Martin was troubled at how viewers consumed the content. “Fundamentally, people were snacking on that content,” he says. “The consumption pattern would be to watch one or less than one clip of the newest, latest, most topical video.”

The Metadata Army
The challenge was how to make every season and every sketch more discoverable and valuable. One advantage the digital group had was NBC’s 40 years of audience research. The first important piece of information gleaned was just how varied the sketches were—by season, cast members, guest stars, topics, categories and many other factors. “We realized that there were scores if not hundreds of facets that could describe an individual sketch,” he says. “We needed something different than the typical recommendation engines, based on commonality in consumption patterns. Those patterns didn’t hold for this content.”

They hired what they called a “metadata army” of people who took four months to go through all 6,000 sketches, re-cataloging them for the hundreds of defined facets. “The semantic model is very flexible,” says Martin. “It isn’t just the facets that are important but their relationship to one another.” The sketches were ultimately connected by 33,000 relationships. “It became an incredibly dense model, so we can take some of what we learned from audience research and put a prediction engine on top of it,” he adds.

Eddie Lee, vice president of technology for NBC Entertainment Digital, was responsible for building the prediction engine from scratch. “We tried to apply and re-use some of the traditional, off-the-shelf recommendation engines, but they couldn’t deal with our model,” Lee says. The app and web site—powered by the MarkLogic Enterprise NoSQL database platform—integrate, manage and search the database. “Building the prediction engine took two to three months, constructing and iterating it,” he says. “It included connection between the CMS [content management system] and the database, built on top of MarkLogic using our resources and our set of rules.” The system also has enterprise traits for security, data integrity and scalability.

Interaction and Interfaces
Also critical was an interface mechanism that let the user interact with the content, and, the team hoped, turn a snack into a meal. The user experience team came up with a gesture-based function that provided real-time feedback to the engine. “We didn’t want to give the user a choice of thumbs up or thumbs down,” Martin says. “The user wouldn’t just perceive that as work, but also it’s too simplistic to get the outcome we were looking for.”

Sample of the app’s emoji library

Instead, if the viewer swipes left, he or she gets a new video. “If you’ve watched 75 percent of that first video, we assume that you liked most of it and will harvest facets that we’ll serve in the second and third video,” says Martin. “If you swipe it very quickly, we assume that you didn’t like that one whatsoever and will revise the model accordingly. And if you swipe five or six videos very quickly, we’ll put you on another path, in a totally non-technical way.”

Swiping up and down to add to favorites is another way the app signals viewer preferences about the sketches. “We built that interface into a product in a way that we don’t have to spend any time up front to explain it to the consumer,” says Martin. “But it also results in a high-quality data stream.” He notes that the data is completely anonymous. The UE design was recently nominated for an Interactive Emmy Award for outstanding user interface.

Doesn’t Need More Cowbell
The response to the app has been stronger than Martin and his team could have anticipated. “We had over 100 million clips streamed to the app,” he says. “Most critical, we definitely unlocked binging. On average, people who were consuming less than one sketch in the past are now watching several to a dozen sketches.”

Since its February release, the team has continually updated the app. It is now at version 1.3.1. “We’ve extended capabilities and added new features and polished some things to make predictions better,” Martin says. And the team has prepared some entirely new features for the opening of SNL‘s 41st season on Oct. 3. “We are adding new social features so people can share their personalized experiences with family and friends,” Martin adds. “We’re also looking for the opportunity to get the cast and show more involved in curating and highlighting content. And our emoji library will expand to include new cast members.”

The app is free and available on iOS and Android (

“Virgin Flight,” from Season 40, Episode 19, May 2, 2015