were saying on Twitter about specific plays in games. They weren’t thinking about the ad industry yet, Roy says. This was about crowdsourcing highlight reels automatically, and tie-ins to fantasy football.
But the sheer volume of social-media content about television was astounding. “This looks bigger than a sports thing or football plays. This is about every show on TV,” Roy realized. “We went from, let’s do this fine granularity of comments on plays in football, to let’s make a machine that watches all of television and listens to all the conversations.” The result, he says, is “the most comprehensive database of what people [say] about what’s on TV. We call it the TV genome.”
(I must admit it would be frightening if the first sentient machine gets its worldview from television and social media. On the other hand, kids these days…)
Fast forward to today, and Bluefin has amassed a database of tweets, blog posts, and other public comments—from Facebook, YouTube, and so on—from nearly 20 million people, to go along with its video analysis of programs and ads across 117 TV networks. Roy says the company tracks 15-16 million comments a month that are about live TV, with about 5 percent month-to-month growth, in the U.S. (Bluefin processes the video—checking that a scheduled program is actually on-screen, for instance—and then throws out the raw footage.)
So where’s the business here? Well, it’s all in how you slice the data, Roy says. If you’re a network exec, you might want to know which programs—and time slots—are generating the most comments, so you can make decisions about scheduling, he says. Or you might want access to the demographics of your audience—gender, age range, whether they’re a parent, and what else they’re watching (all based on their social-media comments and public profile).
If you’re an ad exec, you might be interested in these demographics as well—and in things like what the audience overlap is between The Daily Show and other comedy programs and talk shows, for example. Bluefin has gotten interest from big soda and candy companies, as well as TV networks and ad agencies, Roy says, though he declined to name any yet.
It’s still very early in the product game for Bluefin. My hunch is social media analytics is where the future of Nielsen ratings, polls, and TV-ad placement is going—and the question is whether the analysis that a company like Bluefin can provide is worth paying big bucks for, compared to other options. Bluefin points to the size of its database and depth of its analytics as differentiators from the competition, of which there is plenty.
However it plays out, the company is clearly entering a new phase—as is Roy, who seems to be embracing his transition from professor to CEO. The last three years were about developing a “deep and rigorous technology stack,” he says. Now it’s about “how to productize the data. You don’t invent this kind of thing overnight. If you want to build a tall building, you dig a deep basement.”
