On the Web, we have links, which makes all media trackable. But on TV there are no links. So how do you track the audience response to a TV show or an ad? It’s all guesswork, panels, and surveys pretty much. But Deb Roy thinks he has a better answer: treat social media as a realtime “focus group in the wild” and tie that commentary back to TV. He wants to infer links from what people are talking about. In the video above, he explains his approach with Bluefin Labs.
“Think about a switchboard that links realtime TV with social media,” he says. Roy is the founder and CEO of Bluefin Labs, a video and language analytics startup in Cambridge, Massachusetts. Bluefin is creating a console for advertisers and TV programmers to measure the social resonance of their content. Using sophisticated semantic analysis, Bluefin can determine what peopel are saying about a particular TV show or commercial across various social media, including Twitter, Facebook, and blogs.
The console dashboard (see screenshot below) still spits out fairly raw data right now and is in the process of getting a cleaner UI, but essentially it shows what looks like a digital program guide with shows and ads being tracked on different channels. For each show or ad, the grey bars represent how much commentary was sparked across various social media, with an actual sampling of Tweets and Facebook comments, along with a tag cloud summarizing what people are saying about that show or ad.
Below is a portion of an audience response heatmap generated by Bluefin. Click the image for a full-size version.
A brand introducing a new product could see how often the name of the product is mentioned by people talking about it versus the overall umbrella brand. Advertisers interested in actually measuring engagement could use this data to see how much buzz is created given the reach of a particular show. They could look at the response rate per airing and then rank order each TV network to see where their ad dollars are best spent.
“For every mass media action there is some sort of audience response,” says Roy. “This has always been the case. Because of the low barrier to entry to social media there are feedback loops. Those roll up to a significant new force which shifts how audiences view the mass media.”
Roy is a researcher at the MIT Media Lab and he founded the company in 2008 with one of his Ph.D students, Michael Fleischmann. ver the past 15 years, Roy’s research explored the nexus between video and language. He taught a robot named Toko the names of objects using video and language as complimentary feedback loops, and put his own family under video surveillance to capture how his son learned language over a period of 36 months.
Now with Bluefin, he is taking that deep machine learning and semantic analysis and applying it to TV. Last year, Bluefin raised a $6 million series A financing led by Redpoint Ventures. Other investors in that and a previous seed round include Lerer Ventures, Acadia Woods Ventures, Brian Bedol and Jonathan Kraft. The company has raised a total of $8.35 million, including a $1.15 million grant from the National Science Foundation.
COMMENTARY: Bluefin Lab's television real-time audience analytics technology is quite novel in its approach. Their technology, once all the bugs have been fixed, could easily eliminate focus groups and Nielsen TV ratings reports. TV programmer's will be able to know almost immediately whether a particular TV show has an audience, the size of that audience and what they are saying about that show. Really, really cool. I bet the TV networks, advertising execs and their clients will be drooling over this new technology once Bluefin Lab has completed their pilot program.
Bluefin Lab's website provides an excellent overview of their technology:
WE KNOW DATA
Bluefin Labs' mission is to provide brands, agencies and media companies with precise, real-time audience engagement data by synchronizing social media commentary with television content.
People have always talked about what they watch on television, be it a show, a game, an ad or a news story. Social media now make it possible for them to voice their opinion publicly and frequently. The result is massive volumes of response data spread across multiple social and digital channels—difficult to capture at scale, much less to make sense of.
Bluefin has built a technology platform that ingests these varied streams and syncs this response data with its televised source—real time, at scale and with fine granularity. This data map provides brands with direct insight into how they can modify marketing to drive predictable consumer response. It is an approach based on 15 years of MIT research at the intersection of cognitive psychology and Artificial Intelligence.
Bluefin will debut the first product in market to provide brands and agencies with a turnkey solution for tracking and measuring, at scale, audience engagement on television programming and advertising. The product uses deep machine learning to sift through the world's social media streams to identify and analyze unsolicited comments about TV shows and ads. With this comprehensive, data-grounded measure of audience engagement, brands and agencies can learn in real-time how audiences are responding and what they are saying about their campaigns, along with other ads in market. Based on this measurement, they can use the results to hone their creative, target their audiences with more precision, and better optimize their TV advertising spend.
Bluefin is currently running private pilots with a handful of Fortune 100 companies and agencies, and is expected to be generally available later in 2011.
That's what I call a great mission statement.
Courtesy of an article dated February 1, 2011 appearing in TechCrunch
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