Every day, somewhere in the cloud, Bluefin Labs of Cambridge. MA, is analyzing 200 channels of US television broadcasts around the clock. That’s something like an unfathomable 172 terabytes of raw video data (and a goodly bit of drivel one might add). The company then collects programming information including channels, broadcast schedules, and keywords to tag each show and ad. For each group of ads, Bluefin workers make the initial product identification and then their analytics system automatically identifies repeat airings.
But that’s not all: Bluefin additionally monitors 300 million public social-media comments per day for the keywords associated with programs and ads. Out of that huge number there are on average about 10 million comments about TV content. About 1.4 million of those are made in what Bluefin considers the relevant context for a particular show or advertisement, which is about three hours before to three hours after the actual broadcast. These comments pop up primarily in tweets but there are also public Facebook posts and some other media sites. The company also tracks the online activity of the 9.8 million people who have made online comments about television in the last 90 days.
What does all this add up to (no pun intended)? Based on research originally begun at the prestigious MIT Media Lab, Bluefin Labs is building a business out of creating a context in which television advertisers can understand which ads have more success so that they can make better decisions about where to place their ads in the future. Television producers can also tap into viewers responses and modify content to better please and perhaps increase their audiences.
The effort to better understand audience responses through analyses of social media is still in its infancy. Target marketing is the new Holy Grail for marketing executives. And what Bluefin has been able to accomplish is in some ways impressive. It has created a context that shows how the same viewers might respond to different ads when watching different shows. It ultimately provides two measurements as well. The first is “response level,” which counts the number of people commenting on any given show or ad. The second is “ response share,” which indicates the percentage of all responses that a single show or ad has garnered. The company is already attracting some large corporate clients, such as Pepsico, CBS, Comcast, Fox Sports, and Turner Broadcasting, writes David Talbot in the recent print issue of Technology Review.
That’s a remarkable list and it indicates just how important analytics is becoming for broadcasters and manufacturers.TV advertising is big business, after all. It dictates the success or failure of TV broadcasting because companies spend $72 billion annually these days on TV advertising. And Americans watch a lot of television. According to the Nielson Corporation they spend 20% of their waking hours watching television, some of them multitasking by using their laptops or smartphones at the same time.
Still there are some reasons to be skeptical. For one, as Hill Holiday advertising executive Mike Proulx points out, the connection between social media reaction and the impact of content is still just a theory. There’s no solid evidence to date that proves it is a valid connection. Another major drawback, it seems to me, is that people who actively tweet or post comments on Facebook or elsewhere about television programs are only a subset of the couch potato population, no doubt skewing younger for one thing. What’s more, it’s also becoming more and more common for people to record television shows and watch them at random times, making the correlation between the three hours before and after a broadcast irrelevant for many viewers these days.
So it remains to be seen if all the effort and advanced expertise that is being poured into advertising analytics and social media will generate better advertising, or whether corporations will still be saying ten years from now what the merchant John Wanamaker said over ninety years ago: “Half of the money I spend on advertising is wasted; the problem is I don’t know which half.”
But that’s not all: Bluefin additionally monitors 300 million public social-media comments per day for the keywords associated with programs and ads. Out of that huge number there are on average about 10 million comments about TV content. About 1.4 million of those are made in what Bluefin considers the relevant context for a particular show or advertisement, which is about three hours before to three hours after the actual broadcast. These comments pop up primarily in tweets but there are also public Facebook posts and some other media sites. The company also tracks the online activity of the 9.8 million people who have made online comments about television in the last 90 days.
What does all this add up to (no pun intended)? Based on research originally begun at the prestigious MIT Media Lab, Bluefin Labs is building a business out of creating a context in which television advertisers can understand which ads have more success so that they can make better decisions about where to place their ads in the future. Television producers can also tap into viewers responses and modify content to better please and perhaps increase their audiences.
The effort to better understand audience responses through analyses of social media is still in its infancy. Target marketing is the new Holy Grail for marketing executives. And what Bluefin has been able to accomplish is in some ways impressive. It has created a context that shows how the same viewers might respond to different ads when watching different shows. It ultimately provides two measurements as well. The first is “response level,” which counts the number of people commenting on any given show or ad. The second is “ response share,” which indicates the percentage of all responses that a single show or ad has garnered. The company is already attracting some large corporate clients, such as Pepsico, CBS, Comcast, Fox Sports, and Turner Broadcasting, writes David Talbot in the recent print issue of Technology Review.
That’s a remarkable list and it indicates just how important analytics is becoming for broadcasters and manufacturers.TV advertising is big business, after all. It dictates the success or failure of TV broadcasting because companies spend $72 billion annually these days on TV advertising. And Americans watch a lot of television. According to the Nielson Corporation they spend 20% of their waking hours watching television, some of them multitasking by using their laptops or smartphones at the same time.
Still there are some reasons to be skeptical. For one, as Hill Holiday advertising executive Mike Proulx points out, the connection between social media reaction and the impact of content is still just a theory. There’s no solid evidence to date that proves it is a valid connection. Another major drawback, it seems to me, is that people who actively tweet or post comments on Facebook or elsewhere about television programs are only a subset of the couch potato population, no doubt skewing younger for one thing. What’s more, it’s also becoming more and more common for people to record television shows and watch them at random times, making the correlation between the three hours before and after a broadcast irrelevant for many viewers these days.
So it remains to be seen if all the effort and advanced expertise that is being poured into advertising analytics and social media will generate better advertising, or whether corporations will still be saying ten years from now what the merchant John Wanamaker said over ninety years ago: “Half of the money I spend on advertising is wasted; the problem is I don’t know which half.”
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