AOL Brings Programmatic to TV: How It Works, Why You Should Care

AOL Brings Programmatic to TV: How It Works, Why You Should Care

By: Cesar Brea

Nielsen and Adobe are teaming up to apply TV-style ratings to the internet. But, how do we bring Internet-style tracking and targeting to TV? Though television still accounts for the largest share of advertising budgets, it’s hardly the sine qua non medium it was twenty years ago, or even five. Even mighty TV’s got to be demonstrably effective and efficient today.

Recently, my friend and former boss, AOL Platforms CEO Bob Lord, and his colleagues unveiled “One,” a new data management platform (DMP) to help their advertising clients better target video ads on AOL’s network and beyond.

In the announcement, AOL presented a proprietary metric called the “tRatio.” It tells you what proportion of your ad impressions are reaching what proportion of your target audience, across the media inventory AOL can track through its assets. Applying the tRatio to a pre-One base case, AOL reported that (on average) “85% of video ad impressions reach only 40% of the intended audience.” What’s different now – John Wanamaker fans, take note – is we know which impressions were wasted, and can do something about it.

That’s a pretty big deal, so I thought it would be helpful to explain how AOL’s doing this.

Say you’re an advertiser. You go to AOL to advertise on TV. When you sign up, AOL sticks a tracking tag on your web sites. (They implement this as a “first-party” tag, meaning users’ browsers recognize the tag as yours and not AOL’s, and so fewer browsers block it.)

Now say you’re a potential customer. Your browser visits the advertiser’s site, and requests a page. When the page loads, a little javascript program launches (invoked by AOL’s tracking tag on the page), and rummages around your hard drive for any cookie AOL has previously set there to track you. It checks this cookie against its records of other pages requested by this cookie, or relatable records shared by clients of its Convertro attribution analysis solution. Collectively, this history of your past surfing can tell AOL a lot about who you are, demographically and behaviorally. (Of course AOL can’t act on any specific knowledge of your identity; rather, the firm tightens up its assessment of who you are for later targeting of ads.) More specifically, AOL’s profile of you based on all this data is stored as a record in its DMP, as “anonymous user with record ID ‘Whatever’ has the following characteristics we can use to score him/her for targeting decisions.”

Next, AOL compares this rich (though anonymized) description with a database of viewer descriptions for several hundred thousand individual pieces of video inventory it controls. This includes linear television that AOL, through a partnership with the media buying arm of Publicis, can get ads on. Once it knows which video inventory best fits your profile, it can work to make sure you see the ads that the advertiser would like to show you.

Sometimes this targeting is tighter, for example through pre-roll ads on digital video, and sometimes it’s less tight, either through addressable cable TV advertising (a la services like Visible World), or even just plain “We bought you ad space on show Y because its viewers look more or less like the X profile you’re after.” Presumably when the targeting is looser, the tRatio isn’t quite as favorable, since targeting can be expressed probabilistically.

It’s a pretty audacious vision. It’s got a lot of moving parts to coordinate, at fairly large Big Data scales. There are of course limits on the video inventory available through the platform — NFL games won’t be here anytime soon. There are diminishing returns to incrementally finer-grained targeting, both in terms of reach and in terms of effectiveness. Tracking is tougher, for a variety of reasons, including growing pressures to assure privacy. Plus ultimately good targeting has to be complemented by creative executions that are both strong and cost-effective.

But folks were saying some of the same things about programmatic buying for digital advertising a while back, and now that approach is quickly becoming the dominant way to buy that medium. And if AOL is ultimately going to thrive again, it’s vision like this, delivering meaningful value to its advertisers, that will make that possible. So, I’ll be keeping up with this capability and ones like it, and suggest to advertisers (in particular ones in high-consideration product categories with narrow target customer niches) that they earmark some budget for it, maybe from their direct response TV spending.

Cesar Brea is founding managing partner of Boston-based Force Five Partners, LLC, a marketing and sales analytics consulting firm, and the author of Marketing and Sales Analytics (Pearson FT Press, 2014). He can be reached at


Cesar Brea is author of Marketing & Sales Analytics (Pearson FT Press, July 2014,) and founder and managing partner of Force Five Partners, LLC (, a marketing analytics consulting firm serving leading brands in multiple industries.

With more than 25 years of marketing experience, Cesar has worked as an executive, advisor and entrepreneur across nearly two dozen industries. Prior to starting Force Five Partners in 2008, he headed the digital media and marketing practice at The Monitor Group; led sales and marketing at Razorfish (the world’s leading digital advertising agency); helped build two Internet software start-ups (ArsDigita Corporation and Contact Networks); and led engagements with high-tech clients for Bain & Company.

A frequent writer on marketing and analytics strategy, he published his first book, Pragmalytics: Practical Approaches to Marketing Analytics in the Digital Age, in 2013 and blogs at


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