Filtering Out The Noise

Search has often, and deservedly, been praised as the gold standard of online ad efficiency, the central repository of the world's "database of intentions." Yet the fact remains that most of the best intention-signaling consumer behavior occurs outside the search context.

The pursuit of getting at this behavioral data, and doing it at scale, has been the holy grail of behavioral marketing for some time. While both data and scale, in isolation, are available online in abundance, synergy between the two -- that is, high-quality-intent-based data with scale -- has proven elusive. The question is how to distill rich, truly intent-based behavior from more generic behavioral data.

It's this challenge ad network Adconion and intent-based data exchange BlueKai have taken on in a new partnership, by fusing data from Adconion's site network, which reaches 142 million U.S. unique users, and BlueKai's database of over 100 million buyer attributes in categories including travel, automotive and retail.



The value-add for advertisers of this "next-generation targeting tool," is that, using the fused data, Adconion can identify for specific advertisers which BlueKai users are interested in or have purchased their products, even if the advertiser is not currently targeting that type of user, according to Ben Fox, vice president of product management at Adconion.

"We're focused on culling true intent data -- the signal -- and differentiating it from all the noise," explains Fox. "To aggregate data, that is, so that it is as much a database of intentions as search, using data from actual shopping transactions and customer forms."

" For example," he says, " if you are trying to reach travelers, you might have some idea of your target going in, but to be able to drill down to reach travelers by their city of origination or destination, length of stay, hotel bookings or car rentals by city, to name a few, is an entirely new level of detail."

"A lot of times," he continues," advertisers say, 'I think this is my demographic, and this is my behavioral segment.' But we take a campaign and find out that the areas where the campaign actually performs completely surprise them compared to their expectations. Now we have the ability to show which segments are working and to do something about it quickly by shifting resources in real-time, not after the fact."

A further highly interesting new level of insight that opens up for advertisers exploring intent-based data, according to Fox, is that by comparing their target segments against known intent data, advertisers can form much more educated hypotheses about optimal offers even before they begin advertising the product.

" We can now begin the campaign at the planning level with specific suggestions," he says, "and then, as the campaign gets under way, be testing those hypotheses in real-time and constantly updating and refining those suggestions based on how consumers are actually responding. We can be running a campaign and testing four or five versions of a creative against specific segments."

The partnership, though still in its early stages, augurs a wider industrywide shift, , a shift from having targeting drive data to data driving targeting, Omar Tawakol, CEO at BlueKai, believes.

"In the drive to optimize," Tawakol says, " advertisers have been overwhelmed with an embarrassment of riches, tweaking their choice of sites to target, placements, frequency, time of day and ad creative. The problem is there's so much noise generated by the variables associated with the ad that it has been hard to make sense of the data that drives the targeting. The performance of the targeting data tends to be an after-thought."

The payoff, Fox and Tawakol believe, is the achievement of a new benchmark for scale, one that, potentially at least, will enables advertisers to see both the forest and the trees.

"Behavioral targeting before was struggling with scaling," Tawakol says. "A central problem was that there was a surfeit of data but a scarcity of quality-rich data, the kind from which you can build intent-based, as opposed to more generic, browsing-based, segments. That creates for the first time the opportunity of breaking free from that cul de sac. Crossing that threshold," he adds, "could represent a big step toward bringing the power of search to banner display advertising."

1 comment about "Filtering Out The Noise".
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  1. Mike John-baptiste from Peerset, April 2, 2009 at 4:19 p.m.

    I like the partnership thesis. There will still be debate in the consumer privacy advocacy community as to whether or not the nature of the information gather (i.e. tracking people) is acceptable but certainly online advertising is better off if that threat is minimized.

    There is still a missing piece for the advertiser in my view. Behavioral targeting is wonderful but as mentioned without scale you're doing a disservice to the advertiser by narrowing the scope of the campaign.

    Peerset,, a company I acknowledge I work for, is focused on collecting anonymous human interest data (psychographics) and the system can make predict related interests based on stated intentions and interests. It's an important data layer that is different and/or supplemental to behavioral indicators. - JB

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