AdTheorent offers polling ad to target ad-campaign based on results

Predictive ad tech provider AdTheorent is now finding its model customers for ad campaigns by inquiring them to raise their hands.

Figuratively, of course.

Its new Audience Builder provides 300 x 250 ad devices to poll users, and the qualities of users who answer one method or another are immediately employed to create plus modify custom models that focus on audiences for the followup ad campaign.

For instance, the Audience Constructor poll might ask viewers: What exactly is your favorite weekend activity? Choices (as in the image on the top of this page) might include: a concert, eating at restaurants, cycle class or roof beverages. Each choice will be used to design a different kind of audience.

“ Opt 4 Optimism” campaign. In the inaugural campaign for Audience Builder, the newest York City-based AdTheorent recently assisted target the digital ads regarding Texas-based Frost Bank’ s “ Opt for Optimism” campaign.

The purpose of the campaign was in order to “ combat cultural pessimism” plus align the bank’ s brand name with positiveness. The polling advertisement asked one of two questions:

  • Do you think optimism can be discovered?
  • Have you donated in order to charity recently?

The bank considered that a “ yes” answer to either question indicated an optimistic individual. Users answering in the yes, identified by cookies or cellular device IDs, were then compared to AdTheorent’ s cross-device graph, including such attributes as the user’ t demographics, psychographics (interests, behaviors), age group, gender and/or marital status.

Building the viewers model. Those characteristics were then fed into device learning to create an audience design with a specific set of features — in this case, a perceived predisposition to get optimism — for targeting whether banner ad or a pre-roll video, mainly on mobile web but also for several in-app ads.

AdTheorent SVP Matthew Groner said that 1 ) 4 percent of viewers from the polling ad responded with an solution. For the question of whether confidence can be learned, he said, there was about 7, 000 answers, which about 5, 000 said indeed via a yes/no slider. For the monetary gift to charity question, there were approximately 6, 800 responses, with around 2, 800 of those in the yes, definitely.

AdTheorent said focused users exhibited an 82 % video completion rate, 9. 3 or more percent above the industry standard. The particular polling ad and the followup ad-campaign ran on properties from high quality publishers, including The Washington Post, Company Insider, Weather. com and The Day-to-day Beast.

A click the banner ad took the user to the “ Opt 4 Confidence ” site, as do a link at the end of the pre-roll movie ad.

Exactly why this matters to marketers. Marketers target digital advertisements through all kinds of inferences about what qualities their target audience shares, but straight asking potential targeted users can make inferences unnecessary.

Research have been used to target audiences just before, but in this case a focused polling ad is immediately given into machine learning to target the particular ad campaign. Like other efforts, AdTheorent’ s Audience Builder is portion of the trend away from guessing what kind of qualities your targeted user has, frist by definitively finding the targeted audience and then instantly building a larger audience from them.

This story premoere appearance on MarTech Today. For more upon marketing technology, click here.


About The Author

Barry Levine covers marketing technology for 3rd Door Media. Previously, he protected this space as a Senior Article writer for VentureBeat, and he has discussed these and other tech subjects designed for such publications as CMSWire plus NewsFactor. He founded and brought the web site/unit at PBS train station Thirteen/WNET; worked as an online Older Producer/writer for Viacom; created a prosperous interactive game, PLAY IT SIMPLY BY EAR: The First CD Game; launched and led an independent film display, CENTER SCREEN, based at Harvard and M. I. T.; plus served over five years like a consultant to the M. I. Capital t. Media Lab. You can find him from LinkedIn, and on Twitter at xBarryLevine.

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