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Who’s Most Engaged With Liquor Ads? Answers May Surprise You

Who’s Most Engaged With Liquor Ads? Answers May Surprise You


Source: Media Post

by Felicia Greiff

December 28th


If you assume the engaged beer, wine and spirits audience is young and male (the many ads playing during televised sports games might lead to that assumption), prepare to be surprised. An AdTheorent Q3 study found the following key attributes among the most engaged consumer segments within this vertical:


Segment 1 (195% higher engagement compared to industry average): Couples with an average household income of $150,000 or more, ages 51-65, who live in metropolitan markets and have taken a cruise vacation within the last three years. AdTheorent CEO Anthony Iacovone said the age skewed higher than the company’s team would have guessed. “We would’ve said 35-44. But the machine doesn’t lie.”


Segment 2 (179% higher engagement compared to industry average): Mothers who are electronics early adopters, health and fitness enthusiasts and theme park visitors.


Other key takeaways include:


    Rich media drove strong ad engagement in Q3 — 76% higher than the industry average. Secondary ad engagement within rich media units was 362% higher than the industry average.

    Apps outperformed mobile Web by 37%.

    Photo/Video apps delivered 431% higher engagement than entertainment apps.

    Females slightly outperformed males, delivering a 12% higher engagement rate.

    Social apps outperformed sports apps by 203%. “The surprise was we didn’t find those audiences engaging at scale in sports,” Iacovone said. “When you think of wine, spirits, beer ads you’d think sports. But we actually see the reverse. Sports isn’t driving the needle like others.”


Each quarter, AdTheorent uses its tech to aggregate impressions across a specific vertical and sift through the data for insights.


“In machine learning, you let the system find the segment for you,” said Iacovone. After a campaign’s first week, the system collects ad interactions in real-time. After about 100 conversions, a predictive model is deployed. The tech writes a script specifying which characteristics to look for, and the more the model is used, the more it hones in on the top-performing audience.


“At the end of the day, the system removes any sort of bias or assumption,” said Jason Han, AdTheorent’s senior director of data and analytics. “It allows the data to speak for itself.”