New MediaPET-powered methodology allows researchers to perfectly recreate advertisements using AI, enabling precise measurement of every creative element.
MediaScience announced a major breakthrough in advertising research with its latest feature, “Creative Twin.” The company, known for its work as a global leader in media and advertising innovation, has developed a new AI-powered methodology that enables researchers to perfectly recreate advertisements and test the impact of every individual creative element within them.
The announcement will be presented today at the Advertising Research Foundation’s (ARF) Audience x Science annual conference by founder and CEO, Duane Varan.
Developed using proprietary software within MediaPET.ai, a MediaScience spinoff, the innovation allows MediaScience to generate AI-based replicas of existing advertisements that are indistinguishable from the original creative.
In controlled testing with 812 respondents in the United States, conducted in collaboration with the Ehrenberg-Bass Institute, one of the world’s leading marketing science academic research centers, audiences were unable to differentiate between the original advertisement and the AI-generated version. Once an ad has been recreated in this format, every component within it can then be systematically modified to measure its precise impact on audience response.
The “Creative Twin” opens the door to testing variables that were previously difficult or prohibitively expensive to isolate.
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By digitally manipulating every element of a video ad, for example, the platform allows marketers to test identical executions with different celebrities —or with none at all—revealing the precise brand fit and incremental value each talent delivers.
The technology also enables creative optimization at scale for addressable advertising. Instead of spreading budgets across multiple executions, brands can produce one high-quality ad and digitally adapt it for different audiences—for example, replacing a straight—haired model in a shampoo commercial with the same model now with curly hair (targeted to women who style their hair curly) —delivering personalized creative without compromising production value.
In the case of shampoo, for example, women with curly hair were exposed either to the original ad, which featured a model with straight hair, or an AI-modified version of the same model with curly hair. The curly hair AI version significantly outperformed the original straight-haired version, delivering higher brand recognition, brand attitude and brand choice (indicative of purchase likelihood).
“This represents a fundamental shift in how advertising creative can be evaluated and optimized,” said Duane Varan, CEO of MediaScience and MediaPET. “For the first time, researchers can isolate and measure the contribution of individual creative elements within an advertisement, providing marketers with unprecedented clarity about what truly drives effectiveness. And they can now properly optimize and personalize ads without compromising on production quality.”
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Other examples include:
A premium puppy food commercial featuring a Labrador can be modified to feature a poodle or French bulldog and delivered to owners of those specific breeds.
A coffee ad can explore what the relative contribution of a particular celebrity is. Would an alternative celebrity boost ad impact? Would a generic model deliver similar results?
In each case, the modified advertisement retains the full production quality of the original creative.
The methodology not only supports optimization of advertising creative but also enables precise measurement of the economic value of individual creative decisions, including casting, visuals, messaging, and other production choices.
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