March 4, 2025 | 12:00 - 12:30 pm, ET 

Webinars

MSI Webinar: Contextual Advertising with Theory-Informed Machine Learning

Contextual advertising works by aligning ads with the media environment they appear in. Our research introduces a framework for identifying key ad and context features, using machine learning to predict ad and brand attention.

We leverage a Multimodal Large Language Model to analyze high-level topics and an XGBoost model for prediction, trained on eye-tracking data from 3,531 digital ads.
Our findings show that both XGBoost and ResNet50 accurately predict attention, with ResNet50 excelling in ad-focused attention and XGBoost leading in brand attention. Notably, for new, unseen ads, our theory-driven XGBoost model outperforms ResNet50, offering a more reliable approach for contextual ad targeting. Shapley values highlight which ad and context features drive engagement, reinforcing the power of AI-driven, theory-backed advertising strategies.

 

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speakers

Jianping Ye

University of Maryland, College Park

Jianping Ye is a third-year PhD student of Department of Math at University of Maryland, College Park, advised by Professor Michel Wedel. His research focuses on applications of machine learning on eye-tracking data for more effective marketing and advertising strategies.

Michel Wedel

University of Maryland, College Park

Michel Wedel is the PepsiCo Professors of Consumer Science and a Distinguished University Professor at the Robert H. Smith School of Business at the University of Maryland.

Rik Peters

Tilburg University

Rik Pieters is eminent research scholar at Tilburg University (NL) and Research Professor at Catolica University, Lisbon. He holds a PhD in psychology from the University of Leiden. He has been strategy director at the FCB.Publicis Ad agency, Amsterdam office, with among his clients ABN AMRO bank, Philips, Min. of the Environment. When not working, he doesn’t, which is rare.

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