Jochen Hartmann

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Wednesday Seminar: Jochen Hartmann

We invite you to a SOL Seminar with Jochen Hartmann, Professor of Digital Marketing, TUM School of Management. His research is located at the junction of digital marketing and machine learning, with a focus on unstructured data analytics (computer vision, natural language processing) and generative artificial intelligence (AI). Broadly, his substantive research interests include social media, multi-modal digital advertising, algorithmic fairness, diversity in advertising, and human-machine interactions.

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AI in disguise --- AI-generated ads outperform human-made ads if they don't look like AI 

Generative AI’s recent advancements in synthetic content creation have demonstrated significant potential to transform the advertising industry. This research investigates the impact of generative AI-enabled visual ad creation on real-world advertising effectiveness. For this purpose, we exploit a quasi-experimental setting that includes over 2 million ad-day observations from 7,074 advertisers across 49 product categories, encompassing more than 16 billion ad impressions and 116 million clicks. We find that display ads in which the image was AI-generated outperform ads with human-made images in terms of click-through rates, but only if consumers cannot infer that AI generated these images. We identify key image features influencing consumers’ perception of an ad’s artificiality (’looks like AI’). While AI generates more aesthetic images with larger faces, consumers associate these features with human-made ads. In contrast, in line with consumers’ expectations, intense color saturation in ads signals AI generation to consumers. Our findings have important implications for advertising platforms offering AI-powered content creation tools and for advertisers adopting these technologies. 

ABOUT THE SPEAKER

Jochen Hartmann is a Professor of Digital Marketing, TUM School of Management. His research is located at the junction of digital marketing and machine learning, with a focus on unstructured data analytics (computer vision, natural language processing) and generative artificial intelligence (AI). Broadly, his substantive research interests include social media, multi-modal digital advertising, algorithmic fairness, diversity in advertising, and human-machine interactions. His papers on text and image mining belong to the most read and cited papers at top-tier marketing journals, including International Journal of Research in Marketing and Journal of Marketing Research.