Remi Daviet is an Associate Professor of Marketing at INSEAD. He completed a PhD in Economics from the University of Toronto, specializing in Bayesian econometrics and decision modelling. Prior to joining INSEAD, Remi Daviet was a faculty member at the Wisconsin School of Business and served as a Post-Doctoral Fellow at The Wharton School of the University of Pennsylvania, where he also taught MBA courses.
Remi Daviet studies how emerging technologies and biological data sources disrupt traditional marketing practices to improve decision-making and advance behavioural theory. His research is concentrated in two primary streams: the use of artificial intelligence and machine learning to create value from data and rethink current marketing practices; and the application of consumer biology, including genomics, neuroscience, and physiology, to understand and predict consumer behaviour. His work has been published in leading marketing journals (Journal of Marketing and Journal of Marketing Research) as well as in prominent interdisciplinary and science journals (Nature Communications and Nature Human Behaviour).
A specialist in AI-driven insights, Remi Daviet’s current research focuses on optimizing visual and textual information, such as advertising design, retail spaces, and product packaging, through generative AI and deep learning. His work in consumer biology has pioneered the use of genetic foundations for food preferences and the application of epigenetic "biological age" as a novel variable for market segmentation. A global citizen who has lived and worked across four continents, he maintains active research collaborations with major industry partners across Europe, North America, and Asia, including national media organizations and global publishers.
At INSEAD, Remi Daviet developed a curriculum designed to help students leverage the power of artificial intelligence to bring marketing into a new age. His courses cover the end-to-end integration of AI in business processes, from the innovation stage and product development to the optimization and automation of advertising campaigns. He is a dedicated educator who emphasizes the development of intuition and interest in modern computational methods, ensuring future leaders can effectively bridge the gap between complex data science and strategic marketing execution.
