Wedel, Michel

Michel Wedel
Pepsico Professor of Consumer Science, Distinguished University Professor
Department of Marketing
Robert H. Smith School of Business
3303 Van Munching Hall
Phone: 
301-405-2162

My research interests involve the application of statistical and econometric methods to address substantive marketing problems, in particular involving perception and attention to commercial visual messages. The availability of commercial eye-tracking data at large scales and high levels of precision has enabled me to incorporate the theories on consumer attention and neuropsychology in statistical models to analyze eye tracking and facial expression data for print ads, TV commercials, shelves, websites and online ads. I have explored attention to feature advertising and its effect on sales,  have developed comprehensive models of consumer search of brands on shelves, and have developed models and metrics for copy cats and gist perception of advertising. I have developed Bayesian statistical models that represent consumer behaviors and psychological mechanisms, and I am particularly interested in research that bridges the quantitative and behavioral areas in marketing often requiring us to address the challenges of big-data analytics.   

General Research Interests: 
  • Eye tracking
  • Visual Marketing
  • Advertising effectiveness 
  • Big data analytics

Research examples

Nodule Detection in Chest X-Rays with Eye Movements

 

Background: 
Education
 
Ph.D., Marketing, University of Wageningen, NL, 1990.
MS. Statistics, Netherlands Society for OR and Statistics, 1986.
MS.C., Biomathematics, University of Leiden, NL, 1981
MS. Business Management, University of Delft, NL, 1980
 
Michel Wedel was named a Distinguished University Professor in July 2015. He holds the PepsiCo Chair in Consumer Science at the Robert H. Smith School of Business at the University of Maryland. His main research interest is in Consumer Science: the application of statistical and econometric methods to further the understanding of consumer behavior and to improve marketing decision making. Much of his recent work has measured the effectiveness of visual marketing using eye-tracking technology. He teaches models for Marketing decision making for MBA students, advanced Marketing analytics for MS students, and Bayesian statistics for Ph.D. students.