• Contact Info

Ahn, Gwen

Assistant Professor



research overview

  • My research focuses on how firms can use individual longitudinal choice data to increase engagement, usage, and spending in experiential categories. The importance of experiential consumption among the consumer base is growing, along with its economic significance: 74% of Americans claim to prioritize experiences over ownership of material goods, and they spend billions of dollars in these categories, e.g., over $55B on sports events alone in the U.S. in 2017. My current projects span two broad experiential domains: live events (art performances and professional sports) and charitable donation. In close collaboration with industry partners, I study how to leverage past trajectories of consumer choices to optimize marketing activities, including product recommendation, price and inventory management, and donation solicitation. In these projects, I use both observational and field experiment data, and a range of estimation methodologies, primarily hierarchical and nonparametric Bayesian, and increasingly tools from machine learning.


  • Bayesian Econometrics, Discrete Choice Models, Customer Analytics and Management, Prosocial Behavior, Experiential Consumption, Machine Learning


courses taught

  • MSBX 5310 - Customer Analytics
    Primary Instructor - Spring 2024
    Provides a deep understanding of customer centricity and its implications for the firm; state-of-the art methods for calculating customer lifetime value and customer equity; analytical and empirical skills that are needed to judge the appropriateness, performance, and value of different statistical techniques that can be used to address a issue around customer acquisition, development, and retention. Students will use their knowledge of R programming in this course.


International Activities