New Data for Consumer Insights Conference
Save the Date: June 11 - 12, 2027
Paper Submissions: Coming soon
Conference Co-chairs:
Giovanni Compiani, Associate Professor of Marketing, Chicago Booth
Thomas Wiemann, Assistant Professor of Marketing and Beatrice Foods Co. Faculty Scholar, Chicago Booth
Estimating consumer preferences is a key building block of many empirical analyses in marketing and economics, including pricing, merger policy, product design and branding.
Standard approaches focus on one product category at a time and model demand as a function of a few marketing mix variables and product attributes. Recently, new sources of data have become available, including:
• Unstructured data (e.g., texts, images and videos)
• Big data (e.g., data from a large number of possibly interrelated product categories)
• Clickstream data (e.g., search sessions on e-commerce platforms)
• Data produced by generative AI (e.g., ChatGPT)
• Novel survey data
The conference aims to bring together scholars in marketing, economics and statistics/AI/ML who use Machine Learning, NLP, and other tools to extract valuable insights from new types of data. We hope the conference can serve as a bridge between different fields. Extended abstracts and full papers are welcome for both methodological and empirical submissions.
In addition to contributed sessions, the conference will feature keynote lectures by Aviv Nevo and Guy Arie.
Programming:
Friday, June 11, 2027 12:00 - 9:00 p.m. CT | Chicago Booth, Gleacher Center
Saturday, June 12, 2027 9:00 a.m. - 5:00 p.m. CT | Chicago Booth, Gleacher Center