Anna Tuchman
Anna Tuchman joined the marketing faculty at the Kellogg School of Management in 2016. Professor Tuchman's research interests include the study of advertising and its underlying mechanisms, as well as questions that lie at the intersection of public policy and marketing. Her policy-related work evaluates the effects of e-cigarette advertising on demand for traditional cigarettes, studies how consumers respond to soda taxes, and assesses the prevalence of gender-based segmentation and price discrimination in the consumer packaged goods (CPG) industry. Her work on advertising focuses on measuring advertising effectiveness in both the TV and digital spaces and on understanding the underlying mechanisms through which advertising affects consumer behavior.
Professor Tuchman holds a PhD in Marketing and an MA in Economics from Stanford University. She completed her BA at the University of Pennsylvania. Before her graduate studies, she worked in economic litigation consulting at Cornerstone Research.
- Quantitative Marketing Empirical Industrial OrganizationAdvertising: Digital and TV Advertising
- Mechanisms
- Addictive Goods
- Addressable TV Markets
- Ad Skipping PricingPolicy and Regulation
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Doctor of Philosophy, 2016, Marketing, Stanford University
Master of Arts, 2016, Economics, Stanford University
Bachelor of Arts, 2009, Economics, Mathematics, And Hispanic Studies, University of Pennsylvania -
Associate Professor, Marketing, Kellogg School of Management, Northwestern University, 2020-present
Assistant Professor, Marketing, Kellogg School of Management, Northwestern University, 2016-2020 -
Intern, CIGNA International, 2008
Analyst, Cornerstone Research, 2009-2011 -
Erin Anderson Award for an Emerging Female Mentor and Scholar, American Marketing Association
MSI Young Scholar
Distinguished Winner of the AMA-EBSCO-RRBM Award for Responsible Research in Marketing, American Marketing Association
Finalist, Paul E. Green Award
Winner, Frank M. Bass Dissertation Paper Award, INFORMS Society for Marketing Science
Finalist, John D.C. Little Award for the Best Paper Published in Marketing Science in 2019, INFORMS Society for Marketing Science
Sidney J. Levy Teaching Award -
Associate Editor, Management Science, 2023
Associate Editor, Marketing Science, 2024
Editorial Board, Journal of Marketing Research, 2021
Associate Editor, Quantitative Marketing and Economics, 2024
Topics in Quantitative Marketing (MKTG-552-0)
This seminar required of 2nd-4th year students exposes students to working papers in current areas of active research. Students read, present, and discuss recent papers with the goal of improving their ability to evaluate a paper's academic contribution and managerial relevance and to further extend their knowledge of models and methods.
Quantitative Marketing: Introduction to Theory and Empirical Methods (MKTG-551-1)
This survey course introduces students to substantive and methodological issues in quantitative marketing. We cover ~6 weeks of material on substantive issues such as pricing, advertising, peer effects, and word of mouth. We also cover ~4 weeks of material on methods of causal inference. The readings are multidisciplinary and include topics from marketing, psychology, microeconomics, operations management, and macroeconomics
Retail Analytics and Pricing (MKTG-462-0)
This course will teach you how to use analytics and data to address decisions faced by retailers and manufacturers. Pricing and promotion decisions are emphasized, with additional coverage on topics such as private labels, product assortment, trade funding, shopper marketing, and more. The course is organized around a hierarchy of topics. We spend roughly one week understanding pricing and promoting to an individual customer. This analysis provides the foundation as we move to more aggregate decisions, such as setting regular and promoted prices at the product level, managing category pricing, and understanding the drivers of store traffic. As we progress through this hierarchy of decisions, we illustrate how different types of data can---or can't---be used to answer managerial questions. A key part of the class is understanding the limitations of different types of data and how better planning can both simplify the analytics and increase your confidence in the findings. This class is very practical and hands-on. Most of the data we analyze is from real-world managerial problems, through collaborations with leading retailers and consulting firms who have brought problem-driven challenges to the classroom. Weekly homework assignments, both individual and group, are paired with in-class cases. There is no final exam.
