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Marketing

Charles H. Kellstadt Chair in Marketing

Professor of Marketing

Portrait of Brett Gordon, Faculty at the Kellogg School of Management

Brett R. Gordon is the Charles H. Kellstadt Professor of Marketing at Kellogg School of Management. His research interests are in pricing, advertising, experimentation, promotion, retailing, and competitive strategy. Professor Gordon studies these topics by drawing on methods from empirical industrial organization, econometrics, and machine learning. His articles have appeared in scholarly journals such as American Economic Review, Journal of Political Economy, Marketing Science, Journal of Marketing ResearchQuantitative Marketing and Economics, and Journal of Marketing. He is a three-time winner of the John D. C. Little Award at Marketing Science for best paper and was a Finalist for a fourth article. One paper won the Robert D. Buzzell Best Paper Award from the Marketing Science Institute for its contributions to marketing practice and another paper was twice a Finalist for the Long-Term Impact Award at Marketing Science. A fifth paper was a Runner-Up for the Dick Wittink Prize for the best paper published at Quantitative Marketing and Economics. In April 2023, Professor Gordon was appointed a Co-Editor at the Journal of Marketing Research. Previously, he served as an Associate Editor at Management Science and the Journal of Marketing Research and on the Editorial Boards of Marketing Science and Quantitative Marketing and Economics.

He is a co-founder of the podcast, "How I Wrote This," which interviews authors of great marketing papers to demistify how those papers came to be. Listen on Apple, Spotify, or wherever you get your favorite podcasts. He also co-founded the Quantitative Marketing and Structural Econometrics Workshop, which ran from 2010 to 2019, helping to educate graduate students on state-of-the-art empirical techniques.

At Kellogg, he teaches the MBA course on Retail Analytics and Pricing and a Ph.D. course on Structural Models for Quantitative Marketing.

Previously, he was the Class of 1967 Associate Professor of Business at Columbia Business School, which he joined in 2007. He has held visiting positions at University of Chicago's Booth School of Business and at Stanford GSB. He earned both his Ph.D. in Economics and Masters in Information Systems from Carnegie Mellon University.

About Brett
Research interests
  • Pricing
  • advertising
  • digital marketing
  • promotions
  • innovation
  • new products
  • marketing analytics
  • causal inference
  • empirical industrial organization
  • and technology markets
Teaching interests
  • Retail Analytics and Pricing
  • Ph.D, 2007, Economics, Carnegie Mellon University
    M.S., 2004, Economics, Carnegie Mellon University
    Masters, 2002, Information Systems Management, Carnegie Mellon University
    B.S. (Honors), 2002, Information Systems and Economics, Carnegie Mellon University
  • Professor of Marketing, Northwestern University, Kellogg School of Management, 2021-present
    Visiting Scholar, Marketing, Graduate School of Business, Stanford University, 2017-2018
    Associate Professor (with tenure), Marketing, Kellogg School of Management, Northwestern University, 2014-2021
    Visiting Associate Professor, Marketing, Booth School of Business, University of Chicago, 2013
    Visiting Scholar, Graduate School of Business, Stanford University, 2012
    Class of 1967 Associate Professor, Business, Columbia Business School, Columbia University, 2011-2014
    Associate Professor, Business, Columbia Business School, Columbia University, 2011
    Assistant Professor, Business, Columbia Business School, Columbia University, 2007-2011
  • Ned Smith Research Mentorship Award
    Sidney J. Levy Teaching Award
    Winner, Robert D. Buzzell Best Paper, Marketing Science Institute (MSI), 2020
    Winner, John D.C. Little Best Paper Award, INFORMS Society for Marketing Science, 2019
    Finalist, Long-Term Impact Award, INFORMS Society for Marketing Science
    Scholar, Marketing Science Institute (MSI), 2018
    Finalist, Long-Term Impact Award, INFORMS Society for Marketing Science, 2017
    Honorable Mention, Dick Wittink Prize, Quantitative Marketing and Economics journal
    Doctoral Consortium Presenter, INFORMS Society for Marketing Science
    Doctoral Consortium Presenter, INFORMS Society for Marketing Science
    Doctoral Consortium Presenter, INFORMS Society for Marketing Science
    Finalist, John D.C. Little Best Paper Award, INFORMS Society for Marketing Science
    Distinguished Service Award, Management Science, 2013
    Doctoral Consortium Presenter, INFORMS Society for Marketing Science
    Young Scholar, Marketing Science Institute, 2013
    Meritorious Service Award, Management Science, 2010
    Finalist, Frank M. Bass Dissertation Paper Award, INFORMS Society for Marketing Science, 2009
    Winner, John D.C. Little Award for Best Paper, INFORMS Society for Marketing Science
    Dissertation Award, Center for Analytical Research in Technology (CART), 2006
    Dissertation Competition Award, MSI Alden G. Clayton, 2006
    Best Ph.D. Student Teacher Award, Carnegie Mellon University, 2004
    Graduate Student Research Grant, Carnegie Mellon University, 2004
    William Larimer Mellon Fellowship, Carnegie Mellon University, 2002-2005
  • Co-Editor, Journal of Marketing Research, 2023
    Associate Editor, Journal of Marketing Research, 2022-2023
    Associate Editor, Management Science, 2021-2023
    Editorial Board, Journal of Marketing Research, 2016-2021
    Editorial Board, Quantitative Marketing and Economics, 2014
    Editorial Board, Marketing Science, 2014-2023
    Editorial Board, International Journal of Research in Marketing, 2012-2015

Research (MKTG-590-0)

Independent investigation of selected problems pertaining to thesis or dissertation. May be repeated for credit.

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: Structural Modeling (MKTG-551-3)

This course provides a foundational understanding of static and dynamic discrete-choice models, with applications drawn from quantitative marketing and economics. The course takes a "hands on" approach to research, with class being a mix of lectures, discussion of articles, and hands-on empirical analysis. Coding assignments are the bulk of the grade.