Brett R. Gordon joined Kellogg in 2014 as an Associate Professor of Marketing. His research interests include pricing, advertising, promotions, retailing, innovation, and competitive strategy. Professor Gordon studies these topics by drawing on methods from empirical industrial organization, econometrics, and statistics. His articles have appeared in scholarly journals such as American Economic Review, Journal of Political Economy, Marketing Science, Journal of Marketing Research, and Quantitative Marketing and Economics. His paper on replacement cycles in the PC processor market received the John D.C. Little Award in 2009 for the best paper appearing in Management Science or Marketing Science. Another paper published in 2013 on advertising effects in presidential elections was also nominated for this award.

Professor Gordon is actively involved in the academic field. He serves as an Associate Editor for Quantitative Marketing and Economics and as an Editorial Board member for Marketing Science and the International Journal of Research in Marketing. He is a co-founder of the Quantitative Marketing and Structural Econometrics Workshop, which helps educate graduate students on state-of-the-art empirical techniques.

Previously, he was the Class of 1967 Associate Professor of Business at Columbia Business School, which he joined in 2007. He earned both his Ph.D. in Economics and Masters in Information Systems from Carnegie Mellon University. At Kellogg he teaches the MBA course on Retail Analytics and a Ph.D. course on Structural Models for Quantitative Marketing.

Quantitative Marketing, Empirical Industrial Organization, Pricing, Advertising, Innovation, Online Marketing, Dynamic Oligopoly, Retail.

• 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

• Visiting Scholar, Marketing, Graduate School of Business, Stanford University, 2017-2018
• Associate Professor (with tenure), Marketing, Kellogg School of Management, Northwestern University, 2014-present
• Visiting Associate Professor, Marketing, Booth School of Business, University of Chicago, 2013-2013
• Visiting Scholar, Graduate School of Business, Stanford University, 2012-2012
• Class of 1967 Associate Professor, Business, Columbia Business School, Columbia University, 2011-2014
• Associate Professor, Business, Columbia Business School, Columbia University, 2011-2011
• Assistant Professor, Business, Columbia Business School, Columbia University, 2007-2011

• Scholar, Marketing Science Institute (MSI), 2018
• INFORMS Long-Term Impact Award (Finalist), 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
• John D.C. Little Award for Best Paper, INFORMS Society for Marketing Science, 2009
• 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

• Editorial Board, Journal of Marketing Research, 2016
• Associate Editor, Quantitative Marketing and Economics, 2014-Present
• Editorial Board, Marketing Science, 2014-Present
• Editorial Board, International Journal of Research in Marketing, 2012-Present

Retail Analytics

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.

Strategic Marketing Communications

Explore the power of an integrated marketing communications strategy from fundamental planning to tactical execution utilizing the most current thinking about media channels, customer engagement and measurement. The frameworks and examples provided are applicable to developing both B2C and B2B marketing communications strategies.

Field Study (MKTG-498-0)
Field Studies include those opportunities outside of the regular curriculum in which a student is working with an outside company or non-profit organization to address a real-world business challenge for course credit under the oversight of a faculty member.

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.