Eric T. Anderson is the Polk Bros. Chair in Retailing, Professor of Marketing and former Chair of the Marketing Department at Northwestern University, Kellogg School of Management and Director of the Kellogg-McCormick MBAi Program.  He holds a Ph.D. in Management Science from MIT Sloan School of Management and previously held appointments at the University of Chicago Booth School of Business and the W.E. Simon Graduate School of Business at the University of Rochester. 

Professor Anderson's research interests include analytics, AI/ML, customer loyalty, retailing, pricing strategy, innovation and channel management.  His recent research has been conducted with various companies around the world and has impacted both management practice and academic theory.  His articles have appeared in scholarly journals such as Journal of Marketing Research, Marketing Science, Management Science, Journal of Economic Theory, and Quarterly Journal of Economics.  He has also published three articles in Harvard Business Review and an article in Sloan Management Review.  His 2004 paper on the long-run impact of pricing and promotions was recently recognized for its enduring impact on the field of marketing.  His 2014 paper on deceptive product reviews won the Paul E. Green award for the best paper in Journal of Marketing Research.

Professor Anderson is currently marketing department editor of Management Science.

At Kellogg, Professor Anderson teaches Pricing and Retail Analytics in the MBA program and Marketing Analytics in the EMBA program. He is a four-time winner of the Sydney Levy Award for best elective at Kellogg.  Professor Anderson also serves on the Board of Directors for Canadian Tire and is an advisor for LiftLab.

Analytics and AI, pricing strategies, channel management, new products

• PhD, 1995, Marketing, Massachusetts Institute of Technology
• MS, 1989, Engineering-Economic Systems, Stanford University
• BS, 1988, Electrical Engineering, Northwestern University, Highest Honors

• Department Chair, Marketing, Kellogg School of Management, Northwestern University, 2013-present
• Professor, Marketing, Kellogg School of Management, Northwestern University, 2009-present
• PhD Program Coordinator, Marketing, Kellogg Graduate School of Business, Northwestern University, 2007-2010
• Hartmarx Research Professorship, Kellogg School of Management, Northwestern University, 2007-present
• Associate Professor, Marketing, Kellogg School of Management, Northwestern University, 2004-2009
• Visiting Assistant Professor, Marketing, Kellogg School of Management, Northwestern University, 2003-2004
• Assistant Professor of Marketing, Graduate School of Business, University of Chicago, 1997-2003
• Assistant Professor, Marketing, William E. Simon Graduate School of Business, University of Rochester, 1995-1997

• Sydney J. Levy Teaching Award, Kellog School of Management
• Weitz-Winer-O’Dell Award for “Harbingers of Failure”, Vol. 52, No. 5, October 2015 Recognizes an article in the Journal of Marketing Research that has made the most significant long-term contribution to marketing theory, methodology, and/or practice., American Marketing Association
• Sidney J. Levy Award for Excellence in Teaching, Kellogg School of Management
• Long Term Contribution (Naresh Malhotra Award), Review of Marketing Research
• Paul E. Green Award, American Marketing Association, Awarded Summer 2015
• Sidney J. Levy Teaching Award, Kellogg School of Management
• Sidney J. Levy Teaching Award, Kellogg School of Management, 2009-2010
• Nominated for Clarence Ver Steeg Graduate Faculty Award, Northwestern University, 2006
• Nominated for John D.C Little Best paper Award, INFORMS, 2004
• MSI Young Scholar, Marketing Science Institute, 2001

• Department Editor, Management Science, 2014
• Associate Editor, Operations Research, 2012-2018
• Editorial Board Member, Journal of Marketing, 2011-
• Editorial Board, Journal of Marketing Research, 2009-Present
• Associate Editor, Management Science, 2009-2014
• Editorial Board Member, Marketing Science, 2008
• Ad-hoc Reviewer, International Journal of Marketing Research, 2000

Retail Analytics, Pricing Strategy and Tactics, Channel Management, Launching New Products

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

Business Marketing Strategy

If your business is B2B, here is a rare opportunity to learn from the experts how to deepen your understanding of marketing dynamics and drive profitable growth in the new B2B environment.

Customer Insight Tools

Harness the power of customer insight to drive winning strategies and hard-wire the voice of the customer throughout your organization. This interactive program will equip you with the right blend of qualitative and quantitative tools to gain and sustain competitive advantage.

Leading with Advanced Analytics and Artificial Intelligence

Previously Named: Leading with Big Data and Analytics

Sophisticated subject matter in an easy-to-understand, accessible format equips executives with the working knowledge needed to seize opportunities that analytics, artificial intelligence and a data strategy presents and put data analytics to practical use.

The PHYSICIAN CEO™ Program

Marketing Analytics: Leading with Big Data (MKTGX-950-0)
Big data and analytics represent a huge opportunity for today's business leaders and are of critical importance to marketing. This class will teach senior leaders how to leverage the value and insights of the work done in data science to transform their organization. Big data and analytics is not a technology or data science problem; it's a leadership problem that can and must be solved by leaders. Executives equipped with a working knowledge of data science can massively improve marketing, create operating efficiencies, build new business models, disrupt the competitive status quo of industry and spark innovation. This class will deliver sophisticated data analytics in an easy-to-understand, accessible manner. The content will focus on marketing applications such as pricing, promotion, churn management and memberships (e.g., Amazon Prime). You'll come away equipped with the knowledge you need to seize opportunities that data analytics presents, tools required to put data to practical use and insights to leverage analytics for increased efficiency, productivity or new business opportunities. A solid understanding of Microsoft Excel is required for this course.

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.

MBAi Immersion Internship (MBAI-940-0)


MBAi AI Leaders (MBAI-920-5)


MBAi Seminar Series (MBAI-910-25)