About

Eric T. Anderson is the Polk Bros. Chair in Retailing and Professor of Marketing at Northwestern University’s Kellogg School of Management. He is also the former Chair of the Marketing Department and the Director of the Kellogg-McCormick MBAi Program. He holds a Ph.D. in Management Science from MIT Sloan School of Management, along with a Master’s degree in Engineering-Economic Systems from Stanford University and a Bachelor’s degree in Electrical Engineering from Northwestern University. His research interests include AI transformation, customer loyalty, retailing, pricing strategy, innovation, and channel management. At Kellogg, he teaches courses such as Loyalty Co: The Business of Customer Loyalty and Marketing Analytics in the MBA and EMBA programs. Anderson has received multiple awards for his teaching and research, including the Sydney Levy Award for best elective at Kellogg, the Weitz-Winer-O’Dell Award for long-term impact, and the Paul Green best paper award. His scholarly articles have been published in leading journals such as the Journal of Marketing Research, Marketing Science, Management Science, and the Quarterly Journal of Economics, and he has contributed articles to Harvard Business Review and Sloan Management Review. Anderson serves on the Board of Directors for Canadian Tire and is an advisor for LiftLab. His research has been conducted with various companies worldwide and has significantly impacted both management practice and academic theory.

Research topics

• Computer Science
• Artificial Intelligence
• Microeconomics
• Psychology
• Economics
• Social psychology
• Marketing
• Business
• Communication
• Econometrics

Selected publications

• Pricing with Bandits in the Long-tail: The Role of Competitive Monitoring

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Who Benefits from Alternative Data for Credit Scoring? Evidence from Peru

  Journal of Marketing Research · 2025-07-11 · 1 citations

  articleSenior author

  The World Bank estimates that 1.4 billion individuals worldwide are unbanked, lacking access to credit due to the absence of traditional credit scores. In this article, the authors demonstrate how retail transaction data can be used to construct an alternative credit score, potentially expanding credit access for these individuals. The study utilizes a unique dataset obtained through a partnership with a Peruvian company. The authors merge customer loyalty data and credit card repayment data with administrative records from the Peruvian financial system that provide individuals’ detailed financial histories. This comprehensive dataset allows the authors to construct credit scores for people both with and without a credit history. Through simulations of credit card approval decisions, they find that incorporating retail data increases approval rates for individuals without a credit history, from 16% to between 31% and 48%. In contrast, for those with an established credit history, approval rates remain largely unchanged, at around 88%. The authors investigate why retail data particularly benefits people without a credit history and discuss the broader implications of this credit scoring methodology for consumers, firms, and policy makers. The findings highlight the methodology’s potential to transform credit access for millions of previously unbanked individuals.

  PublisherDOI

• Markups Across Space and Time

  The Review of Economic Studies · 2025-12-28 · 2 citations

  articleOpen access1st authorCorresponding

  Abstract In this article, we provide direct evidence on the behaviour of markups in the retail sector across space and time. Markups are measured using gross margins. We consider three levels of aggregation: the retail sector as a whole, the firm, and the product level. We find that: (1) markups are relatively stable over time and mildly procyclical; (2) there is a large regional dispersion in markups; (3) there is a positive cross-sectional correlation between local income and local markups; and (4) differences in markups across regions result from differences in the assortment of goods sold in different regions, not from deviations from uniform pricing. We propose a simple model consistent with these facts.

  PublisherOA PDFDOI

• Using Grocery Data for Credit Decisions

  Management Science · 2024 · 15 citations

  Senior authorCorresponding
  • Business
  • Marketing

  Many consumers across the world struggle to gain access to credit because of their lack of credit scores. This paper explores the potential of a new alternative data source, grocery transaction data, for evaluating consumers’ creditworthiness. Our analysis takes advantage of a unique, individual-level match of credit card data and supermarket loyalty card data. By developing credit scoring algorithms that either exclude or include grocery data, we illustrate both the incremental value of grocery data for credit decisions and its boundary conditions. We demonstrate that signals from grocery data can improve credit approval decisions, particularly for individuals who lack traditional credit scores. Furthermore, as a consumer establishes a relationship with lenders and builds a credit history, the marginal value of incorporating grocery data diminishes. These findings highlight the potential of grocery data in informing credit decisions and, consequently, in enabling financial institutions to extend credit to consumers who lack traditional credit scores. This paper was accepted by David Simchi-Levi, marketing. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02364 .

  PublisherDOI

• Canary Categories

  Journal of Marketing Research · 2023-11-29

  articleOpen access1st authorCorresponding

  Past customer spending in a category is generally a positive signal of future customer spending. Analyses of historical data at two retailers demonstrate that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that retailer. The authors propose an explanation for the existence of canary categories and then develop a stylized model that illustrates four contributing factors: the probability that a customer finds their favorite brand, customers’ willingness to substitute brands, the cost and attractiveness of visiting other stores, and expectations about future brand availability. The analysis uses both field data and experiments to investigate these factors. The findings suggest that canary categories exist (at least in part) because store assortments are not completely adjusted to local preferences. An implication is that canary categories are endogenous to each retailer; the same category may be a canary category at one retailer and a destination category at a competing retailer.

  PublisherOA PDFDOI

• Measuring Willingness to Pay: A Comparative Method of Valuation

  Journal of Marketing · 2023 · 18 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Willingness to pay (WTP) is a metric that is widely valued and utilized among both practitioners and academics. However, the conceptualization of WTP is ambiguous, and this ambiguity is reflected across existing methods of measuring WTP. The authors first present a formal mathematical framework that clarifies WTP as a distributional concept—rather than a single number—constructed as a function of customers, comparisons, and situations. The framework further reveals the operation of two comparative mechanisms, direct and indirect, by which situational factors affect WTP. They then introduce a new method to measure WTP—the comparative method of valuation (CMV)—that, unlike existing methods, is designed to account for the inherently comparative and situational nature of WTP. Across nine studies reported in the article and four additional studies in the Web Appendix, the authors (1) examine differences in results between CMV and choice-based conjoint as well as between CMV and the classic Becker–DeGroot–Marschak methodology, (2) demonstrate that CMV is a valid and reliable measure of WTP, and (3) illustrate applications of CMV to managerial problems. This article offers both conceptual clarity and methodological advances to understanding the construction and measurement of WTP for practitioners and academics alike.

  PublisherDOI

• Multiyear Impact of Backorder Delays: A Quasi-Experimental Approach

  Marketing Science · 2022-08-05 · 6 citations

  articleSenior author

  This paper investigates the impact of experiencing a backorder on customers’ purchase behaviors the next four years.

  PublisherDOI

• Digitization and Flexibility: Evidence from the South Korean Movie Market

  Marketing Science · 2021-03-11 · 7 citations

  article

  This paper examines how the introduction of digital cinema technologies in the South Korean movie industry created flexibility for theaters in movie showings.

  PublisherDOI

• Conceptualizing and measuring pathways for how object attachment affects willingness to pay (WTP)

  Current Opinion in Psychology · 2020 · 14 citations

  Senior authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Psychology
  PublisherDOI

• How price promotions work: A review of practice and theory

  Handbook of economics marketing · 2019-01-01 · 31 citations

  review1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Duncan Simester

  33 shared

• Dennis P. Nolan

  Los Medanos College

  11 shared

• Erik Brynjolfsson

  National Bureau of Economic Research

  7 shared

• Yu Jeffrey Hu

  Purdue University West Lafayette

  5 shared

• Joonhyuk Yang

  5 shared

• Song Lin

  University of Hong Kong

  4 shared

• Sharlene He

  3 shared

• Sérgio Rebelo

  Northwestern University

  3 shared

Education

• PhD, Sloan School of Management

  Massachusetts Institute of Technology

Awards & honors

• Sydney Levy Award for best elective at Kellogg
• Weitz-Winer-O’Dell Award for long-term impact (2015)
• Paul Green best paper award (2014)
• Weitz-Winer-O’Dell Award for “Harbingers of Failure” (2015)
• Sidney J. Levy Award for Excellence in Teaching, Kellogg Sch…