Oded Netzer | Columbia Business School

Vice Dean for Research: Dean's Office

Arthur J. Samberg Professor of Business: Marketing Division

Areas of Expertise: AI and Business Analytics Digital Future Initiative Marketing

Contact: Office: 941 Kravis; Phone: (212) 8549024; E-mail: [email protected]

Links: Personal Website; Curriculum Vitae

Professor Netzer's expertise centers on one of the major business challenges of the data-rich environment: developing quantitative methods that leverage data to gain a deeper understanding of customer behavior and guide firms' decisions. He focuses primarily on building statistical and econometric models to measure consumer preferences and understand how customer choices change over time, and across contexts. Most notably, he has developed a framework for managing firms' customer bases through dynamic segmentation. More recently, his research focuses on leveraging unstructured data for business applications.

He is the author of the book Decisions over Decimals.

Professor Netzer published numerous papers in leading scholarly journals. His research won multiple awards including, ISMS Long-term Contribution Award, the John Little Best Paper Award, the Frank Bass Outstanding Dissertation Award, the Society for Consumer Psychology (SCP) Best Paper Award, and the George S. Eccles Research Fund Award. He serves on the editorial board of several leading journals including Marketing Science, Management Science, Journal of Marketing Research, Journal of Marketing, Quantitative Marketing and Economics, and International Journal of Research in Marketing.

Oded teaches several courses including the Core Marketing course, a course on Marketing Research, a course on Developing Quantitative Intuition (QI), a doctoral course on Empirical Models in Marketing, as well as several executive education programs. Professor Netzer has won the Columbia Business School Dean’s Award for Teaching Excellence, and the Columbia University GSAC Faculty Mentoring Award to commemorate excellence in the mentoring of Ph.D. students.

Professor Netzer is an Amazon Scholar. Additionally, he frequently consult to Fortune 500 companies and entrepreneurial organization on strategy, data-driven decision making, marketing research and extracting useful information from rich and thin data.

Education: BSc, Technion (Israel Institute of Technology), 1997; MSc, Stanford University, 2002; PhD, 2004

Joined CBS: 2004

Featured Research

When Words Sweat: Identifying Signals for Loan Default in the Text of Loan Applications

Authors: Oded Netzer, Alain Lemaire, and Michal Herzenstein

Date: January 1, 2019

Format: Journal Article

Journal: Journal of Marketing Research

The authors present empirical evidence that borrowers, consciously or not, leave traces of their intentions, circumstances, and personality traits in the text they write when applying for a loan. This textual information has a substantial and significant ability to predict whether borrowers will pay back the loan above and beyond the financial and demographic variables commonly used in models predicting default.

Authors: Yael Karlinsky-Shichor and Oded Netzer

Date: Forthcoming

Format: Journal Article

Journal: Marketing Science

We propose a human-machine hybrid approach to automating decision making in high human-interaction environments and apply it in the business-to-business (B2B) retail context.

Authors: Jochen Hartmann, Mark Heitmann, Christina Schamp, and Oded Netzer

Date: December 1, 2021

Format: Journal Article

Journal: Journal of Marketing Research

Smartphones have made it nearly effortless to share images of branded experiences. This research classifies social media brand imagery and studies user response. Aside from packshots (standalone product images), two types of brand-related selfie images appear online: consumer selfies (featuring brands and consumers’ faces) and an emerging phenomenon the authors term “brand selfies” (invisible consumers holding a branded product).

Authors: Jonah Berger, Ashlee Humphreys, Stephan Ludwig, Wendy Moe, Oded Netzer, and David Schweidel

Date: January 1, 2020

Format: Journal Article

Journal: Journal of Marketing

Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data? This article provides an overview of automated textual analysis and details how it can be used to generate marketing insights. The authors discuss how text reflects qualities of the text producer (and the context in which the text was produced) and impacts the audience or text recipient.

Authors: Oded Netzer, Ronen Feldman, Jacob Goldenberg, and Moshe Fresko

Date: May 1, 2012

Format: Journal Article

Journal: Marketing Science

Web 2.0 provides gathering places for internet users in blogs, forums, and chat rooms. These gathering places leave footprints in the form of colossal amounts of data regarding consumers' thoughts, beliefs, experiences, and even interactions. In this paper, we propose an approach for firms to explore online user-generated content and "listen" to what customers write about their and the competitors' products. Our objective is to convert the user-generated content to market structures and competitive landscape insights.

Authors: Oded Netzer, James Lattin, and V. Srinivasan

Date: March 1, 2008

Format: Journal Article

Journal: Marketing Science

This research models the dynamics of customer relationships using typical transaction data. Our proposed model permits not only capturing the dynamics of customer relationships but also incorporating the effect of the sequence of customer-firm encounters on the dynamics of customer relationships and the subsequent buying behavior. Our approach to modeling relationship dynamics is structurally different from existing approaches.