Florian Zettelmeyer is the Nancy L. Ertle Professor of Marketing at the Kellogg School of Management at Northwestern University. He also founded and directs the Program on Data Analytics at Kellogg, the school's Analytics and AI initiative. 

Prior to his appointment at Kellogg he was an Associate Professor of Marketing and chair of the marketing group at the Haas School of Business, University of California at Berkeley. Before his Ph.D., he briefly worked in consulting at McKinsey and Company's German office. 

Professor Zettelmeyer specializes in evaluating the effects of analytics and AI on firms. In recent years he has focused on the AdTech industry, in particular on how to improve advertising measurement. Before that Professor Zettelmeyer has extensively studied the auto industry as a laboratory to understand the effects of customer information, investigating the effect of the Internet, the passthrough and effectiveness of promotions, and what consumers' online journeys predict about their purchase behavior.   

Professor Zettelmeyer teaches the MBA elective "Customer Analytics," a key analytics course at the Kellogg School of Management. The has received numerous teaching awards and been voted "Outstanding Professor of the Year" by Kellogg MBA students. He also co-directs Kellogg's "Leading with Advanced Analytics and AI" executive education course for senior leaders. He is a Research Associate of the National Bureau of Economic Research (NBER). 

In addition to being a chaired professor at Kellogg, Professor Zettelmeyer is a senior science leader at Amazon. He leads the Advertising Economics organization, whose function it to use data science and economics to come up with disruptive ideas for the Amazon advertising business. 

Professor Zettelmeyer received a Vordiplom in business engineering from the University of Karlsruhe (Germany), a M.Sc. in economics from the University of Warwick (UK) and a Ph.D. in marketing from the Massachusetts Institute of Technology. 

Marketing analytics, digital advertising, marketing implications of consumer search and uncertainty, industrial organization, pricing, Internet, environmental economics

• PhD, 1996, Management Science, Massachusetts Institute of Technology
• Vordiplom, 1992, Business Engineering, University of Karlsruhe
• MS, 1991, Economics, University of Warwick

• Director, Program for Data Analytics at Kellogg, Northwestern University, Kellogg School of Management
• Nancy L. Ertle Chair in Marketing, Marketing, Northwestern University, Kellogg School of Management
• J. L. and Helen Kellogg Chair in Marketing, Professor, Marketing, Northwestern University, Kellogg School of Management
• Professor, Marketing, Haas School of Business, University of California at Berkeley, 9/1/2008
• Chair, Marketing Group, Marketing, Haas School of Business, University of California at Berkeley, 9/1/2008
• Associate Professor, Marketing, Haas School of Business, University of California at Berkeley, 9/1/2008
• Assistant Professor, Marketing, Haas School of Business, University of California at Berkeley, 9/1/2003
• Assistant Professor, Marketing, Simon Graduate School of Business Administration, University of Rochester, 9/1/1997

• John D.C. Little award for best paper in Marketing Science, INFORMS, 2019
• 2021 Sales SIG Excellence in Research Award, American Marketing Association, 2021
• Finalist for L. G. Lavengood Outstanding Professor of the Year Award, Kellogg School of Managment, 2018-2019
• Kellogg Nota Bene Speaker for MBA Programs
• Kellogg Nota Bene Speaker for MBA Programs
• Kellogg Nota Bene Speaker for MBA Programs
• Sid Levy Teaching Award, Kellog School of Management, 2017-2018
• Finalist for L. G. Lavengood Outstanding Professor of the Year Award, Kellogg School of Management, 2017-2018
• Finalist for L. G. Lavengood Outstanding Professor of the Year Award, Kellogg School of Management
• Certificate of Teaching Impact Award, Kellogg School of Management, Winter 2017
• Kellogg Nota Bene Speaker for Part-Time Program, Kellogg School of Management, 2014-2015
• Certificate of Teaching Impact Award, Kellogg School of Management, Winter 2015
• Impact Award, Kellogg
• Impact Award for teaching excellence, Kellogg School of Management, 2014
• Nota Bene, Kellogg
• Sid Levy Teaching Award, Kellogg
• Sidney J. Levy Teaching Award for teaching excellence in elective classes, Kellogg School of Management, 2013
• Faculty Commencement Address to Graduating Class 2011, Kellogg School of Management, 2011
• L. G. Lavengood Outstanding Professor of the Year Award, Kellogg School of Management, 2011
• Sidney J. Levy Teaching Award, Kellogg School of Management, 2010-2011, 2008-2009
• Impact Award for teaching excellence, Kellogg School of Management, 2011
• Lavengood Outstanding Professor of the Year Nominee for excellence , Kellogg School of Management, 2010
• Impact Award for teaching excellence, Kellogg School of Management, 2010

• Co-Editor, Quantitative Marketing and Economics, 2014-2018
• Associate Editor, Management Science, 2009-2019
• Associate Editor, Quantitative Marketing and Economics, 2007-2013
• Associate Editor, Quantitative Marketing and Economics2013
• Editorial Board Member, Marketing Science
• Editorial Board Member, Journal of Marketing Research
• Ad-hoc Reviewer, American Economic Review
• Associate Editor, American Economic Journal: Economic Policy
• Ad-hoc Reviewer, American Economic Journal: Applied Economics

Customer Analytics, Leading with Advanced Analytics and AI

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.

Chief Diversity Officer Summit

Discuss the latest academic research, practitioner insights and best practices in the area of diversity and inclusion with a select group of cross-sector peers.

Chief Marketing Officer Program

Master the insights needed to navigate significant challenges faced by CMOs today, by engaging in meaningful discussions with Kellogg's top faculty and industry executives. This program is specifically designed to increase the odds of success for enterprise marketing leaders.

Kellogg Corporate Governance Conference

Exclusive, by-invitation-only annual conference that brings together more than 200 corporate directors and CEOs to discuss critical issues in corporate governance.

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.

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.