Marketing With Generative AI: Harvard Business School’s Ayelet Israeli

Nov 7, 2023

Ayelet Israeli, assistant professor at Harvard Business School, discusses the opportunities and limitations of generative AI in market research. She explores how AI can simulate focus groups and surveys, reducing time and cost. They also discuss the rationality of marketing strategies and the challenge of finding extreme ideas. Israeli highlights the potential of AI in addressing bias and generating unbiased outcomes, mentioning the improvement in AI models over time.

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Introduction

00:00 • 2min

Using GPT for Market Research and Willingness to Pay

02:13 • 8min

Understanding the Rationality and Non-Rationality of Marketing Strategies

09:55 • 5min

Limitations of Generative AI

14:26 • 13min

AI Bias and Unbiased Outcomes

27:54 • 5min

As an associate professor at Harvard Business School and cofounder of the Customer Intelligence Lab at the school’s Digital Data Design Institute, Ayelet Israeli’s work is focused on how data and technology can inform marketing strategy, as well as how generative AI can be a useful tool in eliminating algorithmic bias. One of the products of her recent work is a paper she coauthored with two Microsoft economists and researchers on how generative AI could be used to simulate focus groups and surveys to determine customer preferences.

Ayelet joins Sam and Shervin to discuss the opportunities and limitations of generative AI in market research. She details how the research was conducted and how artificial intelligence technology could help marketers reduce the time, cost, and complexity associated with traditional customer research methods. Read the episode transcript here.

Guest bio:

Ayelet Israeli is the Marvin Bower Associate Professor of Business Administration in Harvard Business School’s Marketing Unit. She is also the cofounder of the school’s Customer Intelligence Lab at the Digital Data Design Institute. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their internal data, customer data, and market data to improve outcomes. Her research interests include retail, pricing strategy, channel management, marketing analytics, and algorithmic bias. Israeli has a Ph.D. in marketing from the Kellogg School of Management at Northwestern University.

Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.

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