Using GPT for Market Research

35 Pages Posted: 30 Mar 2023 Last revised: 8 Jul 2023

See all articles by James Brand

James Brand


Ayelet Israeli

Harvard Business School - Marketing Unit

Donald Ngwe

Microsoft Corporation

Date Written: March 21, 2023


Large language models (LLMs) have quickly become popular as labor-augmenting tools for programming, writing, and many other processes that benefit from quick text generation. In this paper we explore the uses and benefits of LLMs for researchers and practitioners who aim to understand consumer preferences. We focus on the distributional nature of LLM responses, and query the Generative Pre-trained Transformer 3.5 (GPT-3.5) model to generate hundreds of survey responses to each prompt. We offer two sets of results to illustrate our approach and assess it. First, we show that GPT-3.5, a widely-used LLM, responds to sets of survey questions in ways that are consistent with economic theory and well-documented patterns of consumer behavior, including downward-sloping demand curves and state dependence. Second, we show that estimates of willingness-to-pay for products and features generated by GPT-3.5 are of realistic magnitudes and match estimates from a recent study that elicited preferences from human consumers. We also offer preliminary guidelines for how best to query information from GPT-3.5 for marketing purposes and discuss potential limitations.

Keywords: Large language models (LLMs), Generative Pre-trained Transformer (GPT), Market research, Consumer preferences, AI, Conjoint

Suggested Citation

Brand, James and Israeli, Ayelet and Ngwe, Donald, Using GPT for Market Research (March 21, 2023). Harvard Business School Marketing Unit Working Paper No. 23-062, Available at SSRN: or

James Brand

Microsoft ( email )

Redomond, WA 98052

Ayelet Israeli (Contact Author)

Harvard Business School - Marketing Unit ( email )

Soldiers Field
Boston, MA 02163
United States

Donald Ngwe

Microsoft Corporation ( email )

One Microsoft Way
Redmond, WA 98052
United States

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