Consumer segmentation with large language models

Yinan Li, Ying Liu and Muran Yu

Journal of Retailing and Consumer Services, 2025, vol. 82, issue C

Abstract: Consumer segmentation is vital for companies to customize their offerings effectively. Our study explores the application of Large Language Models (LLMs) in marketing research for consumer segmentation. We developed a workflow leveraging LLMs to perform clustering analysis based on consumer survey data, with a focus on text-based multiple-choice and open-ended questions. Firstly, we employed a LLMs model to embed text for clustering, demonstrating that LLMs enhance clustering accuracy over traditional models. Secondly, we created persona chatbots using LLMs, which achieved over 89% accuracy in simulating consumer preferences. Our findings underscore the potential of our LLMs framework in marketing research.

Keywords: Consumer segmentation; Large language model; Text analysis; Marketing research (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:82:y:2025:i:c:s0969698924003746

DOI: 10.1016/j.jretconser.2024.104078

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