Consumer segmentation with large language models

Yinan Li

doi:10.1016/j.jretconser.2024.104078

Consumer segmentation with large language models

2025-01-01

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AI

DOI：10.1016/j.jretconser.2024.104078

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Abstract

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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 textbased 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

Consumer segmentation with large language models

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