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Consumer segmentation with large language models

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  • Li, Yinan
  • Liu, Ying
  • Yu, Muran

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.

Suggested Citation

  • Li, Yinan & Liu, Ying & Yu, Muran, 2025. "Consumer segmentation with large language models," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:joreco:v:82:y:2025:i:c:s0969698924003746
    DOI: 10.1016/j.jretconser.2024.104078
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    1. Ye Yang & Angela Paladino, 2015. "The case of wine: understanding Chinese gift-giving behavior," Marketing Letters, Springer, vol. 26(3), pages 335-361, September.
    2. Aschemann-Witzel, Jessica & de Hooge, Ilona E. & Almli, Valérie L., 2021. "My style, my food, my waste! Consumer food waste-related lifestyle segments," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    3. Celhay, Franck & Cheng, Peiyao & Masson, Josselin & Li, Wenhua, 2020. "Package graphic design and communication across cultures: An investigation of Chinese consumers' interpretation of imported wine labels," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 108-128.
    4. Miguel Alves Gomes & Tobias Meisen, 2023. "A review on customer segmentation methods for personalized customer targeting in e-commerce use cases," Information Systems and e-Business Management, Springer, vol. 21(3), pages 527-570, September.
    5. Kim, Jungkeun & Kim, Jeong Hyun & Kim, Changju & Park, Jooyoung, 2023. "Decisions with ChatGPT: Reexamining choice overload in ChatGPT recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    6. Nilashi, Mehrbakhsh & Ahmadi, Hossein & Arji, Goli & Alsalem, Khalaf Okab & Samad, Sarminah & Ghabban, Fahad & Alzahrani, Ahmed Omar & Ahani, Ali & Alarood, Ala Abdulsalam, 2021. "Big social data and customer decision making in vegetarian restaurants: A combined machine learning method," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    7. Chen, Zhuo & Gong, Yanping & Huang, Rong & Lu, Xi, 2024. "How does information encountering enhance purchase behavior? The mediating role of customer inspiration," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    8. Kirshner, Samuel N., 2024. "GPT and CLT: The impact of ChatGPT's level of abstraction on consumer recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    9. Martin Reisenbichler & Thomas Reutterer & David A. Schweidel & Daniel Dan, 2022. "Frontiers: Supporting Content Marketing with Natural Language Generation," Marketing Science, INFORMS, vol. 41(3), pages 441-452, May.
    10. Kondo, Fumiyo N. & Okubo, Taishi, 2022. "Understanding multi-channel consumer behavior: A comparison between segmentations of multi-channel purchases by product category and overall products," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    11. Díaz, Asunción & Gómez, Mar & Molina, Arturo & Santos, Jesús, 2018. "A segmentation study of cinema consumers based on values and lifestyle," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 79-89.
    12. Zhou, Jinfeng & Wei, Jinliang & Xu, Bugao, 2021. "Customer segmentation by web content mining," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    13. Rahim, Mussadiq Abdul & Mushafiq, Muhammad & Khan, Salabat & Arain, Zulfiqar Ali, 2021. "RFM-based repurchase behavior for customer classification and segmentation," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    14. Perrine Desmichel & Derek D Rucker, 2024. "Dominance versus Prestige Hierarchies: How Social Hierarchy Base Shapes Conspicuous Consumption," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 50(5), pages 887-906.
    15. Chen, Yanhong & Liu, Luning & Zheng, Dequan & Li, Bin, 2023. "Estimating travellers’ value when purchasing auxiliary services in the airline industry based on the RFM model," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    16. El Hedhli, Kamel & Zourrig, Haithem & Becheur, Imene, 2021. "Celebrity endorsements: Investigating the interactive effects of internalization, identification and product type on consumers’ attitudes and intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    17. Peiyao Li & Noah Castelo & Zsolt Katona & Miklos Sarvary, 2024. "Frontiers: Determining the Validity of Large Language Models for Automated Perceptual Analysis," Marketing Science, INFORMS, vol. 43(2), pages 254-266, March.
    18. Pallant, Jessica & Sands, Sean & Karpen, Ingo, 2020. "Product customization: A profile of consumer demand," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    19. D Matthew Godfrey & Linda L Price & Robert F Lusch, 2022. "Repair, Consumption, and Sustainability: Fixing Fragile Objects and Maintaining Consumer Practices [Matter in or out of Place? Bicycle Parking Strategies and Their Effects on People, Practices and ," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(2), pages 229-251.
    20. Chang, Woondeog & Park, Jungkun, 2024. "A comparative study on the effect of ChatGPT recommendation and AI recommender systems on the formation of a consideration set," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    21. Stöckigt, Gerrit & Schiebener, Johannes & Brand, Matthias, 2018. "Providing sustainability information in shopping situations contributes to sustainable decision making: An empirical study with choice-based conjoint analyses," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 188-199.
    22. Andreas Niedermeier & Agnes Emberger‐Klein & Klaus Menrad, 2021. "Which factors distinguish the different consumer segments of green fast‐moving consumer goods in Germany?," Business Strategy and the Environment, Wiley Blackwell, vol. 30(4), pages 1823-1838, May.
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