Evaluation of a Customer Development Simulator Using Large Language Model-Based Multi-agent System and Synthetic Respondents

Lois Abigail To, Zachary Matthew Alabastro, Joseph Benjamin Ilagan

In Proceedings of the Tenth International Congress on Information and Communication Technology (ICICT 2025), LNNS 1441, pp. 261–270. Springer, 2025.

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Abstract

Customer development (CD) is a Lean Startup (LS) methodology for startups to validate their business hypotheses and refine their business model based on customer feedback. This paper proposes designing a large language model-based multi-agent system (LLM MAS) to enhance the customer development process by simulating customer feedback. Using LLMs’ natural language understanding (NLU) and synthetic multi-agent capabilities, startups can conduct faster validation while obtaining preliminary insights that may help refine their business model before engaging with the real market. The study presents a model in which the LLM MAS simulates customer discovery interactions between a startup founder and potential customers, together with design considerations to ensure real-world accuracy and alignment with CD. If carefully designed and implemented, the model may serve as a useful co-pilot that accelerates the customer development process.

Keywords: Large language models; Multi-agent systems; LLM-based multi-agent systems; Customer development; Lean startup

About this copy

Preprint (version submitted for peer review). This is a preprint of the following chapter: Lois Abigail To, Zachary Matthew Alabastro, Joseph Benjamin Ilagan, Evaluation of a Customer Development Simulator Using Large Language Model-Based Multi-agent System and Synthetic Respondents, published in Proceedings of Tenth International Congress on Information and Communication Technology (ICICT 2025), edited by Xin-She Yang, R. Simon Sherratt, Nilanjan Dey, Amit Joshi, 2025, Springer reproduced with permission of Springer Nature Singapore Pte Ltd. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-981-96-6938-7_22.

Cite as

Lois Abigail To, Zachary Matthew Alabastro, Joseph Benjamin Ilagan (2025). Evaluation of a Customer Development Simulator Using Large Language Model-Based Multi-agent System and Synthetic Respondents. In Proceedings of the Tenth International Congress on Information and Communication Technology (ICICT 2025), LNNS 1441, pp. 261–270. Springer. https://doi.org/10.1007/978-981-96-6938-7_22