Elicitron: An LLM Agent-Based Simulation Framework for Design Requirements Elicitation

TL;DR

This paper presents Elicitron, a framework using LLM-based agents to simulate user interactions, uncover diverse and latent needs, and improve requirements elicitation in product development.

Contribution

Elicitron introduces a novel LLM agent-based simulation framework that enhances requirements gathering by exploring broader user needs and analyzing interview data.

Findings

Context-aware agent generation increases need diversity

Framework identifies more latent needs than traditional interviews

LLMs effectively analyze and classify user needs

Abstract

Requirements elicitation, a critical, yet time-consuming and challenging step in product development, often fails to capture the full spectrum of user needs. This may lead to products that fall short of expectations. This paper introduces a novel framework that leverages Large Language Models (LLMs) to automate and enhance the requirements elicitation process. LLMs are used to generate a vast array of simulated users (LLM agents), enabling the exploration of a much broader range of user needs and unforeseen use cases. These agents engage in product experience scenarios, through explaining their actions, observations, and challenges. Subsequent agent interviews and analysis uncover valuable user needs, including latent ones. We validate our framework with three experiments. First, we explore different methodologies for diverse agent generation, discussing their advantages and shortcomings. We measure the diversity of identified user needs and demonstrate that context-aware agent generation leads to greater diversity. Second, we show how our framework effectively mimics empathic lead user interviews, identifying a greater number of latent needs than conventional human interviews. Third, we showcase that LLMs can be used to analyze interviews, capture needs, and classify them as latent or not. Our work highlights the potential of using LLM agents to accelerate early-stage product development, reduce costs, and increase innovation.