Copersona: Leveraging LLMs and Expert Collaboration to Understand User Personas Through Social Media Data Analysis

Personalizing product innovation methodologies to align with user needs is essential in China’s rapidly evolving electronic manufacturing industry. Despite this necessity, there remains limited understanding of how advanced technologies can be effectively leveraged to create consumer personas that inform successful product development. The present study examines the impact of the CoPersona methodology, a novel approach that integrates human expertise with Large Language Models (LLMs), on the innovation process within this competitive sector. Through a detailed case study of a mid-sized manufacturer, B.Co, we investigated the use of CoPersona in the design and marketing of a bedside lamp. By analyzing over 38 million posts from the RedNote social network, we examined users’ daily life behaviors in bedroom contexts, leading to the creation of five distinct personas that informed key aspects of the product’s design. By integrating GPT-4 with expert human review, this methodology enabled B.Co to translate consumer pain points into 13 actionable product design directives, achieving a commercial adoption rate of 69.2%. Our findings suggest that the CoPersona methodology enhances the ability to process large datasets while maintaining the critical understanding needed for effective product design. We provide insights into how this hybrid approach can be utilized to personalize product and marketing strategies, offering valuable recommendations for manufacturers aiming to achieve market success through consumer-driven innovation.