Abstract
The integration of customer feedback is universally acknowledged as crucial in the product development process. Yet, traditional feedback collection methods employed by companies, such as interviews and surveys, have remained mainly unchanged and come with limitations. Interviews often fail to accurately capture customers' needs due to communication barriers, while surveys prompt only incremental changes instead of inspiring innovation. This challenge is compounded in the service industry, where feedback is intangible and more difficult to quantify. Text analysis presents a promising solution to delve into customer preferences more deeply, providing insights that can guide the development of new products and services. Our research advances the use of generative AI, specifically the GPT engine, beyond its conventional role as a chatbot. We innovate by adapting it to extract actionable insights from customer-service interactions, offering real-time, valuable data for decision-making and representing a significant leap forward in Voice of the Customer (VoC) analysis.
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