Can Large Language Models Extract Customer Needs as Well as Professional Analysts? – MSI

Working Paper

Can Large Language Models Extract Customer Needs as Well as Professional Analysts?

Artem Timoshenko, Chengfeng Mao, and John R. Hauser

Feb 4, 2025

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Compares results from human analysts, a LLM with prompt engineering only and one with supervised fine-tuning to determine the potential to automate extracting consumer needs from text such as online reviews.

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research recap

Training LLMs to ID Implicit Consumer Needs

Extracting consumer needs from online reviews and other sources can inform product and service innovation but is typically costly. Large language models (LLMs) trained to professional standards can cost-effectively identify implicit consumer needs that are specific but abstract enough to be useful. Automating other innovation tasks may be more difficult.

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