aceAdvancing value creation in B2B market research – a human–AI collaboration framework for large language model
Purpose This study aims to examine how prompt design influences the quality of large language model (LLM)-generated business-to-business (B2B) market research outputs. It also proposes a switch-point governance mechanism for converting LLM-generated drafts into decision-ready market intelligence artefacts. Design/methodology/approach The study uses an exploratory pilot evaluation of three market-facing LLM-based tools: ChatGPT, Gemini and Perplexity AI. The tools are compared across three benchmark B2B market re…
In a small pilot, role-specific prompts produced the strongest descriptive scores for AI-drafted B2B market research, and Gemini showed the best observed profile on relevance, stability and speed.
The study is an exploratory pilot with a small task set, and the ANOVA rests on only three observations per tool, so results may not generalise across domains, model versions or organisations.
Evidence
- Peer-reviewedJournal of Business & Industrial Marketing2026-10-28
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Truvace Impact Record TRV-2026-2305, v1: “Advancing value creation in B2B market research – a human–AI collaboration framework for large language model.” Truvace, 2026-10-29. /record/TRV-2026-2305 (accessed at citation time). sha256 d56c378669c04348…
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