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EXPRESS: AI-Human Hybrids for Marketing Research: Leveraging LLMs as Collaborators
Journal of Marketing ( IF 11.5 ) Pub Date : 2024-08-09 , DOI: 10.1177/00222429241276529
Neeraj Arora , Ishita Chakraborty , Yohei Nishimura

The authors’ central premise is that a human-LLM hybrid approach leads to efficiency and effectiveness gains in the marketing research process. In qualitative research, they show that LLMs can assist in both data generation and analysis; LLMs effectively create sample characteristics, generate synthetic respondents, and conduct and moderate in-depth interviews. The AI-human hybrid generates information-rich, coherent data that surpasses human-only data in depth and insightfulness and matches human performance in data analysis tasks of generating themes and summaries. Evidence from expert judges shows that humans and LLMs possess complementary skills; the human-LLM hybrid outperforms its human-only or LLM-only counterpart. For quantitative research, the LLM correctly picks the answer direction and valence, with the quality of synthetic data significantly improving through few-shot learning and retrieval-augmented generation. The authors demonstrate the value of the AI-human hybrid by collaborating with a Fortune 500 food company and replicating a 2019 qualitative and quantitative study using GPT-4. For their empirical investigation, the authors design the system architecture and prompts to create personas, ask questions, and obtain responses from synthetic respondents. They provide roadmaps for integrating LLMs into qualitative and quantitative marketing research and conclude that LLMs serve as valuable collaborators in the insight generation process.

中文翻译:


EXPRESS:用于营销研究的人工智能与人类混合体:利用LLMs作为合作者



作者的中心前提是人类——LLM混合方法可以提高营销研究过程的效率和有效性。在定性研究中,他们表明LLMs可以协助数据生成和分析;LLMs有效地创建样本特征,生成综合受访者,并进行和主持深度访谈。人工智能与人类的混合体生成信息丰富、连贯的数据,在深度和洞察力上超越了人类的数据,并且在生成主题和摘要的数据分析任务中与人类的表现相匹配。专家评审的证据表明,人类和LLMs拥有互补的技能;人类——LLM混合动力优于纯人类或LLM-唯一的对应物。对于定量研究,LLM正确选择答案方向和效价,通过少量学习和检索增强生成,合成数据的质量显着提高。作者与一家财富 500 强食品公司合作,并使用 GPT-4 复制 2019 年的定性和定量研究,证明了人工智能与人类混合的价值。为了进行实证调查,作者设计了系统架构,并提示创建角色、提出问题并获得综合受访者的答复。他们提供了整合路线图LLMs进行定性和定量营销研究并得出结论:LLMs在洞察生成过程中充当有价值的合作者。
更新日期:2024-08-09
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