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<p>Integrating generative artificial intelligence (AI), particularly large multimodal models (LMMs) like ChatGPT, into the research process offers significant opportunities for marketing scholars. This manuscript provides a field guide into the potential advantages and possible limitations of using LMMs in different stages of consumer research, including idea generation, theory development, pretesting and pilot testing, data collection for experimental designs, data analysis, and reporting. We illustrate LMMs’ capabilities by replicating the consumer research stages of 35 articles from five marketing journals using ChatGPT-4o. Our findings suggest that LMMs enhance the efficiency and effectiveness of consumer research, though their performance varies across stages. LMMs excel in developing theoretical frameworks and collecting data for experimental designs, offer moderate support for idea generation, pre-/pilot testing, and reporting but perform less effectively in data analysis (e.g., silicon sampling). This manuscript underscores generative AI’s potential in consumer research and calls for further exploration into ethical guidelines and best practices to ensure high-quality work.</p>

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A whole new world, a new fantastic point of view: Charting unexplored territories in consumer research with generative artificial intelligence

  • 期刊论文

  • 发表日期：

    2025年4月11日

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  • Kiwoong Yoo,
  • Michael Haenlein,
  • Kelly Hewett

摘要

Integrating generative artificial intelligence (AI), particularly large multimodal models (LMMs) like ChatGPT, into the research process offers significant opportunities for marketing scholars. This manuscript provides a field guide into the potential advantages and possible limitations of using LMMs in different stages of consumer research, including idea generation, theory development, pretesting and pilot testing, data collection for experimental designs, data analysis, and reporting. We illustrate LMMs’ capabilities by replicating the consumer research stages of 35 articles from five marketing journals using ChatGPT-4o. Our findings suggest that LMMs enhance the efficiency and effectiveness of consumer research, though their performance varies across stages. LMMs excel in developing theoretical frameworks and collecting data for experimental designs, offer moderate support for idea generation, pre-/pilot testing, and reporting but perform less effectively in data analysis (e.g., silicon sampling). This manuscript underscores generative AI’s potential in consumer research and calls for further exploration into ethical guidelines and best practices to ensure high-quality work.