Generative AI models offer unprecedented opportunities for marketing scholars to complete tasks more effectively and efficiently.
This Marketing Science Institute (MSI) working paper illustrates the transformative potential of generative AI, particularly large language models (LLMs) and large multimodal models (LMMs), in consumer research. The authors, Kiwoong Yoo, Michael Haenlein and Kelly Hewett, highlight how these advanced AI models can generate new content, such as text and images, and assist in various stages of the research process, from idea generation to reporting. They emphasize the significant impact of LLMs and LMMs on enhancing creativity, efficiency and effectiveness in consumer research.
The authors provide a detailed framework for integrating LMMs into each stage of consumer research, including idea generation, theory development, pretesting, experimental design, data analysis and reporting. They present empirical evidence demonstrating the capabilities of LMMs in identifying literature gaps, designing experiments and generating silicon samples for testing hypotheses. The paper also discusses the mixed performance of LMMs in theory development and data analysis, noting their limitations in understanding complex human experiences and conducting sophisticated statistical analyses.
Despite the challenges, such as potential biases and the risk of homogeneity in research findings, the authors argue that LMMs offer valuable opportunities for marketing scholars. They propose guidelines for crafting prompts to effectively utilize LMMs in consumer research and suggest that these models can support qualitative research, democratize access to advanced analytical tools and enhance the overall research process. The paper concludes by acknowledging the need for ethical considerations and careful implementation to maximize the benefits of LMMs in consumer research.
Read the full study: A Whole New World: Charting Unexplored Territories in Consumer Research with Generative Artificial Intelligence.