Market Intelligence and AI: Our Course

Robert J. Morais, Lecturer in Business 
Kamel Jedidi, Jerome A. Chazen Professor of Global Business

Marketing Intelligence: The Art and the Science is a comprehensive market research course for MBA and MS marketing students. It is predicated on the idea that to understand customer attitudes, sentiments, and behavior fully, both qualitative and quantitative research are necessary. The course covers how brand-building insights, strategic business planning, and sound marketing decision making are best served by applying an array of behavioral, social, and mathematical sciences and using them complementarily. Our aim is to teach students to define marketing problems clearly, select and execute the right research to obtain customer intelligence, and apply the findings to marketing. A major group project enables students to learn experientially by conducting market research for real companies. Generative AI (GAI) is incorporated throughout the course. 

Teaching Market Research in the Age of AI

There is mounting evidence in practice and academic studies that AI has value for market research. In fact, AI could plausibly replace the expertise of some market researchers; at the very least, employees engaged  in market research will be judged by their use of AI. We view incorporating AI as a course imperative; excluding it would be a disservice to our students. 

GAI is integrated into the vast majority of our classes. Numerous lectures demonstrate the utility of GAI for research design, analysis, and marketing ideation. It was used by us and our students for input on interview guides and questionnaires, quantitative data analysis, e.g., customer segmentation, factor analysis, regression, topic modeling, qualitative content analysis, generating marketing insights, strategy formulation, and producing innovative marketing ideas. For instance, in a case study, we employed ChatGPT to analyze themes from focus group discussions held by a Chilean nutritional company. ChatGPT completed this task in seconds, yielding results comparable to those the company took two weeks to produce. A class devoted to market research ethics featured responses from GAI that informed a robust class discussion. 

What We’ve Learned from Teaching with AI

AI has transformed the way we teach market research, profoundly enhancing our students’ learning experience. GAI tools enabled us and our students to obtain product category knowledge with unmatched efficiency, design market research expansively, and conduct data analysis faster and more comprehensively than with traditional methods. With carefully constructed prompts, GAI generated a wealth of promising research-based marketing initiatives. One risk in tapping AI is that students could become overly dependent upon it and bypass the immersive human intellectual exercise that brings creativity and personal satisfaction to the market research process. Just as this course stresses the complementarity of qualitative and quantitative research, we underscore the complementarity and the inherent rewards of human-machine collaboration. Our conclusion about teaching with AI: AI empowers our students, serving as a sophisticated research assistant and collaborator. They are thrilled to be using it.

Advice for Other Columbia Instructors Teaching with AI

Professors should require students to be transparent about their use of AI and how they built upon it, ensuring they do not present AI-generated work as their own. Students should be required to verify the accuracy of AI’s responses. Professors should experiment with AI to discover the applications that work best for their courses. Finally, professors should actively embrace AI in their teaching rather than fear and shun it. AI is here to stay and, while it is not perfect, it is improving exponentially, and it will enrich their own and their students’ educational experience.