This paper explores the uses and benefits of LLMs for researchers and practitioners who aim to understand consumer preferences. We show that GPT-3.5, a widely used LLM, responds to sets of survey questions in ways that are consistent with economic theory and well-documented patterns of consumer behavior, including downward-sloping demand curves and state dependence. We also show that estimates of willingness-to-pay for products and features generated by GPT-3.5 are of realistic magnitudes.
