To Buy or not to Buy? How GenAI Transforms Consumer Decision-Making in Online Consumption

Abstract

As generative artificial intelligence (GenAI) tools become increasingly integrated into everyday digital experiences, their role in consumer decision-making demands closer investigation. This thesis explores how GenAI influences the online consumer journey through the lens of the Engel-Blackwell-Miniard (EBM) model. Using qualitative interviews with consumers who regularly interact with GenAI in shopping contexts, the study examines each stage of the decision-making process, from need recognition to post-purchase and divestment. Findings suggest that GenAI significantly impacts early-stage behaviors by simplifying information search and structuring product comparisons. In the purchase decision stage, participants treated GenAI as an advisor rather than a final decision-maker, often relying on it more heavily when product knowledge was low or the perceived risk was minimal. Post-purchase, GenAI supported troubleshooting, feature discovery, and product evaluation, though traditional sources like manuals and peer reviews still played a dominant role. The study extends existing literature by highlighting how GenAI influences not only the pre-purchase stage but also post-purchase behavior, areas often overlooked in prior research. The findings offer theoretical contributions to the EBM framework and present practical implications for marketers seeking to align with evolving consumer habits shaped by GenAI technologies.