Is Less More? Exploring AI-Driven Personalization in Online Retail : An Exploratory Mixed-Methods Research

Background: In the modern world, consumers are faced with an endless number of choices on online retail platforms, potentially resulting in choice delay or abandonment. This presents a significant challenge for retailers operating in a rapidly evolving digital environment, where Artificial Intelligence (AI) increasingly influences consumer behavior. To maintain a competitive advantage retailers must develop an understanding of the changing dynamics of consumer purchasing behavior and their influence on online retail platform selection to adapt their platform strategies accordingly. Purpose: The aim of the study is to explore how consumers perceive AI-driven personalization when shopping online, and consequently, how this influences the retail platform selection, driving the evolution of online retail. Method: To investigate the research questions, exploratory research with a mixed-method design was employed. Data was collected through a Google Form survey of online consumers who purchased in the last 12 months and semi-structured interviews with AI or Retail experts. Conclusion: The results showcased a trend that AI-driven personalization influence consumer purchasing interest by making the decision-making process simpler and more efficient through personalized recommendations. Followingly, the concept of hyper-personalization is introduced as a driving force for the increased use of social commerce for greater tailored online shopping. Lastly, based on the findings, “Unichannel” retailing emerged as a suggestion for the future evolution of online retail, where platforms are further interlinked, easing consumers decision-making process.