AI-Powered Customer Journey Mapping and Experience Personalization: Examining Their Influence on Electric Vehicle Consumer Behavior in Punjab”

Abstract

This study explores the factors influencing electric vehicle (EV) adoption in Punjab, India, with a focus on mapping the customer journey and evaluating the role of AI-driven personalization in enhancing the purchase and ownership experience. The primary objective is to identify key psychological, economic, and social factors that impact EV adoption intentions and examine the role of AI in personalizing the consumer journey. The research employs a mixed-methods approach, combining both primary data (surveys and interviews) and secondary data from existing literature. Factor analysis and regression analysis were used to identify underlying drivers of EV adoption, and AI’s impact was analyzed through customer satisfaction surveys. The findings reveal that environmental concerns (r = 0.47) and fuel cost savings (r = 0.51) are the strongest motivators for adoption, while range anxiety (r = -0.35) and high upfront costs (r = -0.48) serve as significant barriers. Additionally, AI-driven personalization, including tailored recommendations and predictive maintenance, has a positive influence on consumer satisfaction, though its direct impact on purchase intention needs further exploration. This research contributes to a deeper understanding of EV consumer behavior in emerging markets and highlights the potential of AI to improve customer engagement and satisfaction. However, challenges related to data privacy, cost of implementation, and skepticism toward AI, particularly in rural areas, remain. Future research should explore the relationship between AI tools and purchase intent more comprehensively, particularly in rural and semi-urban settings.