The Impact of AI-Driven Personalisation on Consumer Trust, Perceived Value, and Customer Loyalty in Indian E-Commerce

Abstract

These days, AI is an increasingly prominent figure in ecommerce, influencing recommendations, adaptive interfaces, personalised offers, virtual assistants and predictive content. The systems can do much to cut down search effort as well as increase relevance, but they rely on lots of consumer information and can cause privacy issues that lead to loss of trust. This analytical study examines the impact of the personalisation quality and recommendation relevance on perceived value, privacy concern on consumer trust and perceived value and consumer trust on customer loyalty in the Indian ecommerce industry. A cross-sectional quantitative design was determined for 312 online shoppers that had experienced AI recommendations in the last year. A structured five point likert scale was used to assess six constructs. The reliability of all scales was satisfactory. The perceived value was greatly enhanced by personalisation quality, in particular by recommendation relevance, which had the greater impact. Perceived value positively influenced consumer trust, whereas privacy concern negatively did. Consumer trust was the most significant factor affecting customer loyalty. The results indicate that the elements of effective personalisation are not necessarily those of intensity: they are relevant recommendations, user friendly data usage, consumer control and reliable platform behaviour. E-commerce companies must, therefore, integrate privacy protection, personalisation transparency and recommendation precision to generate long-term loyalty, not just short-term convenience, from their algorithms.