The Impact of AI-Driven Personalization on Customer Satisfaction in E-Commerce: Balancing Technology, Transparency, and Control

Abstract

The rapid advancements in artificial intelligence (AI) have revolutionized the way businesses interact with their customers. One key area of AI-driven innovation is personalization, where algorithms analyze customer data to deliver tailored experiences. This study investigates the impact of AI-driven personalization on customer satisfaction in e-commerce.Using a sample of 502 customers from an e-commerce platform, the research examines the relationships between AI-driven personalization, recommendation algorithm transparency, customer control over personalization, and overall customer satisfaction. A quantitative cross-sectional design is employed, utilizing validated scales and multiple linear regression analysis. Results indicate that AI-driven personalization has the strongest positive effect on customer satisfaction (β = 0.45, p < 0.001), followed by recommendation algorithm transparency (β = 0.23, p < 0.001) and customer control over personalization (β = 0.16, p < 0.01). The model explains 49% of the variance in customer satisfaction.These findings underscore the importance of implementing sophisticated AI-driven personalization strategies while maintaining transparency and offering customers control over their personalized experiences. The study contributes to the growing body of literature on AI applications in e-commerce and provides practical implications for businesses seeking to enhance customer satisfaction through personalization technologies.