AI-Driven Personalization in E-Commerce: Impact on Customer Engagement and the Role of Privacy Concerns - Lang, Ratnawati; Saragih, Afni Eliana (Universitas Hamzanwadi, 2025)
This study addresses the gap in understanding the effects of different AI-driven personalization strategies on customer engagement in e-commerce, particularly considering the moderating role of privacy concerns. The purpose is to analyze how product recommendations, AI-driven customer service, and automated personalized promotions influence customer engagement, and how privacy concerns affect these relationships. A quantitative approach was applied using survey data collected from 258 e-commerce users. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that automated personalized promotions significantly enhance customer engagement, while product recommendations and AI-driven customer service do not have a significant impact. The findings suggest that privacy concerns play a critical role in moderating the effectiveness of AI personalization. This study contributes to e-commerce marketing strategies by highlighting the importance of privacy considerations and targeted personalized promotions to increase customer engagement. Future research should explore privacy concern mitigation and test findings across diverse e-commerce platforms.