Intelligent Customer Relationship Management in the Platform Economy: The Interplay of AI Personalization, Customer Experience, Trust, and Loyalty

Abstract

The platform economy has intensified the use of algorithmic intermediation, data analytics, and artificial intelligence (AI) in customer relationship management. This methodology paper develops an empirically testable framework for intelligent customer relationship management (iCRM) by examining the interplay among AI personalization, customer experience, trust, and customer loyalty. Drawing on customer relationship management, digital platform, online customer experience, personalization-privacy, and trust-loyalty research published in 2020 or earlier, the study proposes a quantitative cross-sectional design for users of digital platforms such as e-commerce, mobility, food-delivery, travel, and digital-service applications. The model treats AI personalization as a technology-enabled relational stimulus that can improve relevance and convenience, customer experience as an evaluative response to the platform journey, trust as a key relational mechanism under uncertainty, and loyalty as the focal behavioral outcome. The proposed study uses a structured questionnaire, multi-item Likert scales, and partial least squares structural equation modeling (PLS-SEM) to assess measurement quality, direct effects, mediation, and predictive power. Because this paper is methodological and no original field dataset is supplied, the Results section reports expected analytical patterns and a transparent reporting template rather than fabricated coefficients. The framework offers a rigorous basis for evaluating how platform firms can use AI-enabled CRM to create personalized experiences while maintaining trust and long-term customer relationships.