A Framework for Integrating Social Media Engagement into Customer Loyalty Models

Thesis Abstract

In an increasingly digital marketplace, social media platforms have emerged as pivotal channels for fostering customer engagement, yet their integration into traditional customer loyalty models remains inadequately conceptualized and empirically validated. This study aims to develop a comprehensive framework that elucidates the role of social media engagement in shaping customer loyalty, thereby addressing the gap between digital interaction behaviors and established loyalty constructs. The specific objectives are to identify key dimensions of social media engagement that influence customer loyalty, to examine the mediating role of customer satisfaction and trust, and to propose an integrated model that enhances existing customer loyalty frameworks. Adopting a mixed-methods research design, the study combines quantitative analysis through a cross-sectional survey and qualitative insights derived from semi-structured interviews. The quantitative component targeted a population of 5,000 active customers of a leading telecommunications provider in a metropolitan region, employing stratified random sampling to select 500 respondents. Data were collected via structured questionnaires measuring social media engagement (using adapted scales from the Social Media Engagement Scale), customer loyalty (based on the Latin Square Loyalty Scale), customer satisfaction, and trust. Validity and reliability of the instruments were ensured through exploratory and confirmatory factor analyses, along with Cronbach’s alpha coefficients exceeding 0.80. Quantitative data were analyzed using descriptive statistics, Pearson correlation analysis, and hierarchical multiple regression to determine the influence of social media engagement dimensions on customer loyalty. Structural Equation Modeling (SEM) with AMOS was employed to test the proposed integrated framework, assessing the mediating effects of satisfaction and trust within the model. Qualitative data from 15 in-depth interviews were analyzed through thematic analysis to explore contextual nuances and deepen understanding of engagement behaviors, supplementing quantitative findings. Preliminary anticipated findings suggest that social media engagement significantly predicts customer loyalty, with active participation, advocacy, and sustained interaction emerging as critical dimensions. The analysis is expected to demonstrate that customer satisfaction and trust partially mediate this relationship, confirming the relevance of an integrated model that combines digital engagement metrics with traditional loyalty factors. The study further aims to identify specific social media activities that positively impact loyalty metrics, providing actionable insights for managers. This research makes a novel contribution to marketing theory by operationalizing and empirically validating an integrated model that incorporates social media engagement into customer loyalty frameworks. It advances existing knowledge by demonstrating the direct and indirect pathways through which social media behaviors influence loyalty outcomes, guided by the Stimulus-Organism-Response (S-O-R) theory and the Technology Acceptance Model (TAM). The study also offers practical implications, suggesting strategic social media interventions to enhance customer retention and advocacy. The conclusions underscore the importance of strategic social media management as a driver of customer loyalty, recommending that firms invest in tailored engagement strategies aligned with identified engagement dimensions. Future research directions include longitudinal studies to observe causal effects over time and cross-industry validations to enhance generalizability. Overall, this study provides a robust, empirically grounded framework that integrates digital engagement into traditional loyalty models, offering valuable insights for academics and practitioners seeking to leverage social media for competitive advantage in customer relationship management.