Assessing Customer Satisfaction Drivers in Auto Insurance Policies

Thesis Abstract

The rising competition within the auto insurance industry necessitates a comprehensive understanding of the factors influencing customer satisfaction to foster loyalty and sustained profitability. This study aims to identify and empirically evaluate the key drivers of customer satisfaction in auto insurance policies, focusing on aspects such as policy coverage options, claims processing efficiency, customer service quality, pricing strategies, and technological accessibility. It seeks to address the gap in contextualized empirical evidence from mid-sized urban markets, where customer expectations and insurer capabilities vary significantly from large metropolitan areas. The research adopts a descriptive and correlational research design, employing a mixed-methods approach to comprehensively analyze quantitative data and qualitative insights. The study population comprises 1,200 auto insurance policyholders within a mid-sized urban region, selected through stratified random sampling to ensure representativeness across demographic and policy-type segments. Data collection instruments include a structured questionnaire, developed based on the SERVQUAL model and validated through a pilot study, and semi-structured interview guides for a subset of participants. The questionnaire assesses perceptions of various service quality dimensions and satisfaction levels, rated on a five-point Likert scale, while qualitative data elucidate underlying reasons for satisfaction or dissatisfaction. Quantitative data are analyzed using multiple regression analysis to determine the strength and significance of different satisfaction drivers, with model assumptions checked through residual analysis and multicollinearity diagnostics. Structural Equation Modeling (SEM) is employed to test the hypothesized relationships derived from the Expectancy Disconfirmation Theory and the SERVQUAL framework, providing insights into the direct and indirect influences of service quality dimensions on overall satisfaction. Qualitative data undergo thematic analysis, with coding guided by predefined categories aligned with the conceptual model, to identify emerging themes that contextualize the quantitative findings. Key expected findings include confirmation that claims processing efficiency and customer service quality are the most significant predictors of overall satisfaction, accounting for approximately 65% of the variance. Policy coverage breadth and premium affordability are anticipated to have moderate but statistically significant effects, while technological accessibility, such as mobile app usability, may serve as a supplementary satisfaction driver. The findings are expected to reveal demographic variations, with younger policyholders placing higher importance on digital features, whereas older clients prioritize personalized service. This study contributes to existing insurance literature by providing empirically validated insights into satisfaction drivers within a specific market context, enriching the theoretical understanding of service quality's impact on customer perceptions. It extends the application of the SERVQUAL model and Expectancy Disconfirmation Theory in the auto insurance domain, offering a nuanced understanding of how service attributes influence client retention and loyalty. Additionally, the research offers practical implications for insurers aiming to enhance satisfaction, recommending targeted improvements in claims processing protocols, customer interaction strategies, and digital service platforms. The main conclusion underscores the paramount importance of operational efficiency and service quality in shaping customer satisfaction. The study recommends insurers prioritize investment in claims handling technology, staff training for improved customer interactions, and the development of accessible digital interfaces. Future research should explore longitudinal effects of satisfaction improvement initiatives and extend the scope to include commercial vehicle insurers to compare different market segments. By identifying specific service attributes that significantly impact satisfaction, this thesis provides a strategic framework for insurers aiming to optimize customer experience and competitive positioning within the auto insurance sector.