Browsing by Author "Kayaga Miria"

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    Customer Intelligence, Data-Driven Marketing, and Customer Retention: A Study of Insurance Companies in Kampala District.
    (Makerere University Business School, 2025-05-20) Kayaga Miria
    This study investigates the relationship between customer intelligence, data-driven marketing, and customer retention within insurance companies operating in Kampala District. The research seeks to explore how customer intelligence strategies influence customer retention, the role of data-driven marketing in enhancing retention, and the mediating effect of data-driven marketing between customer intelligence and customer retention. A structured questionnaire was administered to insurance company employees, and the data collected were analyzed using SPSS, focusing on Pearson correlation and Hierarchical linear regression to identify key relationships. The findings revealed a significant positive correlation between customer intelligence and customer retention, with insurance companies that effectively utilized customer data showing higher retention rates compared to those with limited customer intelligence. Data-driven marketing also showed a strong association with retention, where companies leveraging data analytics to personalize marketing strategies experienced higher customer loyalty. Additionally, data-driven marketing was found to mediate the relationship between customer intelligence and retention, further emphasizing its importance in optimizing customer loyalty strategies. The study highlights the critical role of customer intelligence and data-driven marketing in fostering customer retention and suggests that insurance companies investing in these areas are better positioned to enhance customer loyalty. Despite its contributions, the study acknowledges limitations, including a focus on a single industry and geographical area, and recommends further research into broader sectors and regions, as well as the integration of qualitative approaches to enrich the findings.