The Impact of Customer Satisfaction on Retention Rates: An Applied Study Using Predictive Statistical Analysis

Abstract—This research employed predictive statistical analysis to explore the relationship between customer satisfaction and retention rates in the Turkish internet services industry. Data collected from customer satisfaction surveys were analyzed using techniques such as regression models and Analysis of Variance (ANOVA). The findings revealed a significant positive relationship between customer satisfaction and retention rates, supporting the first hypothesis. Predictive models further demonstrated that customer satisfaction serves as a critical indicator of retention, confirming the second hypothesis. However, demographic variations affected the relationship, with no statistically significant differences observed in retention rates across certain age groups, leading to the rejection of the third hypothesis. Key factors like service quality, perceived value, and trust emerged as essential for enhancing retention. The study recommends fostering personalized interactions, improving service quality, and leveraging predictive analytics to design effective retention strategies. This research contributes to understanding customer satisfaction and retention dynamics, offering actionable insights for Turkish service providers and other competitive markets. Keywords - Customer Satisfaction, Customer Retention, Predictive Statistical Analysis, Internet Services, Retention Strategies.