Behavioural Data Analytics on Customer Churn Reduction in Telecommunication Services in Rivers State

Abstract This study examined the influence of behavioural data analytics on customer churn reduction in telecommunication services in Rivers State. Specifically, it focused on two dimensions of behavioural data analytics: social network behaviour analysis and customer usage analytics, while reduced switching intention was used as a measure of customer churn reduction. The study adopted a survey research design, collecting data from 324 telecom subscribers using a structured questionnaire. Descriptive statistics, correlation, and multiple regression analyses were employed to analyze the data. The findings revealed that both social network behaviour analysis (r = 0.612, p < 0.05) and customer usage analytics (r = 0.658, p < 0.05) have significant positive relationships with reduced switching intention. The regression analysis further showed that these two dimensions together explained 52.3% of the variance in reduced switching intention (R² = 0.523, F = 167.91, p = 0.000), with both predictors being significant contributors. The study concludes that behavioural data analytics is a critical tool for enhancing customer retention in the telecom sector, as understanding social interactions and usage patterns enables proactive strategies to reduce churn. It is recommended that telecom providers leverage social network insights and usage analytics to design personalized retention strategies and strengthen subscriber loyalty. The study contributes to knowledge by empirically linking behavioural data analytics to customer churn reduction and supporting the application of the Theory of Planned Behaviour in understanding subscriber retention behaviour.