Developing a Data-Driven Customer Retention Framework for Nigerian Commercial Banks

Customer retention is a strategic priority for Nigerian commercial banks facing intensifying competition from fintech disruptors, and a professionally designed data science framework can systematically translate customer behavioural data into actionable retention programmes. This study developed a customer retention framework for Tier 1 and Tier 2 commercial banks in Nigeria, drawing on practice assessment at three banks in Lagos and Abuja and benchmarking against international banking analytics models. A professional framework development methodology was applied, incorporating structured consultations with 15 bank data analytics managers and 8 customer experience specialists, review of CBN customer protection guidelines, and analysis of published customer churn research in comparable emerging market banking contexts. The framework specifies four operational components: a real-time churn risk scoring engine using gradient boosting, a customer lifetime value segmentation model, a next-best-action recommendation system for relationship managers, and a closed-loop programme evaluation mechanism. Data governance provisions aligned with NDPA 2023 are embedded throughout. Feature engineering recommendations for the Nigerian context, including mobile banking inactivity signals and cross-product usage patterns, are detailed. Expert review by nine banking analytics and CRM specialists confirmed the framework's operational feasibility and regulatory alignment. The study recommends the framework be piloted at one Tier 2 bank with a six-month evaluation cycle before scaling, and that CBN incorporate data-driven retention standards into its consumer protection supervisory assessment framework.

Keywords: customer retention, commercial banking, churn prediction, data science framework, Nigeria