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In digital markets, customer exit has become faster, quieter, and more difficult to reverse. Customers can reduce usage, compare alternatives, migrate to competitors, or cancel subscriptions with minimal friction. Despite this reality, many firms still allocate disproportionate managerial attention to acquisition rather than structured exit management. Existing research offers important insights into customer churn prediction, switching behaviour, engagement, loyalty programmes, service recovery, and win-back campaigns. However, these streams are often treated as separate domains rather than as connected stages in a customer exit process. This fragmentation limits managers’ ability to detect early churn signals, interpret switching intentions, and deploy retention interventions at the right time. This article proposes the Digital Customer Exit Management Framework as an original conceptual framework for digital customer retention. The framework links observable churn signals, psychological and contextual switching intentions, and targeted retention interventions into a unified process model. It positions customer exit not as a single cancellation event but as a dynamic trajectory that can be anticipated, interpreted, and influenced. The article argues that proactive exit management is a strategic capability for digital businesses. By moving from reactive retention to early signal detection and intervention alignment, firms can reduce avoidable churn, protect customer lifetime value, and improve the quality of customer relationship management. The framework provides a structured roadmap for managers and a foundation for future empirical testing.