churnrisk

Churn risk is the probability that a customer will discontinue using a product or service within a specified time frame. It is a forward-looking predictive metric used by businesses to anticipate attrition and prioritize retention efforts. Churn risk is distinct from churn rate; churn risk focuses on individuals, while churn rate is the observed proportion of customers who leave over a period.

Inputs to churn risk assessment include historical churn data, usage patterns (login frequency, feature adoption), engagement signals (recency, session duration), customer satisfaction indicators, support tickets, payment activity, contract terms, and tenure. Modeling methods range from classical statistics such as logistic regression and survival analysis to machine learning classifiers and time-to-event models. The output is a churn risk score or probability for each customer over a specified horizon (for example, next 30 or 90 days).

Interpretation and use: higher risk scores flag customers who may churn and warrant targeted intervention. Applications include proactive outreach, personalized offers, improved onboarding or product changes, pricing experiments, and win-back campaigns. Risk can be enriched by segmentation across cohorts, value (lifetime value), product line, geography, and channel.

Limitations and governance: model performance depends on data quality and relevance; risk scores reflect associations rather than causation and can drift with market changes. Ongoing validation and recalibration are needed. Data privacy, consent, and transparent use of predictive insights should be maintained, and qualitative insights from account teams should complement quantitative risk estimates.

See also: churn rate, customer lifetime value, retention, propensity score.