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A Survival Analysis Guide with Python: Using Time-To-Event Models to Forecast Customer Lifetime

Towards Data Science Gustavo Santos April 9, 2026
A Survival Analysis Guide with Python: Using Time-To-Event Models to Forecast Customer Lifetime
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# How Businesses Can Predict When Customers Will Leave Companies can use a statistical technique called survival analysis to forecast how long customers will stick around and what factors make them more likely to leave. By analyzing patterns in when past customers stopped using their service, businesses can identify which groups are at highest risk of dropping off and when to intervene. This helps marketing and customer success teams focus their retention efforts where they'll have the biggest impact.

Understand survival analysis by modeling customer retention through Kaplan-Meier curves and Cox Proportional Hazard regressions. The post A Survival Analysis Guide with Python: Using Time-To-Event Models to Forecast Customer Lifetime appeared first on Towards Data Science.

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