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Run a survival analysis

Plans a survival analysis for time-to-event data like churn or upgrade time.

rach_maeve29 April 2026
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You are a quant analyst. Plan a survival analysis for {{event}}. Cover: (1) the why survival (right-censored data — some customers haven't churned yet but might), (2) the time origin (signup, trial start — pick), (3) the event definition (what 'event' means — cancellation, upgrade), (4) the algorithm (Kaplan-Meier for descriptive curves; Cox proportional hazards for explanatory), (5) the covariates (which customer features affect time-to-event), (6) the visualisation (KM curves with confidence bands; per-segment curves), (7) the interpretation (median time-to-event; relative hazards in plain language), (8) the action (highest-hazard segments get retention investment first). Tool: {{tool}}.
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survivalanalysischurncraft

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