How long does a defined key action persist, and when does drop-off risk rise?

Estimate survival, hazard, and observed recurring value from censored action episodes.

Should cases still active at observation end be included?

Yes. They are censored observations, not cases that never exit. Excluding them biases survival downward.

Does a segment difference prove a cause?

No. Channel, plan, customer mix, and timing can differ together. Treat it as a directional observation until an intervention is tested.

Does this predict drop-off for individual entities?

No. It summarizes time-based survival and hazard for action episodes. Individual scoring is a separate modeling problem.

Action survival

Action survival and drop-off analysis

See when a key action drops off over time and which group should be tested first.

Summary

Measure whether an entity keeps a defined key action and when it exits or drops off with censoring handled. Subscription is only one input example; this does not predict individual drop-off or establish causes.

Measure how long a defined key action persists and when drop-off or exit risk rises while retaining censored observations.Needs: Survival observation duration · Drop-off or exit observed2 required columns

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