Survival analysis refers to a collection of statistical techniques used to analyze the occurrence and expected timing of events. Survival analysis can provide not only the probability of an event of interest occurring, but also the time at which the event is likely to occur. A particularly useful application of survival analysis is in the area of "customer churn"—the loss of clients or customers—which is a major concern in many industries. This note introduces survival analysis and discusses two approaches to examine customer churn: the Kaplan-Meier estimator and the Cox proportional hazards model. Instructions are provided on how to build these models in Microsoft Excel, without add-ins.

Survival analysis refers to a collection of statistical techniques used to analyze the occurrence and expected timing of events. Survival analysis can provide not only the probability of an event of interest occurring, but also the time at which the event is likely to occur. A particularly useful application of survival analysis is in the area of "customer churn"-the loss of clients or customers-which is a major concern in many industries. This note introduces survival analysis and discusses two approaches to examine customer churn: the Kaplan-Meier estimator and the Cox proportional hazards model. Instructions are provided on how to build these models in Microsoft Excel, without add-ins.