Survival Analysis For Customer Retention
Illustrates how retention can be better modelled using a survival function like Kaplan–Meier survival curves.
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How to project customer retention faculty.wharton.upenn.edu
A seminal paper, with a stronger approach compared to the one above: the exponential distributions is replaced by a geometric model, which is better suited to discrete time intervals like monthly contracts, the former being more appropriate to continuous time process.
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“On the surface, churn rate may seem like a natural proxy for changes in customer lifetimes. Let's dig into why that is not true.” Churn rate is not a meaningful metric to compute CLV: during the customer lifetime, the churn probability is not constant. Most of the time because…
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Billing › Business Intelligence > Customer Lifetime Value: “Illustrates how retention can be better modelled using a survival function like Kaplan–Meier survival curves.”