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What is churn prediction and when is it useful?
Churn prediction uses past customer behaviour to estimate who is likely to leave, so you can act before they do. It is useful for subscription or repeat-purchase businesses with enough customer history and the ability to run retention actions. Without a retention action, predictions add little.
Before building a model, check that you can define churn clearly, for example no purchase in 90 days, and that you track relevant behaviour.
Often a simple analysis of what leaving customers have in common gives most of the insight. A model adds value when you have many customers and need to prioritise limited retention effort. Without a response plan, the prediction has no benefit.
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