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How can a small company improve customer retention using data?
Find which customers are leaving, when, and what they had in common before they left, then act early on those signals. Useful data includes purchase frequency, time since last order, support complaints, discounts used and product mix. Test any retention offer on a small group before rolling it out widely.
Start with simple analysis: retention by cohort, by first product bought, by acquisition channel and by region. Often one or two patterns explain most of the loss.
A churn model can then rank current customers by risk, but only helps if someone acts on the list. Decide in advance what the action is, such as a call, an offer or a service fix, and measure whether treated customers stay longer than a comparable untreated group. Otherwise you cannot tell whether the action worked.
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