Unsubscribe rate is the metric most teams watch. This walkthrough makes the case that composition — who is leaving — often matters more than the headline churn number on email or SMS.
A never-engaged contact who signed up years ago and never bought is a very different loss than a VIP who purchases repeatedly and then opts out because cadence or content pushed them there. Same unsub rate; very different hit to future customer lifetime value.
Intuitively, not every unsubscribe hurts the same. Someone who never bought, never shared, and barely engaged is far less valuable than a brand advocate who buys multiple times — and leaves because marketing volume or creative started working against them.
If your reporting only shows “0.8% unsubscribed,” you cannot tell which story you are in. Retention risk lives in the mix of leavers, not just the percentage.
A simple model holds unsubscribe rate constant at a fairly typical ~0.8% for email, then varies only the share of unsubscribers who are high-value customers.
With dummy inputs (swap in your own), if ~24% of unsubscribes are high-value, you can see roughly $30K in projected 12-month CLV disappear with those opt-outs. Drop that high-value share to ~5% and the same unsub rate implies closer to ~$12K in projected CLV loss.
The model is intentionally simple — some of those customers may still buy through other channels — but once they leave email or SMS, you lose the primary retention levers you were using to contact them.
SMS unsubscribe rates often run higher than email, but the composition question is identical: who left, what is their average order value on SMS, and what conversion rate did that cohort historically deliver?
Adjust list size and those inputs and you get a clearer read on whether current send practices are eroding high-value SMS subscribers or mostly shedding contacts who were never carrying retention revenue.
When campaigns go out, pair baseline unsubscribe rate with a breakdown of who unsubscribed — especially high-value / VIP / recent-purchaser share. That tells you whether churn is working against the retention engine long-term, or whether the people leaving are largely ones who did not need to stay on the list anyway.
Learn more: Retention marketing strategy, Retention marketing hierarchy (article), and Book a call.
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