Email List Churn Calculator

Setting it out

List churn is the share of subscribers lost over a period: (unsubscribes + bounces + spam complaints + suppressed for inactivity) ÷ starting list × 100.

Transparent churn is the visible part, unsubscribes and bounces. Opaque churn is the larger part: subscribers who stop engaging without ever telling you.

Only the first appears in standard reporting, which is why most businesses underestimate churn by a wide margin.

A concrete case

A 12,000 list losing 236 unsubscribes and 180 bounces a month has 3.5% transparent churn, 42% a year, which is high but visible.

Now the opaque part: if 400 subscribers a month stop opening entirely without unsubscribing, real churn is 816 a month, or 6.8%, 81% annualised.

The list still reports 12,000 subscribers because those 400 are still on it. The engaged list is shrinking at twice the rate the reported figure suggests.

At $3.38 of annual contribution each, that hidden 4,800-a-year loss is worth $16,200 of contribution that nobody recorded going.

What the number hides

Counting only unsubscribes and bounces makes churn look manageable and makes acquisition targets too low. The list appears stable while its earning capacity falls.

Inactivity is also a judgement rather than an event, six months without an open is a reasonable definition and it is a choice, and different definitions produce very different churn figures.

Where to go from here

Define an engagement window, measure churn against it, and report the engaged list size rather than the total. That single change usually reveals a business with a substantially smaller and more valuable list than it thought.

Then set acquisition targets against total churn including the opaque part, which is typically double the visible figure.

Re-engagement, and when to let people go

A re-engagement sequence to subscribers who have gone quiet typically recovers 5% to 15% of them, which is worth running before suppression.

The rest should be suppressed rather than kept. They generate no revenue, they damage inbox placement for everyone else, and on most platforms they cost money by inflating the billed subscriber count.

Removing a large block of dormant subscribers feels like destroying an asset and is closer to writing off a bad debt: the value has already gone, and continuing to carry it costs more than the write-off. Businesses that clean regularly send to smaller lists, reach more inboxes, and generate more revenue than those that do not.

Sunset policies are worth writing down rather than improvising, since the decision to suppress a segment is easier to make in advance than in the moment.

A stated rule, re-engagement attempt at six months, suppression at nine, removes the recurring argument and keeps the list healthy without anyone having to be the person who deletes subscribers.

Win-back offers to lapsed subscribers work better than generic re-engagement, since a specific reason to return outperforms a message asking whether they still want to hear from you.

Measuring churn by cohort rather than in aggregate shows whether it is worsening, since a stable overall rate can hide newer cohorts leaving much faster than older ones.