What is a normal churn rate on Skool?

By Christopher Ward, Co-founder, SkoolgradesPublished

Short answer

There is no published benchmark for churn on Skool, and anyone quoting one is guessing. Monthly churn is cancellations divided by members at the start of the month. What counts as normal swings with your price, niche, community age, and whether members joined free or paid. The only useful comparison is your own community against its own last six months.

You will find articles that confidently tell you the average churn rate for a Skool community. They are making it up. No credible published benchmark exists for churn specifically on Skool, and we are not going to invent one here — a fake number would give you a target that has nothing to do with your community and would either panic you or falsely reassure you.

What does exist is a formula, a set of choices about what goes in the denominator, and a method for building a baseline you can actually trust. That is what this page is.

How do I actually calculate my churn rate?

Monthly churn rate is cancellations divided by the members you started the month with, multiplied by 100, and the arithmetic is the easy part:

Members who cancelled during the month, divided by members you had at the start of the month, times 100.

If you started March with 200 paying members and 14 cancelled, that is 14 divided by 200, which is 7 percent for that month.

The formula is trivial. The choices around it are not, and they are where most people's numbers stop being comparable to anyone else's.

Choice one: who is in the denominator

Do you count everyone in the community, or only people paying you? If your community has both a no-cost level and a paid level, mixing them produces a number that means nothing — free members leave for completely different reasons and at completely different rates.

Count paid churn and free churn separately. Always.

Choice two: what counts as a cancellation

  • A member who cancels but stays until the end of their billing period — do you count them the day they cancel, or the day access ends?
  • A failed payment that never recovers — churn, or a billing problem?
  • A member you removed for breaking the rules — that is not churn, that is you.
  • An annual member who does not renew — they churn once a year, so folding them into a monthly rate distorts it.

None of these has a right answer. There is only a consistent answer. Pick your definitions, write them down, and never change them mid-comparison.

Choice three: the window

Monthly is standard because most subscriptions are monthly. But in a small community, one month is mostly noise. If you have 60 members, one person leaving moves your rate by 1.7 points. Three people leaving in a bad week can look like a crisis and be nothing.

Small communities should look at a rolling 90-day rate alongside the monthly one. The rolling number tells you the trend; the monthly number tells you whether something happened.

Why can't I just compare my churn to the Skool average?

A Skool-wide churn average is meaningless to you because four variables move churn so hard that any cross-community figure is arithmetic on unrelated things.

VariableEffect on churn
Price pointA $9/mo community and a $497/mo mastermind churn for entirely different reasons and at entirely different scales
Free vs paid entryFree members leave with zero friction; paid members had to make a decision to stay
NicheA skills course with a natural finish line churns by design; an ongoing peer group does not
Community ageA community six weeks old is nearly all new joiners, which is the highest-risk tenure band there is

Add a fifth: whether your last cohort came from ads or from your own audience. Cold traffic churns differently from people who already knew you.

So when someone tells you "the average is X percent", ask which of those five they controlled for. The honest answer is none of them.

If you take one thing from this page: your only meaningful benchmark is your own community six months ago.

How do I build a churn baseline for my own community?

You build a churn baseline by logging the same three numbers every month until you have six months of them, using a method that takes about twenty minutes to set up and five minutes a month to maintain.

  1. Pick your definitions. Paid only. Cancellation counted on the day access actually ends. Removals excluded. Annual members tracked separately. Write this in a note.
  2. Record the starting count on the first of each month. One number. Just the paid roster.
  3. Record cancellations during the month. One number.
  4. Compute the rate and log it. A spreadsheet with three columns beats any dashboard here, because the discipline is the point.
  5. After three months you have a range. After six you have a baseline. Now a month that lands outside the range means something.
  6. Annotate the outliers. When a month spikes, write down what happened — a price change, a launch, a long silence from you, a bad onboarding week. That annotation is worth more than the number.

The first three months will feel useless. Do them anyway. A baseline you built yourself is the only churn figure that will ever tell you something true.

Why doesn't churn rate help me save members before they go?

Churn rate cannot save an individual member because it is a lagging indicator: by the time a cancellation shows up in your count, the decision was made weeks earlier. Nobody cancels the day they lose interest. They stop opening the community, then stop reading, then stop noticing, and eventually a payment reminder lands and they act on a feeling they have already had for a month.

So a churn rate is a report card on a period you can no longer influence. Useful for spotting whether something structural broke. Useless for saving the individual member.

What you actually want to watch is the thing that happens before the cancellation: a member's activity falling off relative to their own past. Someone who commented three times a week for four months and has now been quiet for two weeks is a different situation from someone who has always been quiet. The first is drift. The second is just who they are.

Define "activity" carefully or you will miss the drift entirely. Skoolgrades defines it as participation — comments, comment replies and poll votes, never a page load — which is why its figure runs below a visit-based engagement rate (the reason that matters). A drifting member stays invisible in a visit-based figure right up until they cancel.

That is why spotting members who are about to leave is a separate job from measuring churn, and the more valuable one.

Should I split my churn rate by how long members have been here?

Splitting churn by tenure is the single most useful cut you can make, because not all churn is the same churn and how long someone has been a member changes what their leaving means.

Skoolgrades resolves member lifecycle across six lanes and three tenure bands — newly joined at 14 days or less, mid at 15 to 90 days, and long-tenured beyond 90 days. The reason for splitting it that way is that the three bands fail differently:

  • Newly joined churn is an onboarding problem. They never got in. Nothing about your ongoing content caused it.
  • Mid-tenure churn is a value problem. They looked around, participated a bit, and did not find the thing that would make it a habit.
  • Long-tenure churn is usually completion or drift. They got what they came for, or life moved.

A single blended churn number hides all three. If your rate ticks up and you do not know which band moved, you will fix the wrong thing. Splitting churn by tenure is the highest-leverage thing you can do with the number after you have started tracking it at all.

The same split tells you where to spend effort. Newly-joined churn is the cheapest to fix, because the window is short, the cause is usually structural, and the fix is the same for everyone. See how to reduce churn and member retention for what to actually do about each band.

So what is a normal churn rate for my community?

There is no normal churn rate on Skool because there is no normal Skool community. Compute your own with definitions you write down, track it monthly for six months until you have a range, split it by tenure so you know which failure you have, and treat the number as a smoke alarm rather than a steering wheel. The steering happens earlier, in the behavior that precedes the cancellation.

And be suspicious of any article, tool, or coach who hands you a benchmark percentage. They do not know your price, your niche, your age, or your traffic source, and those are the whole answer.

Frequently asked

How do I calculate churn rate for my Skool community?
Divide the number of members who cancelled during a month by the number of members you had at the start of that month, then multiply by 100. If you started with 200 paying members and 14 left, that is 7 percent for the month. Count paid and free members separately, because they leave for completely different reasons.
What is the average churn rate for a Skool community?
No credible published benchmark exists for churn on Skool specifically. Rates vary enormously with price point, niche, community age, and whether members joined free or paid, so any single average would be comparing unrelated things. Build your own baseline over three to six months and compare your community against its own history instead.
Should I count free members in my Skool churn rate?
Track them separately. Free members leave with no financial friction and often without ever deciding to leave at all, so blending them with paid cancellations produces a number that hides both signals. Two rates, tracked side by side, tell you far more than one combined figure ever will.
Is monthly or annual churn the better measure for a small community?
In a community under about a hundred members, a single month is mostly noise, because one person leaving can swing the rate by more than a point. Track the monthly number for events, but read a rolling 90-day rate for the trend. Annual members should be tracked separately since they can only churn once a year.
Why does churn rate not help me save individual members?
Because it is a lagging indicator. By the time a cancellation registers, the member decided weeks earlier and drifted quietly in between. Churn rate is good for detecting that something structural broke. Saving a specific person requires watching their activity fall off relative to their own past behavior, well before the payment date.
Does Skoolgrades predict which members will churn?
No. Skoolgrades has no predictive churn model and no backtested forecasts, and its snapshot history is deliberately shallow. What it does is surface behavioral signals of drift, meaning a member whose activity has fallen off relative to their own past, and place every member in a lifecycle lane across three tenure bands so you can see where attention is needed.
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Last updated 2026-07-29. Skoolgrades is an independent tool and is not affiliated with or endorsed by Skool.