A projection is only useful if it subtracts. Add eight customers a month to a base losing seven and the line looks like growth until you plot it.
Twelve months, accounting for churn. Most projections fail because they add new customers without subtracting the ones leaving.
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An MRR projection is only useful if it subtracts. Add eight customers a month to a base that loses seven and the line looks like growth until you plot it — which is the single most common reason a plan and reality diverge.
At a fixed acquisition rate and a fixed churn rate, your MRR does not grow forever. It converges on a ceiling, and the arithmetic is simple: new customers per month ÷ monthly churn rate gives you the customer count where additions and losses cancel out.
Eight new customers a month at 8% monthly churn converges at a hundred customers. Not eventually — that is the maximum, regardless of how long you run. Doubling acquisition to sixteen a month moves the ceiling to two hundred. Halving churn to 4% also moves it to two hundred, and is usually the cheaper of the two.
The calculator shows this figure directly. Founders who have never computed it are often surprised to find they are already close to it, which explains a plateau better than any marketing diagnosis.
Three assumptions this model makes that will not hold exactly.
Churn is constant. It usually is not — early cohorts churn faster than mature ones, so a blended rate overstates losses among long-standing customers and understates them among new ones.
Acquisition is constant. Solo acquisition is lumpy. A launch, a mention, or a quiet fortnight all move the monthly figure more than a model can capture.
ARPU is constant. With no expansion revenue this holds, which is itself the problem — the value metric framework covers building a structure where revenue can grow without customer count growing.
Use the projection to compare scenarios rather than to predict a number. The difference between a 4% and an 8% churn scenario is real information; the exact MRR figure in month nine is not.
| Change | Effect on the ceiling | Usually costs |
|---|---|---|
| Halve churn | Doubles it | One-time fixes, mostly onboarding |
| Double acquisition | Doubles it | Ongoing effort every month |
| Raise price 25% | No change to ceiling, +25% MRR | One notification cycle, some churn |
The first two produce the same ceiling and cost very differently. Retention fixes tend to be one-time work that keeps paying; acquisition has to be sustained every month, which is the harder ask for a solo founder — retention versus acquisition covers the trade-off in more detail.
The third row is the one founders under-use. A price increase moves revenue without touching either input, and the price increase playbook covers doing it without losing your base.
Run the model with your actual churn rather than the rate you hope to reach. A projection built on an aspirational number is a plan, not a forecast, and the gap between them is where founders lose two quarters.
Flat output at a healthy acquisition rate means churn is consuming your additions, and that is arithmetic rather than a marketing problem. Diagnose the type before acting — the churn reduction framework sorts cancellations into five types using two data points you already have.
If your rate itself looks high, the churn benchmark check interprets it against bands for your price point. And for the wider diagnosis when growth has stopped entirely, breaking the MRR plateau covers the causes in order.
Start from your current customer count, then each month subtract churn and add new customers, multiplying the result by ARPU. The common error is adding new customers without subtracting churn, which makes a flat business look like it is growing.
At a fixed acquisition and churn rate, MRR converges on a maximum rather than growing forever. The customer count where additions and losses cancel is new customers per month divided by monthly churn rate — eight new at 8% churn converges at a hundred customers.
They move the ceiling identically — halving churn and doubling acquisition both double it. They cost very differently: retention fixes are mostly one-time work that keeps paying, while acquisition must be sustained every month.
Useful for comparing scenarios, unreliable for predicting a specific figure. The model assumes constant churn, constant acquisition and constant ARPU, and none of those holds exactly for a solo product where acquisition is lumpy.
Almost always because churn is consuming your additions. That is arithmetic rather than a marketing problem, and the fix is diagnosing which of the five churn types you have before changing anything about acquisition.
Bring your MRR, churn and acquisition rate. Marcus names whether retention or acquisition is your binding constraint.
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