Churn & MRR Growth Calculator
Enter one month of MRR movement — starting, new, expansion, contraction, and churned — and this page returns the full picture: ending MRR, net new MRR, growth rate, gross and net revenue churn, gross and net revenue retention, and, if you add customer counts, customer churn with the lifetime it implies. Add a target MRR to see how many months the current growth rate would take to get there.
This month's MRR movement
From customers who were not paying last month.
Upgrades from existing customers.
Downgrades. Enter as a positive amount.
Customers who left entirely.
Customer counts (optional)
Projection (optional)
Projected at this month's growth rate, held constant.
Result
Enter starting MRR (or a starting customer count) and this month’s movement to see growth, churn, and retention.
Turn the MRR story into a designed update
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Try Moda free →The five components, and why new MRR is kept out of retention
A month of MRR movement has exactly five parts: what you started with, revenue from brand-new customers, expansion from existing ones upgrading, contraction from existing ones downgrading, and churn from customers who left. Ending MRR is the sum; net new MRR is everything except the starting balance. The crucial rule is that retention metrics exclude new MRR entirely — net revenue retention asks what happened to the customers you already had, and folding new sales into it produces a number that hides a leaking bucket behind a strong sales month. This calculator keeps them separate on purpose, which is why NRR here can sit below 100% in a month where total MRR grew.
Gross churn, net churn, and NRR — three numbers, one month
Gross revenue churn is everything lost from the existing base: cancellations plus downgrades, divided by starting MRR. Net revenue churn subtracts expansion from that, so it can go negative — negative net churn is the coveted state where upgrades outpace losses. Net revenue retention is the same fact expressed the other way round, as a percentage of the base you kept: NRR above 100% and negative net churn are equivalent statements. Gross revenue retention, which ignores expansion, can never exceed 100% and is the harsher, more honest read on whether customers stay. Quote all three or quote gross retention; quoting only NRR is how a company with a real churn problem sounds healthy.
Revenue churn and customer churn move independently
They routinely disagree, and the direction of the disagreement is informative. If customer churn is high while revenue churn is low, you are losing small accounts — annoying, but survivable, and often a self-serve pricing artefact. If revenue churn is high while customer churn is low, you lost a few large accounts, which is the more dangerous version because concentration means a single logo can move the metric. That is also why a monthly churn rate on a small customer base is mostly noise: with 200 customers, one leaving moves the rate by half a point, and three leaving in the same week is not a trend.
What the months-to-target projection is worth
The projection compounds this month’s growth rate forward: months = ln(target ÷ current) ÷ ln(1 + rate). It is arithmetic, not a forecast, and it makes three assumptions that are all false — that growth stays constant, that churn does not rise as the base grows, and that this month was typical. Percentage growth in particular gets harder every month because the same percentage represents more absolute revenue. Use it as a sanity check on plausibility, not as a plan: if a target needs 14 months of your best-ever month repeated, that is worth knowing before it goes in a deck. A flat or shrinking month has no answer at all, and the calculator says so rather than printing an infinity.
Frequently asked questions
How do you calculate monthly churn rate?
For customers: churned customers during the month divided by customers at the start of the month. For revenue: MRR lost during the month divided by MRR at the start. Customers who joined and left within the same month are the classic edge case — most teams exclude them from the starting base, which is what this calculator assumes since it only asks for the starting count.
What is net revenue retention?
The percentage of last month’s revenue you still have this month, counting upgrades and downgrades from existing customers but not revenue from new ones: (starting + expansion − contraction − churn) ÷ starting. Above 100% means the existing base grew on its own. It is the single most-quoted SaaS metric and also the easiest to flatter, because including new MRR — which some dashboards quietly do — turns it into a growth number rather than a retention one.
Can net revenue churn be negative?
Yes, and it is a good thing. Negative net revenue churn means expansion from existing customers exceeded everything lost to downgrades and cancellations, so the base grows without a single new customer. It is the same statement as net revenue retention above 100%.
What is the difference between MRR growth and net revenue retention?
MRR growth includes new customers; net revenue retention deliberately does not. A month can post 8% MRR growth on the back of a strong sales push while NRR sits at 94%, meaning the existing base is shrinking and new sales are covering the gap. That combination is worth catching early — it gets more expensive every month, because the base you have to replace keeps growing.
How is customer lifetime derived from churn?
As 1 ÷ monthly churn rate: 3% monthly churn implies about 33 months. The identity assumes churn is constant month to month, which real cohorts never are — early months churn hardest — so treat it as a rough estimate rather than a measurement. At very low churn rates it becomes unstable: 0.5% implies a 200-month lifetime, which no company has actually observed. At exactly 0% there is no answer, and the calculator leaves it blank rather than printing infinity.
Should contraction MRR be entered as a negative number?
No — enter contraction and churned MRR as positive amounts. The calculator subtracts them. Entering them negative would double the sign and inflate every result, so negative values are rejected with an inline message instead of being silently accepted.