SaaS metrics

Churn Rate Calculator

Calculate customer churn, revenue churn and average customer lifetime, then project the next twelve months of your customer base. Churn is the metric that compounds against you, so the projection matters more than the single-month rate.

Monthly customer churn rate

Good

3.00%

In line with well-run SMB SaaS. A 2% monthly rate implies a ~50-month average lifetime.

Compounded for a year, 3.00% monthly churn leaves 347 of 500 customers — 69.4% retention.

Customer churn: 3.00%
Revenue churn: 4.00%
Avg. customer lifetime: 33.3 months
Customers after 12 months: 347
12-month retention: 69.38%
MRR lost per year: $11,760

Compounding projection using the current monthly churn rate. Each month keeps the same percentage of the previous month's customers.

View chart data as a table

Month	Customers remaining
Month 1	485
Month 2	470
Month 3	456
Month 4	443
Month 5	429
Month 6	416
Month 7	404
Month 8	392
Month 9	380
Month 10	369
Month 11	358
Month 12	347

Revenue churn exceeds customer churn. You are losing fewer customers than you are losing dollars, which usually means your largest accounts are the ones leaving — or that downgrades are concentrated in your highest-value plans.

Monthly churn rate benchmarks

Monthly customer churn is the single most destructive metric in SaaS because it compounds. The difference between 2% and 5% monthly churn is roughly a 50-month average lifetime versus a 20-month one — on identical acquisition spend.

Segment	Typical monthly churn	Best-in-class
SMB self-serve (< $50/mo) Low switching costs and card-optional trials drive the high end.	3% - 7%	< 3%
SMB sales-assisted ($50 - $500/mo) The band most bootstrapped and seed-stage SaaS companies sit in.	2% - 4%	< 2%
Mid-market ($500 - $2k/mo) Onboarding quality shows up here more than pricing does.	1% - 2%	< 1%
Enterprise (> $2k/mo) Measured annually in most enterprises; monthly figures get noisy.	0.5% - 1.5%	< 0.5%
Annual contracts (any size) Renewal-date clustering makes monthly numbers spiky — read the yearly figure.	0.5% - 1%	< 0.5%

Churn bands are drawn from the benchmark ranges published by OpenView, ChartMogul and ProfitWell. Segment by plan and by acquisition channel before acting on a blended number.

Frequently asked questions

What is a good monthly churn rate for SaaS?

It depends entirely on your segment. Self-serve SMB products commonly run 3% to 7% per month, sales-assisted SMB around 2% to 4%, mid-market 1% to 2% and enterprise under 1.5%. A blended target of under 3% monthly is a reasonable goal for an early-stage B2B product, but the honest comparison is against your own segment and your own trend.

What is the difference between customer churn and revenue churn?

Customer churn counts logos lost as a share of logos at the start of the period. Revenue churn counts dollars of MRR lost as a share of starting MRR, and includes downgrades. They routinely diverge: if your smallest customers churn most, customer churn runs ahead of revenue churn, which is a much better position than the reverse.

What is negative revenue churn?

When expansion revenue from existing customers exceeds churn and contraction, net revenue churn is negative — the existing base grows without any new customers. This is the strongest possible retention signal and is common in seat-based products where usage grows over time. It means MRR would rise even if acquisition stopped entirely.

How do I convert monthly churn into customer lifetime?

Divide 100 by the monthly churn rate as a percentage. A 4% monthly churn rate implies a 25-month average customer lifetime. This assumes a constant churn rate, which real cohorts violate — churn is usually highest in the first 90 days, so early-life churn disproportionately shortens the true average.

Should I include involuntary churn?

Yes, for a complete picture. Involuntary churn is revenue lost to failed payments and expired cards, and in self-serve businesses it is often 20% to 40% of total churn. It gets left out because it is invisible in a CRM, but it is real and, unlike voluntary churn, it is usually fixable with dunning emails and card-updater services.

Is monthly churn or annual churn the right measure?

Both, and they do not convert linearly. Subtracting twelve times the monthly rate is wrong: 5% monthly churn compounds to roughly 46% of the base lost over a year, not 60%. Use the monthly rate for early-warning signals and the annual rate for cohort and LTV work.

How churn is calculated (and why it compounds)

The formula

customer churn rate = customers lost / customers at start * 100
revenue churn rate  = MRR lost / MRR at start * 100
average lifetime    = 100 / customer churn rate
projection month N  = starting customers * (1 - churn rate)^N

The exponent in the last line is the part people underestimate. Churn does not remove a fixed slice of your original base each month; it removes a slice of whatever is left. At 5% monthly churn, after twelve months you keep 0.95^12 = 54% of your customers, not 40%. After twenty-four months you keep 29%.

A worked example: 500 customers losing 15 a month is a 3% monthly churn rate and a 33-month average lifetime. Compounded over a year, 500 customers become 500 × 0.97^12 = 347 — a loss of 153 customers that looks small month by month and is enormous annually. You would need to acquire 153 customers just to stand still.

Customer churn vs revenue churn

These two numbers should be read together, and their relationship matters more than either in isolation:

Revenue churn below customer churn — the customers you keep pay more than the ones you lost. This is the healthy pattern, and if expansion outweighs it entirely you have negative revenue churn.
Revenue churn above customer churn — you are losing fewer logos but more dollars, which almost always means your largest accounts are leaving. That is materially worse than the logo count suggests, and it is invisible if you only track customer churn.

Common mistakes

Dividing by the ending customer count. Churn is measured against the start of the period. Using the (smaller) end-of-period base inflates the rate, and using the average can understate it when growth is fast.
Annualising by multiplying by twelve. 5% monthly is about 46% annually, not 60%. Compounding is not optional.
Excluding involuntary churn. Failed payments are real churn. Leaving them out flatters the number and hides the fastest fix available to you.
Reporting a blended rate. A single number averages a 1% enterprise cohort with a 9% self-serve cohort and tells you nothing actionable about either. Segment by plan and by acquisition channel.
Ignoring the first 90 days. Early-life churn is typically several times the steady-state rate. If your cohort curves never flatten, the problem is onboarding, not the product.

What to do about a bad number

Retention is cheaper to fix than acquisition is to buy. A 3% monthly churn rate implies a 33-month lifetime; 2% implies 50 months. That difference raises LTV by more than 50% at constant ARPU, which flows straight into the LTV:CAC ratio without any additional sales and marketing spend. Fixing involuntary churn, improving onboarding, and annual plans — which convert monthly churn into an annual renewal decision — are the highest-leverage levers in most early-stage SaaS businesses.

Related calculators

Churn drives customer lifetime, which drives LTV. It also determines the denominator of the SaaS quick ratio and how quickly you can reach breakeven on the runway calculator.

How the churn formula is derived

Step 1 — churn as a fraction of the opening base

Churn is a rate, and a rate needs a denominator. The correct one is the base at the start of the period, because those are the customers who were at risk of leaving:

customer churn % = customers lost / customers at start × 100
revenue churn %  = MRR lost / MRR at start × 100

Using the ending base inflates the rate (the base is smaller after the losses), and using the average is ambiguous in a fast-growing business. Start-of-period is what the published benchmarks mean, so this calculator uses it — otherwise your number would not be comparable with the table above it.

Step 2 — from a monthly rate to a lifetime

If a constant fraction c of the surviving base leaves each month, the proportion still present after m months is (1 - c)^m, and the mean of that distribution is where the lifetime formula comes from:

average lifetime (months) = 100 / churn rate %

This is the same identity the LTV calculator uses, deliberately, so the lifetime implied by your churn rate is identical on both pages.

Step 3 — compounding, not multiplying

Churn removes a slice of whatever remains, not a slice of the original base, so projecting forward is exponentiation rather than repeated subtraction:

customers after N months = starting customers × (1 - churn rate)^N

At 5% monthly, 0.95^12 = 0.54: you keep 54% of the base after a year, not 40%. That gap between multiplying by twelve and exponentiating is the single largest source of over-optimistic retention plans, and it is why this page shows a twelve-month curve rather than only the headline rate.

Assumptions and where this breaks

Every model is wrong somewhere. These are the assumptions baked in here, and the situations in which you should not trust the number that comes out.

Assumes

The denominator is the customer count (or MRR) at the start of the period, not the end and not the average. Start-of-period is the standard definition and the one the benchmarks assume.
The period is exactly one month, so that the compounding maths below is consistent with a monthly rate.
Customer churn counts logos and revenue churn counts dollars, including downgrades as dollars lost. The two are reported separately and never blended into one number.
Involuntary churn from failed payments is included. It is real revenue loss and excluding it flatters the figure.

Does not apply when

Your churn is lumpy rather than smooth. One enterprise renewal can dominate a month; the monthly rate then says more about renewal timing than about retention.
You are pre-product-market-fit. Churn in the first year of a product is dominated by a mis-targeted acquisition channel, and the steady-state rate is not yet measurable.
The cohort is very young. Average lifetime of 100 ÷ churn assumes a mature, flat hazard rate; cohorts younger than about six months have not yet revealed their curve.
You want a single blended figure to report. A blended rate averages a 1% enterprise cohort with a 9% self-serve cohort and describes neither — segment by plan and by channel before acting.
The comparison is against another company’s published churn. Definitions differ (logos versus revenue, voluntary versus gross) and a small definitional difference easily accounts for a two-point gap.

Edge cases handled explicitly

Churn of 0% produces an infinite lifetime; the calculator labels it rather than inventing a large finite number.
Monthly and annual churn are never converted by multiplying or dividing by 12 — 5% monthly compounds to roughly 46% annually, not 60%, and the projection is done by exponentiation.
A customer who downgrades rather than cancelling appears in contraction, not in churn, so the same customer is never counted twice.

Where the benchmark numbers come from

The bands in the table above are drawn from the following published sources. They are orientation figures published for the whole industry, not a proprietary dataset and not a target — your own segment, stage and three-month trend matter more than any published band.

OpenView Partners: Their annual SaaS benchmarks report churn and retention by segment, which is the basis of the segment bands shown here.
ChartMogul: Their writing sets out the customer-versus-revenue churn distinction this page is built around, and the correct start-of-period denominator.
ProfitWell: Publishes research on the share of churn that is involuntary (failed cards) and on dunning recovery, referenced in the assumptions below.

Where no single institution publishes a figure, this page says so and labels it commonly cited rather than attributing it to a named firm. Nothing on this site is presented as proprietary data we collected.

These six tools are designed to be read as one chain, not six separate numbers:

LTV:CAC → CAC Payback → Quick Ratio → MRR → Churn → Runway

Each tool in the chain is a pure function of the ones before it, which is why the six share one formula module and one set of benchmark bands — the same inputs on different pages cannot disagree here.

Maintained by The SaaS Metrics Calculators Editorial Team

Maintained by the site’s editors, with every formula unit-tested and every benchmark traced to a published source

Formulas and benchmarks last reviewed October 2026.

This page is educational. Every figure is computed in your browser from the inputs you supply, and nothing is checked against your own accounts — treat results as a planning aid, not as financial advice.