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Churn Rate Calculator

Enter Customers at start of month, Customers lost during the month and MRR at start of month plus 2 more inputs — every figure updates as you type. Nothing you type leaves your browser.

How do you calculate Churn Rate?

Customer churn rate is the number of customers who cancelled during a period divided by the number active at the start of that period, expressed as a percentage. This calculator returns customer churn, gross revenue churn and net revenue churn side by side, plus the annualised rate and the implied average customer lifetime.

Customer churn rate

2.4%

Share of customers lost this month.

Gross revenue churn: 1.8%Share of starting MRR lost, before any expansion.
Net revenue churn: -0.9%After expansion. Negative is good — you grew without new customers.
Annualised customer churn: 25.7%Compounded over twelve months, not multiplied by twelve.
Implied average lifetime: 41Months, as 1 ÷ monthly churn. Shows 0 when churn is 0.

Results are rounded for display; the calculation runs at full precision.

The maths

How Churn Rate is calculated

The formula this calculator runs, written out so you can check it against your own model rather than trust a black box.

Customer churn = (customers lost ÷ customers at start) × 100

customers lost: Customers active at the start of the period who were no longer paying at the end. Customers who joined and left inside the same period are excluded from both sides.
customers at start: Active paying customers on day one. Trials, free plans and 100%-coupon accounts are not counted.
net revenue churn: (churned MRR − expansion MRR) ÷ starting MRR × 100. Goes negative when expansion outruns losses.

Reading the result

What the number is telling you

Bands are directional, not verdicts. Stage, price point and contract length move every one of them, so treat these as a starting point for the conversation rather than a grade.

Under 1% monthly: Strong retention — roughly 11% annualised. Typical of mid-market and enterprise contracts, or products embedded deeply enough in a workflow that leaving is expensive. At this level growth compounds efficiently and acquisition spend keeps paying back long after the sale.
1 – 3% monthly: Healthy for SMB and self-serve SaaS, and where most subscription businesses live. Around 12% to 31% annualised. Worth splitting into voluntary and involuntary before optimising: if failed payments are a large share, dunning recovers revenue faster than any product change.
3 – 5% monthly: Elevated. Roughly 30% to 46% of customers gone in a year, so acquisition is largely replacing losses rather than adding growth. Usually one of three causes — weak onboarding, a mismatch between the customers you acquire and the ones the product serves, or unaddressed involuntary churn.
Over 5% monthly: Above 45% annualised, which makes durable growth arithmetically very difficult: you replace half the business each year before growing at all. Treat it as a product or fit problem rather than a marketing one, and look at first-90-day retention by cohort before spending anything further on acquisition.

Three churn rates, three different answers

The defaults above are deliberately ordinary, and they produce three figures that point in different directions: customer churn near 2.4%, gross revenue churn near 1.8%, net revenue churn slightly negative. All three are correct. They disagree because they measure different things.

Customer churn counts logos. Every customer weighs the same, so it is the right lens for support load, onboarding capacity and product fit.
Gross revenue churn weights by money. When it sits below customer churn, your smaller customers are leaving — usually the healthier pattern.
Net revenue churn subtracts expansion. When it is negative, the customers who stayed grew more than the leavers cost you, and revenue rose without a single new customer.

Quote one number without the others and you can tell almost any story. Report all three.

Annualise by compounding, never by multiplying

The monthly churn of 2.44% above is not 29.3% a year. Each month's loss applies to a base already reduced by the previous month, so the correct annualisation compounds: 1 − (1 − 0.0244)¹² ≈ 25.7%. Multiplying by twelve overstates the damage, and at higher rates it produces figures above 100% — which should be a clue that the arithmetic is wrong.

The implied lifetime figure inverts the same rate: at 2.44% monthly, an average customer stays roughly 41 months. Treat it as a rough planning input rather than a fact. It assumes a constant hazard rate, and real churn is heavily front-loaded — most cohorts lose a disproportionate share in the first ninety days and then settle.

The definitions that decide the number

Churn is the metric most sensitive to definitional choices, and small decisions move it by a percentage point or more:

Delinquency window — how long a failed-payment subscription stays alive before it counts as churn. Thirty days is the common default; a longer window flatters this month at the expense of next.
Annual plans — an annual subscriber cannot churn until renewal, so measuring them on a 30-day window hides them entirely. Use a 365-day lookback for annual cohorts and report them separately.
Involuntary churn — failed cards rather than cancelled intent. It typically accounts for a substantial share of total churn and is the most recoverable kind. Track it separately, because the fix is dunning, not product.
Same-period signups — a customer who joined and left within the period should be excluded from both numerator and denominator, or you punish the month for a customer it never really had.

Bastle makes each of these a workspace setting and recalculates history when you change one, and every resulting figure carries the formula and the records behind it. A versioned record of who changed which setting and when is on the roadmap, so for now keep your own note of a change if a churn figure quoted last quarter has to be defended later.

Definition

Where Churn Rate gets argued about

A calculator settles the arithmetic, not the definition — and the definition is where most disagreements about this number actually live. The glossary entry covers the conventions, the edge cases and how Bastle handles each one.

Read the Churn Rate definition Browse the metric glossary

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Frequently asked questions

What is a good monthly churn rate for SaaS?

It depends almost entirely on who you sell to. Self-serve and SMB products commonly run between 1% and 3% monthly, while mid-market and enterprise businesses with annual contracts typically sit below 1%. Rather than chasing a universal benchmark, compare against your own trend and against companies with a similar contract length and customer size — a 2% rate is unremarkable for SMB and alarming for enterprise.

How do I calculate annual churn from monthly churn?

Compound it rather than multiplying: annual churn = 1 − (1 − monthly rate)¹². At 2% monthly that gives 21.5% annually, not 24%. Multiplying by twelve consistently overstates the loss because it ignores that each month's churn applies to a base already shrunk by the months before it.

Should churn include customers who failed payment?

Yes, once they pass your delinquency window — usually thirty days — but track them separately as involuntary churn. Failed payments are typically a large share of total cancellations and are the most recoverable kind, since the customer never intended to leave. Mixing them into a single headline number hides the fact that a meaningful portion is fixable with retries and card-update prompts.

What is the difference between customer churn and revenue churn?

Customer churn counts departing customers regardless of size; revenue churn weights each departure by the MRR it took with it. When revenue churn is lower than customer churn, you are losing mostly small accounts. When it is higher, you are losing your larger ones — a materially worse situation that a customer-count view would understate.

Can churn rate be negative?

Customer churn cannot — you cannot lose fewer than zero customers. Net revenue churn can, and negative net revenue churn is the goal: it means expansion from existing customers exceeded everything lost to downgrades and cancellations, so revenue from your existing base grew on its own. That is the same condition as net revenue retention above 100%.

How do annual contracts affect churn measurement?

They suppress it artificially in any short window. An annual subscriber has no opportunity to cancel for twelve months, so a 30-day churn calculation counts them in the denominator while they are structurally incapable of appearing in the numerator. Measure annual cohorts on a 365-day lookback and report them separately from monthly ones, or the blended figure will flatter you until the first renewal wave arrives.

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