How to calculate churn rate: customer, gross and net revenue churn

“What’s our churn?” sounds like a simple question, but it has at least three correct answers depending on what you count. Customer churn, gross revenue churn and net revenue churn can tell very different stories about the same month.

This guide gives the formulas, works through each with an example, shows how to convert monthly churn to annual churn correctly, and lists the mistakes that most often distort the numbers. All examples use hypothetical numbers.

The three churn rates

Metric	What it measures	Counts
Customer churn (logo churn)	Share of customers who left	Customers
Gross revenue churn	Share of recurring revenue lost	Cancellations and downgrades
Net revenue churn	Revenue lost after expansion from remaining customers	Cancellations, downgrades and upgrades

Use customer churn to understand how many relationships you keep. Use revenue churn to understand the money. Most subscription businesses track all three.

Customer churn rate

Formula

customer churn rate =
  customers lost during the period
  ÷ customers at the start of the period

Only count customers who were there at the start. New customers who sign up during the period are not in the denominator, so they should not be in the numerator either (see the mistakes section).

Example

A company has 400 customers on March 1. During March, 20 of them cancel or are lost to failed payments, and 30 new customers sign up. On March 31 it has 410 customers.

customer churn = 20 ÷ 400 = 5.0%

The 30 new customers do not change the churn rate. They change growth, which is a different metric.

Variant: average customers

Some teams divide by the average number of customers over the period instead of the starting count:

average customers = (400 + 410) ÷ 2 = 405
customer churn = 20 ÷ 405 = 4.9%

This variant is useful when the customer base grows quickly within the period. Either method is fine; pick one and use it consistently.

Gross revenue churn

Revenue churn uses monthly recurring revenue (MRR). Annual plans are counted as one twelfth of their annual price per month.

Formula

gross revenue churn =
  (MRR lost to cancellations + MRR lost to downgrades)
  ÷ MRR at the start of the period

Gross revenue churn never includes upgrades or new customers. It can never be negative.

Example

The same company starts March with $40,000 MRR. During the month:

• Cancellations remove $2,000 MRR.
• Downgrades (customers moving to a cheaper plan) remove $600 MRR.
• Upgrades from existing customers add $1,800 MRR.
• New customers add $3,000 MRR.

gross revenue churn = (2,000 + 600) ÷ 40,000 = 6.5%

Net revenue churn

Formula

net revenue churn =
  (MRR lost to cancellations + MRR lost to downgrades
   − MRR gained from upgrades of existing customers)
  ÷ MRR at the start of the period

New customers are still excluded. Only expansion from customers who were already there at the start counts.

Example

Using the same numbers:

net revenue churn = (2,000 + 600 − 1,800) ÷ 40,000 = 800 ÷ 40,000 = 2.0%

If upgrades had been larger than losses, for example $3,000 of expansion, net revenue churn would be negative:

(2,000 + 600 − 3,000) ÷ 40,000 = −1.0%

Negative net revenue churn means the existing customer base grew in revenue even before adding new customers.

Net revenue retention

Many teams report the same information as net revenue retention (NRR):

NRR = (starting MRR − cancellations − downgrades + upgrades)
      ÷ starting MRR

    = (40,000 − 2,000 − 600 + 1,800) ÷ 40,000
    = 39,200 ÷ 40,000
    = 98%

Net revenue churn of 2% and NRR of 98% describe the same month.

When customer churn and revenue churn disagree

Suppose a hypothetical company with $50,000 MRR loses, in one month:

• Scenario A: 20 small customers paying $50 each. That is $1,000 MRR.
• Scenario B: 1 large customer paying $2,000.

If it has 500 customers at the start, scenario A is 4% customer churn and 2% revenue churn. Scenario B is 0.2% customer churn and 4% revenue churn. Neither number alone tells the full story. Report both.

Splitting voluntary and involuntary churn

Churn has two sources: customers who decide to cancel (voluntary) and customers lost because a payment could not be collected (involuntary). Splitting them matters because the fixes are completely different: product and cancel flows for the first, payment recovery for the second.

voluntary churn   = customers who canceled ÷ customers at start
involuntary churn = customers lost to failed payments ÷ customers at start

In the March example, if 14 of the 20 lost customers canceled and 6 were lost to failed payments, voluntary churn is 3.5% and involuntary churn is 1.5%. More on this in what involuntary churn is and how to reduce it.

For context, Recurly’s churn benchmarks (accessed November 2026) report an average monthly churn rate of 3.60% across industries, split into 2.34% voluntary and 1.25% involuntary. Benchmarks vary a lot by industry, price point and method, so compare against your own history first.

Converting monthly churn to annual churn

A common mistake is multiplying monthly churn by 12. Churn compounds: each month you lose a percentage of a smaller base.

annual churn = 1 − (1 − monthly churn) ^ 12

With 5% monthly customer churn:

1 − (0.95) ^ 12 = 1 − 0.540 = 46.0%

Not 60%. The difference grows as churn rises.

Monthly churn	Multiplied by 12 (wrong)	Compounded (right)
1%	12%	11.4%
2%	24%	21.5%
3%	36%	30.6%
5%	60%	46.0%

This conversion assumes the monthly rate stays constant and applies to the same cohort, which is a simplification. For annual plans, measure annual churn directly at renewal.

Cohort churn

Overall churn mixes customers of all ages. New customers usually churn faster than long-time ones, so a month with many new signups can look worse even if nothing changed.

Cohort analysis groups customers by signup month and tracks what share is still active after 1, 2, 3 months and so on.

Signup cohort	Customers	Month 1	Month 2	Month 3
January	100	88	81	77
February	120	104	96
March	90	81

These are hypothetical numbers. Reading down a column shows whether recent cohorts retain better or worse than older ones, which is the clearest way to see if product or onboarding changes worked.

Common mistakes

1. Including new customers in the numerator. If a customer signs up and cancels in the same month, they were not in the starting count. Either track them separately (often called first-month churn) or use the average-customers method consistently.
2. Including new revenue in net revenue churn. Only expansion from existing customers belongs there. New customer MRR is growth.
3. Annualizing by multiplying by 12. Use the compounding formula.
4. Mixing monthly and annual plans without normalizing. Convert all plans to MRR before calculating revenue churn.
5. Counting failed payments as churn too early, or never. A failed payment is not churn until the subscription ends. But if past-due subscriptions stay “active” indefinitely, involuntary churn disappears from your reports. Set a rule, such as counting the customer as lost when the subscription is canceled or 30 days after the final retry.
6. Counting paused subscriptions as churned (or as active) without saying so. Decide how pauses are treated and document it.
7. Changing the definition between reports. A churn rate is only useful as a trend. Write the definition down and keep it.
8. Reporting averages across very different segments. Monthly consumer plans and annual B2B contracts churn differently. Report by segment where it matters.
9. Ignoring sample size. With 40 customers, two cancellations move churn by five points. Look at multi-month trends.

A simple monthly churn report

Metric	Value
Customers at start
Customers lost (voluntary / involuntary)
Customer churn
MRR at start
MRR lost to cancellations
MRR lost to downgrades
MRR from upgrades
Gross revenue churn
Net revenue churn / NRR
Failed payment recovery rate

Fill it in the same way every month, and add a short note on anything unusual, such as a price change or a large customer leaving.

To go further, see how to find which customer attributes predict churn and the complete guide to recovering failed payments on Stripe.

How NoChurn helps

NoChurn works on both sides of churn. For involuntary churn, it recovers failed payments with smart retries, AI-written emails on day 0, 3, 7 and 14, and a hosted card update page. For voluntary churn, it runs cancel flows that match an offer to the cancel reason (discount, pause, downgrade or a call) with a one-click cancel always visible, and sends win-back emails at 30, 60 and 90 days.

You can also send your own customer attributes and usage events. NoChurn computes which ones go with churn (relative risk, sample size, confidence) and AI explains the results. Correlation, not cause. See custom data, cancel flows and pricing.