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SaaS Churn Rate Calculator

Enter your customer counts and MRR. See monthly churn, annual churn, revenue lost, and a severity rating - in seconds.

Enter your numbers above to see churn metrics

Know who is about to cancel - before they do

This calculator shows what you are losing. SaaS Churn Predictor scores every customer 0 to 100 so you can save the ones who still have time to stay.

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How to calculate SaaS churn rate

How do you calculate SaaS churn rate?

The standard formula is (customers lost in a period / customers at the start of the period) × 100. For monthly churn, count customers lost in one month divided by customers at the start of that month. Annual churn compounds differently - a 5% monthly rate means roughly 46% annual churn, not 60%, because each month the base shrinks.

What is a good SaaS churn rate?

It depends on your segment. Enterprise SaaS with annual contracts: 1-2% monthly is strong. SMB SaaS with monthly billing: 3-5% is common. Consumer SaaS: 5-10% is typical. The key metric is whether your churn rate lets you recoup customer acquisition cost before the customer leaves.

What is the difference between monthly and annual churn rate?

Monthly churn is the percentage of customers lost each month. Annual churn is the percentage lost over a full year. A 5% monthly churn rate does not equal 60% annual churn - it compounds to roughly 46%. The formula: annual = (1 - (1 - monthly/100)^12) × 100.

Why does my MRR churn differ from customer churn?

Customer churn treats every lost customer equally. MRR churn (or revenue churn) weighs each loss by its dollar value. If you lose one Enterprise customer and one Starter customer, customer churn counts two losses, but MRR churn shows the Enterprise loss dominates. Both metrics matter - track both.

How can I reduce my SaaS churn rate?

The highest-impact actions: (1) identify at-risk customers early with churn risk scoring, (2) reach out before the customer decides to leave, (3) address the specific reason they are at risk (payment failures, low usage, missing feature), and (4) track which interventions work so you can systematize them.