How fast are you
losing customers?

Field guide

Logo churn vs. revenue churn — they’re not the same metric.

Churn is the rate at which a business loses customers or revenue over a given period. There are two distinct ways to measure it, and conflating them leads to bad decisions.

Logo churn (customer churn)

Logo churn counts the number of customer accounts lost — ignoring how much they were paying. The formula is simple:

If you start a month with 500 customers and lose 25, your monthly logo churn is 5%. Logo churn is the most widely cited retention metric because it’s easy to measure and universally comparable across companies.

Revenue churn (MRR churn)

Revenue churn measures the percentage of monthly recurring revenue lost — from cancellations and downgrades. A company can have low logo churn but high revenue churn if its largest, highest- paying customers are the ones leaving.

Conversely, a company with high logo churn but negative net revenue churn (expansion from existing customers outpacing losses) can still grow MRR rapidly. This is the flywheel behind many enterprise SaaS companies — losing small accounts while expanding large ones.

Why monthly churn annualizes so harshly

Monthly churn compounds. A 5% monthly churn rate does not equal 60% annual churn — it actually means losing approximately 46% of your customer base per year because each month’s churn is applied to a smaller base. The formula:

This compounding effect is why even small improvements in monthly churn rate produce outsized annual results. Reducing monthly churn from 5% to 4% saves not just 1% per month — it lifts annual retention from 54% to 61%, a 7-point improvement in the customer base you keep.

B2B SaaS churn benchmarks

Churn varies enormously by segment. According to ProfitWell, Baremetrics, and ChartMogul data across thousands of SaaS companies:

• Below 1% monthly: Enterprise SaaS benchmark. Companies with multi-year contracts and embedded workflows. Salesforce, Workday, and similar platforms operate in this range.
• 1–2% monthly: Strong for B2B SMB or mid-market. Indicates solid product-market fit and effective customer success.
• 2–5% monthly: Typical for early-stage B2B SaaS. Common for products that haven’t yet invested heavily in onboarding or have competitive alternatives.
• 5–7% monthly: High. Losing more than half the customer base annually. Requires immediate investigation — often onboarding, feature gaps, or pricing mismatch.
• Above 7% monthly: Critical. The business cannot sustain growth without extraordinarily high acquisition spending. Fundamental product-market fit issues are likely.

Note: B2C SaaS benchmarks are significantly higher — 5–8% monthly is considered normal for consumer subscription products because switching costs are lower and loyalty is driven by habit rather than workflow integration.

Gross vs. net revenue retention

Net Revenue Retention (NRR) is a more powerful metric than MRR churn. It accounts for expansion revenue (upsells, seat additions) from existing customers:

An NRR above 100% means the company grows MRR from its existing customer base alone, even with some churn. Elite SaaS companies (Snowflake, Datadog, MongoDB) have historically reported NRR of 120–170%. This calculator measures gross MRR churn; to compute NRR, you’d also need expansion data.

The retention projection

The calculator’s projection section answers a critical question: given this churn rate, how many customers will you have left in N months? This uses the geometric retention model:

This assumes a constant churn rate, which is a simplification — in practice, older cohorts often churn less (survivors are sticky) and new cohorts may churn more during onboarding. Still, the constant model is the standard planning tool for SaaS forecasting.

Reducing churn: where to focus

• Onboarding. Most churn decisions happen in the first 30–90 days. A customer who reaches their “aha moment” during onboarding churns at a fraction of the rate of one who never does. Time-to-value is the leading indicator.
• Health scoring. Proactively identify at-risk accounts before they churn. Low login frequency, declining feature usage, or support ticket spikes are leading indicators.
• Customer success touchpoints. Periodic check-ins, QBRs (quarterly business reviews), and renewal conversations should be structured, not reactive.
• Exit interviews. Every churned customer is a signal. Systematic collection and tagging of churn reasons builds a product roadmap from real pain points.
• Pricing and packaging. High churn sometimes reflects value mismatch — customers don’t feel the price is commensurate with outcomes. Price-to-value alignment reduces involuntary price-sensitivity churn.