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Read the postProfit Intelligence
Churn rate (also called attrition rate, customer churn, or revenue churn) is the rate at which customers cancel or revenue is lost over a defined period. There are two types: logo churn (percentage of customer accounts lost) and revenue churn (percentage of MRR lost). Both matter. They often tell different stories.
Churn is the gravitational force working against every SaaS business. New sales add revenue. Churn takes it away. The gap between the two determines net growth. A company adding $100K in new MRR per month with 3% monthly churn on a $2M base loses $60K — keeping only $40K net. At 1% churn, it keeps $80K. That difference compounds every month.
For B2B SaaS companies at $3-15M ARR, churn becomes the dominant constraint on growth. At this stage, the base is large enough that even moderate churn rates consume a significant portion of new sales effort. Companies with monthly revenue churn above 2% find that 40-60% of their new business just replaces what they lost.
Logo churn and revenue churn can diverge significantly. If small customers churn at 5% but large customers churn at 1%, logo churn will be high while revenue churn might be low. Revenue churn is the more important metric for financial planning. Logo churn is more important for understanding product-market fit across segments.
Churn determines LTV, NRR, and ultimately company valuation. A 1-point reduction in monthly churn extends average customer lifespan by years and increases LTV proportionally. This makes churn reduction the highest-leverage activity in most SaaS companies.
Without granular churn tracking, operators can't diagnose why customers leave. "We have 2.5% monthly churn" is a fact, not an insight. The insight comes from decomposing it: which segments churn fastest? Which cohorts? At what point in the customer lifecycle? Customers who churn in month 2 have a different problem than customers who churn in month 14.
A typical mid-market SaaS company discovers three patterns when they first decompose churn: most churn concentrates in the first 90 days (onboarding problem), one customer segment churns 3x faster than others (fit problem), and churned customers had 40% fewer product interactions in their last 30 days (engagement problem). Each pattern requires a different fix.
Logo Churn Rate (monthly):
Logo Churn = Customers Lost in Month / Customers at Start of Month x 100
Example:
- Starting customers: 450
- Customers lost: 12
Logo Churn = 12 / 450 x 100 = 2.67%
Revenue Churn Rate (monthly):
Revenue Churn = MRR Lost to Cancellations / MRR at Start of Month x 100
Example:
- Starting MRR: $680,000
- MRR lost to cancellations: $11,560
Revenue Churn = $11,560 / $680,000 x 100 = 1.70%
Net Revenue Churn (including expansion):
Net Revenue Churn = (Churn MRR + Contraction MRR - Expansion MRR) / Starting MRR x 100
If expansion exceeds churn + contraction, net revenue churn is negative — meaning negative churn, the ideal state.
What each type means:
| Segment | Monthly churn (good) | Monthly churn (average) | Monthly churn (concerning) | Annual equivalent |
|---|---|---|---|---|
| Enterprise SaaS (>$100K ACV) | <0.5% | 0.5-1.0% | >1.5% | <6% / 6-12% / >17% |
| Mid-market SaaS ($25-100K ACV) | <1.0% | 1.0-2.0% | >2.5% | <12% / 12-22% / >26% |
| SMB SaaS (<$25K ACV) | <2.0% | 2.0-3.5% | >4.0% | <22% / 22-35% / >39% |
| D2C / E-commerce subscriptions | <3.0% | 3.0-6.0% | >8.0% | <31% / 31-53% / >63% |
| Usage-based SaaS | <1.0% | 1.0-2.0% | >3.0% | <12% / 12-22% / >31% |
Sources: ChartMogul SaaS Benchmark Data 2025 (n=2,600), Recurly Research SaaS Churn Index 2025, Bessemer Cloud Index 2025.
Note: SMB churn is structurally higher because small businesses fail, pivot, and outgrow tools faster than larger companies. This is not always a product problem.
1. Measuring only logo churn and ignoring revenue churn
A company with 3% logo churn might have 1% revenue churn (small accounts leaving) or 5% revenue churn (large accounts leaving). The financial impact is completely different. Track both — but make decisions based on revenue churn.
2. Measuring churn annually instead of monthly
Annual churn hides monthly trends. A company with 18% annual churn might have had 1% monthly churn in H1 and 2.5% in H2 — meaning churn is accelerating. Monthly measurement catches problems 4-6 months faster.
3. Not segmenting churn by cohort
Blended churn rates hide cohort-specific problems. If the January cohort churns at 4% monthly but the April cohort churns at 1.5%, something changed (better onboarding? better ICP targeting?). Without cohort analysis, the improvement is invisible.
4. Excluding downgrades from churn analysis
A customer who drops from $5,000/month to $1,500/month didn't churn — but you lost $3,500 in MRR. Track contraction alongside churn. Combined, they give you the full picture of GRR (gross revenue retention).
5. Treating all churn as a product problem
Some churn is structural: the customer went out of business, got acquired, or outgrew your product tier. Some is preventable: poor onboarding, missing features, or competitor displacement. Categorize churn reasons to know which type to address.
Fairview's Operating Dashboard connects to your CRM and payment processor (Stripe) to track both logo churn and revenue churn in real time — segmented by cohort, plan type, and customer segment.
The dashboard surfaces churn trends and flags acceleration: "Monthly revenue churn increased from 1.2% to 1.9% over the last 3 months. Largest contributor: Growth plan customers with <30 days since last login." The Forecast Confidence Engine factors churn trends into forward revenue projections, so forecasts account for expected churn — not just new pipeline.
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| Churn Rate | NRR (Net Revenue Retention) | |
|---|---|---|
| What it measures | Revenue or customers lost | Revenue kept + gained from existing customers |
| Includes expansion | No (gross churn) or Yes (net churn) | Always yes |
| Direction | Lower is better | Higher is better (above 100% = growth) |
| Perspective | How leaky is the bucket? | Is the bucket growing or shrinking? |
| Typical use | Operational diagnostic | Strategic metric, investor reporting |
Churn tells you what you're losing. NRR tells you the net effect after expansion. Both are essential — churn diagnoses the problem, NRR shows the outcome.
Churn rate is the percentage of customers or revenue you lose in a given period. If you start the month with 500 customers and 15 cancel, your monthly logo churn is 3%. If you start with $500K MRR and lose $7,500, your monthly revenue churn is 1.5%. Lower churn means customers stick around longer.
For mid-market B2B SaaS, monthly revenue churn below 1% is excellent. Between 1-2% is healthy. Above 2.5% is concerning and signals retention problems. Enterprise SaaS (high ACV) should be below 0.5% monthly. These benchmarks assume revenue churn, not logo churn.
Focus on the first 90 days — that's where most churn concentrates. Improve onboarding completion rates, set up health scoring to identify at-risk accounts, and ensure customers reach value within the first 2 weeks. Beyond that: segment your churn data to find which cohorts, segments, or plan types churn fastest, and fix those specifically.
Voluntary churn is when a customer actively cancels. Involuntary churn is when a subscription lapses due to failed payments or expired cards. Involuntary churn typically accounts for 20-40% of total churn and is the easiest to fix — automated payment retry and card update flows recover 30-50% of involuntary churn.
Weekly for early warning signals. Monthly for operational tracking and reporting. Quarterly for strategic analysis and cohort comparisons. The weekly check is important — a churn spike in week 2 gives you 2-3 weeks to investigate before the monthly number is impacted.
Negative net churn means your existing customers are generating more expansion revenue (upsells, cross-sells, seat growth) than you're losing to cancellations and downgrades. If you lose $10K to churn but gain $15K from expansion, net churn is -$5K — your existing base is growing on its own.
Fairview is an operating intelligence platform that tracks churn by cohort, segment, and plan type — alongside NRR, pipeline coverage, and forecast confidence. Start your free trial →
Siddharth Gangal is the founder of Fairview. He built cohort-level churn tracking because monthly churn rates hide the patterns that actually explain why customers leave.
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