Churn rate measures the percentage of customers who stop using your product or service during a specific period.

Basic formula: Churn Rate = (Customers Lost ÷ Starting Customers) × 100.

Example: Start month with 1,000 customers, lose 50, churn rate = (50 ÷ 1,000) × 100 = 5%.

Monthly churn compounds over time: 5% monthly = 46% annual churn (not 60% because remaining base shrinks each month).

Revenue churn formula: (MRR Lost ÷ Starting MRR) × 100—can be negative if expansion revenue from existing customers exceeds lost revenue (negative churn is ideal).

Cohort-based churn: track specific customer groups acquired in same period for more accurate trend analysis.

Logo churn (customer count) vs revenue churn (dollar amount) can tell different stories: losing 10% of customers generating 30% of revenue = 10% logo churn but 30% revenue churn signals unhealthy customer concentration.

Industry benchmarks: SaaS 5-7% monthly, consumer subscription (Netflix, Spotify) 5-10% monthly, B2B enterprise <3% monthly, telecommunications 1-2% monthly, retail memberships 6-8% monthly.

Acceptable churn depends on payback period: if customer acquisition cost (CAC) paid back in 6 months, 8% monthly churn still profitable; if payback takes 18 months, need <3% monthly churn to achieve ROI.

Top churn drivers in order of impact: (1) Poor Onboarding—40% of churn happens in first 90 days, customers don't experience value, solution: structured onboarding program with milestones, personal check-ins, and success metrics, reduces first-quarter churn 30-50%. (2) Pricing Misalignment—15-25% of churn, customers outgrow plan or can't afford it, solution: usage-based pricing or multiple tiers, proactive plan migrations before cancelation. (3) Better Alternatives—20-30% of churn to competitors, solution: continuous product improvement, feature parity monitoring, competitive win-back campaigns. (4) Lack of Engagement—customers not using product, 80% of inactive users churn within 6 months, solution: engagement scoring, automated re-activation emails, product education. (5) Poor Customer Support—16% cite support as churn reason, solution: 24-hour response SLA, self-service knowledge base reducing support tickets 40%. (6) Payment Failures—20-40% of involuntary churn (credit card expirations, insufficient funds), solution: dunning campaigns, multiple payment retry attempts, account updater services. (7) Missing Features—customers need functionality you don't offer, solution: product roadmap aligned to churn exit interviews, prioritize most-requested features.

Effective reduction strategies: (1) Churn prediction models—identify at-risk customers 30-60 days early using engagement signals (login frequency decline, feature usage drop, support ticket increase), proactive intervention reduces predicted churn 25-35%. (2) Win-back campaigns—offer discounts, new features, or personalized outreach to recently churned customers, 10-15% win-back rate is achievable. (3) Annual contracts—reduce churn 60-80% vs monthly, lock in commitment with small discount (10-20% off monthly price). (4) Community building—users with 5+ community connections have 70% lower churn, foster peer relationships through forums, events, user groups.

Implementation: reduce churn 1% = revenue increase of 5-25% over 5 years due to compounding retention.

Gross churn and net churn measure customer loss differently, with net churn accounting for business growth from existing customers.

Gross Revenue Churn = (MRR Lost from Cancellations + Downgrades) ÷ Starting MRR × 100, measures pure revenue leakage without considering expansions, always positive number, shows maximum potential revenue loss.

Example: $100,000 starting MRR, lose $8,000 from cancelations, $2,000 from downgrades = $10,000 lost ÷ $100,000 = 10% gross churn.

Net Revenue Churn = (MRR Lost - MRR Gained from Expansions) ÷ Starting MRR × 100, subtracts expansion revenue (upsells, cross-sells, usage increases) from losses, can be negative number indicating revenue growth despite customer losses.

Same example with $12,000 expansion revenue: ($10,000 lost - $12,000 gained) ÷ $100,000 = -2% net churn (negative churn = revenue growth).

Negative churn (net revenue retention >100%) is the gold standard for SaaS: customers spending more over time despite some leaving, achieved by only 25% of SaaS companies, requires strong product-led growth and expansion revenue engine.

Logo churn vs revenue churn: losing 100 small customers ($50/month each = $5,000 MRR) vs losing 10 enterprise customers ($1,000/month each = $10,000 MRR) = same 10% logo churn but 2x difference in revenue impact.

Best practice tracking: monitor both gross and net churn monthly, gross churn shows product-market fit strength (should decrease over time as product improves), net churn shows monetization effectiveness (expansion revenue captures increasing customer value).

Benchmarks: gross revenue churn 5-7% monthly acceptable for early-stage SaaS, net revenue churn <2% monthly (or negative) required for sustainable growth beyond $10M ARR.

Quick test: if net churn is much lower than gross churn, expansion revenue is working; if gross churn increasing, customer satisfaction declining regardless of expansion success.

Annual churn is NOT simply monthly churn × 12 due to compounding—customer base shrinks each month.

Correct formula: Annual Churn Rate = 1 - (1 - Monthly Churn Rate)^12.

Example: 5% monthly churn, annual = 1 - (1 - 0.05)^12 = 1 - (0.95)^12 = 1 - 0.5404 = 0.4596 = 46% annual churn (not 60% if you incorrectly multiply).

Mathematical proof: Start with 1,000 customers, 5% monthly churn.

Month 1: 1,000 - 50 = 950 remain.

Month 2: 950 - 47.5 = 902.5 remain (5% of 950, not original 1,000).

Month 12: 540 customers remain, 460 churned = 46% annual churn.

Reverse calculation (annual to monthly): Monthly Churn = 1 - (1 - Annual Churn)^(1/12).

Example: 50% annual churn target, monthly = 1 - (1 - 0.50)^(1/12) = 1 - (0.50)^0.0833 = 1 - 0.9439 = 5.61% monthly churn allowed.

Rule of thumb approximation for small churn rates (<3% monthly): Annual ≈ Monthly × 12 × 0.96, works reasonably well as shortcut but becomes less accurate above 3% monthly.

Cohort-based annual calculation (more accurate): Track specific customer cohort for 12 months, Annual Churn = (Starting Cohort - Remaining after 12 Months) ÷ Starting Cohort.

Example: 1,000 customers acquired January 2024, 580 remain January 2025 = (1,000 - 580) ÷ 1,000 = 42% annual churn.

Industry comparison: SaaS with 5% monthly churn has 46% annual churn (needs to replace nearly half customer base yearly), SaaS with 3% monthly churn has 30% annual churn (much more sustainable, 70% year-over-year retention).

Growth impact: if acquiring 100 new customers/month but churning 5% monthly, need to reach 2,000 customer equilibrium before net growth occurs—reducing churn to 3% monthly lowers equilibrium to 1,111 customers, enabling faster scaling.

Good churn rates vary dramatically by business model, customer segment, and company maturity.

SaaS churn benchmarks by segment: Consumer/SMB (small business) SaaS: 5-7% monthly acceptable (<$100/month price point), high acquisition volume compensates for higher churn, focus on rapid customer acquisition over retention.

Mid-Market SaaS ($100-$500/month): 3-5% monthly churn, longer sales cycles justify better retention, product complexity and customer success reduce churn.

Enterprise SaaS ($500+/month, annual contracts): 0.5-2% monthly churn (6-22% annual), sticky products with implementation costs, multi-year contracts common, churn often forecastable quarters in advance.

Vertical SaaS (industry-specific): 2-4% monthly, switching costs high due to industry workflows, churn rate stability more important than absolute number.

Prosumer/Creator tools: 8-12% monthly, high experimentation, seasonal usage patterns, many casual users alongside serious customers.

Consumer subscription benchmarks: Streaming (Netflix, Spotify): 3-6% monthly, low switching costs and high competition drive higher churn, requires constant content investment.

Fitness/wellness apps: 8-15% monthly, very high first-month churn (30-50%), resolution-driven signups (January spike and February crash).

Meal kits/subscription boxes: 10-20% monthly, novelty wears off, shipping costs and logistics challenges, requires continuous product innovation.

Email/productivity: 2-4% monthly, habit-forming products have lower churn, daily use drives retention.

Churn targets by company stage: Pre-product-market fit (0-$1M ARR): 8-10% monthly acceptable, rapid iteration and customer feedback more important than retention.

Early growth ($1-10M ARR): 5-7% monthly target, onboarding and product improvements should decrease churn over time.

Growth stage ($10-50M ARR): 3-5% monthly requirement, customer success team and engagement programs mandatory.

Scale stage ($50M+ ARR): <3% monthly necessary for sustainable growth, negative net churn goal (>100% net revenue retention).

Warning signs: churn increasing month-over-month, churn higher in recent cohorts than older cohorts (product degradation), revenue churn 2x+ higher than logo churn (losing highest-value customers).

Improvement potential: reducing churn from 7% to 5% monthly increases customer lifetime from 14 months to 20 months (43% improvement), dramatically improving LTV:CAC ratio and profitability.

Churn rate is the denominator in LTV calculation—small churn improvements create exponential LTV gains.

Basic LTV formula: LTV = Average Revenue Per Customer ÷ Churn Rate.

Example: $100/month ARPU, 5% monthly churn: LTV = $100 ÷ 0.05 = $2,000.

Reduce churn to 4%: LTV = $100 ÷ 0.04 = $2,500 (25% LTV increase from 1% churn reduction).

More accurate LTV formula (accounting for gross margin): LTV = (ARPU × Gross Margin %) ÷ Churn Rate.

Example: $100 ARPU, 80% margin, 5% churn = ($100 × 0.80) ÷ 0.05 = $1,600 LTV.

Cohort-based LTV (most accurate): Sum all revenue from customer cohort over lifetime ÷ number of customers in cohort, accounts for expansion revenue and actual customer behavior.

The LTV:CAC ratio determines business viability: LTV:CAC < 1 = unsustainable (losing money on each customer), LTV:CAC 1-3 = break-even to marginal (need improvements), LTV:CAC 3-5 = good (profitable scaling possible), LTV:CAC >5 = excellent (underinvesting in growth).

Churn impact on LTV:CAC: $500 CAC, $100 ARPU.

At 5% churn: LTV = $2,000, ratio = 4.0 (good).

At 7% churn: LTV = $1,429, ratio = 2.9 (marginal).

At 3% churn: LTV = $3,333, ratio = 6.7 (excellent).

Payback period (months to recover CAC): Payback = CAC ÷ (ARPU × Gross Margin). $500 CAC, $100 ARPU, 80% margin = $500 ÷ $80 = 6.25 months payback.

If monthly churn >16% (reciprocal of 6.25), you lose money on average customer.

Rule: payback period must be <50% of average customer lifetime (1 ÷ churn rate) for profitability.

Expansion revenue impact on LTV: Net revenue retention 110% (negative -10% net churn) multiplies LTV by 1.5-2x.

Example: $100 starting ARPU growing 10% annually, 5% gross churn: LTV = $100 ÷ 0.05 × (1 + expansion growth factor) ≈ $3,000-$4,000 vs $2,000 without expansion.

Strategic implications: reducing churn 1% often easier and more profitable than increasing ARPU $10 or reducing CAC $50, focus on retention before acquisition optimization.

Cohort profitability calculation: total LTV from cohort minus total CAC for cohort = cohort profit, positive cohort profit required for sustainable growth (many startups acquire customers at loss hoping to reduce churn over time).

Churn distribution matters: if 80% of churn happens in first 3 months, focus on onboarding improvements has 4x impact vs reducing steady-state churn; if churn evenly distributed, broad product improvements needed.

For $50M ARR SaaS at 5% monthly churn, reducing to 4% monthly churn increases total enterprise value ~$100M+ due to higher revenue multiples and predictable growth.