Metrics & Finance DefinedTerm

Churn Rate

Also known as: Customer Churn, Attrition Rate

Rate at which customers stop subscribing to a service, critical metric for subscription businesses and retention.

Updated: 2026-01-04

Definition

Churn Rate, or Attrition Rate, is the percentage of customers who stop using a product or service during a specific time period. It’s a fundamental metric for subscription-based businesses (SaaS, telecom, media streaming, fitness) because it measures a company’s ability to retain customers and indicates the health of recurring revenue.

The basic Customer Churn Rate formula is:

Customer Churn Rate = (Customers Lost in Period / Customers at Start of Period) × 100

Example: a company starts January with 1,000 customers and loses 50. January Churn Rate = (50 / 1,000) × 100 = 5% monthly.

Beyond Customer Churn (logo churn), there’s Revenue Churn (dollar churn), which measures revenue loss:

Revenue Churn Rate = (MRR Lost in Period / MRR at Start of Period) × 100

Revenue Churn better captures economic impact because it weights customers by value. Losing 10 SMB customers at 100 euros per month (1,000 euros MRR) has less impact than losing 1 enterprise customer at 10,000 euros per month.

Churn is critical because:

  • Economics: high churn makes sustainable growth impossible (leaky bucket)
  • LTV: churn determines Customer Lifetime Value (LTV = ARPU / Churn Rate)
  • Valuation: SaaS with low churn (under 5% annually) has higher valuation multiples
  • Product-market fit: churn over 10% monthly indicates PMF not achieved

Churn Rate emerged as a metric in the 1990s in telecom (mobile, internet), became central for SaaS in the 2000s. Netflix, Spotify, Salesforce built empires by optimizing retention and minimizing churn.

How it Works

Calculating churn requires attention to detail to be accurate and actionable.

Types of Churn

1. Customer Churn (Logo Churn): counts number of customers lost, regardless of value.

Formula: (Customers canceled / Customers at start of period) × 100

Pros: simple, intuitive. Cons: doesn’t weight economic value.

2. Revenue Churn (Dollar Churn): measures MRR or ARR lost.

Formula: (MRR lost from churn / MRR at start of period) × 100

Also includes Contraction (downgrades). More accurate for businesses with high variability in customer value.

3. Gross Churn vs Net Churn:

Gross Churn: only losses (cancellations plus downgrades), ignores expansion.

Net Churn: (Churn plus Contraction minus Expansion) / MRR at start. Can be negative if expansion exceeds churn (holy grail).

Example:

  • MRR start of month: 100K
  • Churned MRR: 8K
  • Contraction MRR: 2K
  • Expansion MRR: 15K
  • Gross Revenue Churn: (8K plus 2K) / 100K = 10%
  • Net Revenue Churn: (8K plus 2K minus 15K) / 100K = -5% (negative churn!)

4. Cohort Churn: analysis by acquisition cohort reveals retention patterns.

Jan 2024 Cohort: 100 customers. After 12 months: 70 remaining. Cumulative churn 30%, average churn rate approximately 2.8% monthly.

Timeframe and Annualization

Churn is measured over different timeframes:

  • Monthly Churn: for early-stage, high-velocity business (SMB SaaS)
  • Quarterly Churn: for mid-market
  • Annual Churn: for enterprise, long-term contracts

Approximate conversion (compounding): Annual Churn ≈ 1 - (1 - Monthly Churn)^12

Example: 5% monthly churn → annual churn ≈ 1 - (0.95)^12 = 46% (nearly half customers lost in a year).

Conversely: 20% annual churn → monthly churn ≈ 1 - (0.8)^(1/12) = 1.8% monthly.

Advanced Formulas and Corrections

New customer problem: basic formula overestimates churn if many new customers (still onboarding) churn quickly.

Cohort-based churn: calculate churn only on customers over 90 days (seasoned customers).

Adjusted Churn: exclude voluntary churns (e.g., company acquired, customer closes business) from involuntary churn (dissatisfaction, price).

Churn by reason: segment by cause (price, product gaps, competitor, customer success failure) for actionability.

Use Cases

Benchmark and Health Check

Churn varies dramatically by segment and industry:

B2B SaaS:

  • SMB: 3-7% monthly (approximately 35-60% annual) - high because SMB have high failure rate
  • Mid-Market: 1-2% monthly (approximately 12-22% annual)
  • Enterprise: 0.5-1% monthly (approximately 6-12% annual) - low due to lock-in, switching costs

B2C SaaS:

  • Consumer apps: 5-10% monthly (over 60% annual)
  • Media streaming: 3-6% monthly
  • Fitness/coaching: 5-8% monthly

Best-in-class: churn under 5% annually (0.4% monthly) for B2B enterprise. Slack pre-IPO: approximately 3% annual churn.

If churn exceeds benchmark, indicates a problem. SMB SaaS with 10% monthly churn (over 75% annual) has a leaky bucket: needs to acquire 75% plus new customers per year just to keep base flat.

Calculating Customer Lifetime Value (LTV)

Churn determines how long a customer stays, therefore LTV.

Simplified formula: LTV = ARPU / Churn Rate

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

If you reduce churn to 2.5%, LTV doubles: 100 / 0.025 = 4,000 euros.

This explains why retention is critical: small improvements in churn have exponential impact on LTV and unit economics.

LTV/CAC ratio: target over 3x. If CAC is 500 euros and LTV 2,000 euros (churn 5%), ratio is 4x (healthy). If churn increases to 10%, LTV drops to 1,000 euros, ratio becomes 2x (borderline).

Early Warning System and Churn Prediction

Tracking leading indicators predicts churn before it happens:

Behavioral signals:

  • Reduced usage (DAU/MAU drops)
  • No login for X days
  • Low feature adoption
  • Negative support tickets
  • Low NPS

Machine learning models: use random forest or logistic regression for churn prediction. Inputs: usage patterns, support history, invoice payments, NPS, firmographics.

Output: churn probability per customer. Proactive intervention on high-risk (over 70% probability): CSM outreach, offer discount/incentive, executive call.

Example: Spotify uses ML to identify at-risk users, offers personalized playlists and promotions for retention.

Cohort Retention Curves

Graphing retention by cohort reveals patterns:

Jan 2024 Cohort:

  • Month 0: 100% (100 customers)
  • Month 1: 85% (15% churned in onboarding)
  • Month 3: 75%
  • Month 6: 68%
  • Month 12: 60%

Curve shape:

  • Steep initial drop: high churn in first months (onboarding critical)
  • Flattening: after 6-12 months, retention stabilizes (customers become sticky)

Best practice: optimize first 90 days (time-to-value) to reduce early churn. “Aha moment” must arrive within 7-14 days.

Segmentation and Targeted Interventions

Not all churns are equal. Segment by:

High-value at-risk: enterprise customers with high MRR, low health score. Intervention: executive sponsor, dedicated CSM, customization.

Low-value chronic churners: SMB with recurring churn pattern (sign up, churn after trial). Decision: accept churn, optimize CAC for this segment (lower touch).

Winnable churners: mid-market churning for resolvable reason (missing feature). Intervention: product roadmap, workaround, partnership integration.

Unwinnable churns: business closure, acquisition, budget cuts. No effective intervention, accept.

Practical Considerations

Churn vs Growth Trade-off

Reducing churn to zero can slow growth. Accept strategic churn:

  • Freemium: high churn of free users is normal (conversion to paid is the goal)
  • Low-end market: SMB high churn is acceptable if CAC is low and volume compensates
  • Product pivots: during transition, old customer base churn is inevitable

Amazon Prime accepts churn on customers who sign up only for Black Friday (strategic: acquire those who stay long-term).

Relationship Churn vs Revenue Churn

Losing 10 SMB customers at 50 euros per month (500 euros MRR) is different from losing 1 enterprise at 10,000 euros per month.

Logo churn: 10 vs 1 (looks worse) Revenue churn: 500 vs 10,000 (enterprise churn is catastrophic)

Best practice: track both, but prioritize revenue churn for business decisions.

Involuntary vs Voluntary Churn

Involuntary churn: expired credit card, failed payment (often 20-40% of total churn). Solution:

  • Dunning: automated emails to update payment
  • Retry logic: reprocess payment after X days
  • Payment providers: use Stripe, Chargebee with smart retry

Recovering 50% of involuntary churn can reduce total churn by 10-20%.

Voluntary churn: active decision to cancel. Requires product or CS intervention. Harder to solve.

Churn Surveys and Feedback Loop

Exit survey at churn captures reasons. Questions:

  1. Why did you decide to cancel? (checkbox plus free text)
  2. What could we have done differently?
  3. Would you use the product in the future? (win-back potential)

Aggregating data reveals patterns: 40% churn for “price too high” → pricing problem. 30% for “feature X missing” → roadmap priority.

Netflix, Spotify use cancellation flow with retention offers (e.g., pause account 3 months, downgrade to cheaper plan) reducing churn by 15-20%.

Common Misconceptions

”Zero Churn is the Goal”

Zero churn is unrealistic and often not optimal. Some customers aren’t fit (wrong ICP), others have businesses that fail (outside control).

Healthy churn: 5-10% annual for B2B is normal. Focus: reduce churn on high-value segments, accept churn on low-fit customers.

Additionally, obsession with zero churn can lead to suboptimal decisions (e.g., giving excessive discounts, retaining unprofitable customers).

”Churn is Only a Product Problem”

Churn is cross-functional:

  • Product: feature gaps, UX friction, bugs
  • Customer Success: onboarding, training, engagement
  • Sales: sell to wrong ICP, overselling capabilities
  • Pricing: value mismatch, sticker shock
  • Support: slow resolution, poor quality

Reducing churn requires org-wide alignment. Single-function fix (e.g., only improve product) has limited impact.

”Churn is Measured the Same Way for Everyone”

B2B enterprise with annual contracts can’t use monthly churn (annual contract = zero churn until renewal). Need:

Renewal Rate: percent of contracts renewed at expiration. Formula: (Contracts Renewed / Contracts Expiring) × 100. Best-in-class: over 90%.

Logo Retention: percent of customers still active after 12 or 24 months.

B2C month-to-month SaaS uses monthly churn. Each business must define metric suited to its contract model.

Sources

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