Formula Guide

Churn Rate Formula: The Complete
Customer Churn & Retention Guide

Master the churn rate formula for subscriptions and ecommerce: customer churn, revenue churn, and how churn drives LTV and lifespan.

The Churn Rate Formula

Churn Rate = (Customers Lost ÷ Customers at Start) × 100

Customer Lifespan = 1 ÷ Churn Rate (use decimal, same period)

Customers Lost

Number who churned (cancelled, lapsed, or left) in the period.

Customers at Start

Total eligible customers at the beginning of the same period.

Result

Percentage that churned. Use 1 ÷ churn for average lifespan and LTV.

Quick Example

Start of month: 500 customers. During month: 25 churned.

Churn = (25 ÷ 500) × 100 = 5% monthly

Average customer lifespan = 1 ÷ 0.05 = 20 months. Use this in LTV = AOV × Frequency × Lifespan.

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Churn Rate Formula Variations

Customer churn, revenue churn, and lifespan

Customer Churn Rate
Formula
(Customers Lost ÷ Customers at Start) × 100
Example
(24 ÷ 400) × 100 = 6% monthly
Use Case
Subscription and cohort-based businesses

Count customers who left in the period. Start = beginning of period.

Revenue Churn (MRR/ARR)
Formula
(Revenue Lost in Period ÷ Revenue at Start) × 100
Example
($2,400 ÷ $40,000) × 100 = 6% MRR churn
Use Case
Subscription and recurring revenue

Includes cancellations and downgrades. Net churn subtracts expansion.

Customer Lifespan from Churn
Formula
1 ÷ Churn Rate (decimal)
Example
1 ÷ 0.06 = 16.7 months
Use Case
Input for LTV and payback calculations

Use same period as churn (monthly churn → lifespan in months).

Retention Rate
Formula
100 - Churn Rate
Example
6% churn = 94% retention
Use Case
Flip side of churn; often easier to communicate

Retention + Churn = 100% (assuming no new in cohort).

Cohort Churn
Formula
(Cohort Customers Lost by Period End ÷ Cohort Size) × 100
Example
Jan cohort: 200 customers, 50 left by month 3 → 25% by month 3
Use Case
Track how a single cohort decays over time

Curve of churn over time; doesn't add new customers to cohort.

Worked Examples

Step-by-step churn and lifespan calculations

1

Monthly Customer Churn

Scenario

Subscription business. Start of month: 1,200 customers. During month: 48 cancelled.

  1. 1 Customers at start = 1,200
  2. 2 Customers lost = 48
  3. 3 Churn Rate = (48 ÷ 1,200) × 100
  4. 4 Churn = 4% monthly
Result

Monthly churn rate is 4%.

Interpretation

At 4% monthly churn, average customer lifespan = 1 ÷ 0.04 = 25 months. Annual churn ≈ 1 - (0.96)^12 ≈ 39%.

2

Customer Lifespan and LTV

Scenario

Your annual churn rate is 25%. AOV $70, purchase frequency 2x/year. What's LTV?

  1. 1 Annual churn = 25% = 0.25
  2. 2 Lifespan = 1 ÷ 0.25 = 4 years
  3. 3 LTV = AOV × Frequency × Lifespan
  4. 4 LTV = $70 × 2 × 4 = $560
Result

Customer lifespan is 4 years; LTV is $560.

Interpretation

Reducing churn to 20% would give lifespan 5 years and LTV $700—a 25% LTV increase from retention alone.

3

Revenue Churn (MRR)

Scenario

Start of month MRR $85,000. Lost $4,250 from cancellations, $800 from downgrades. Gained $2,100 from upgrades.

  1. 1 Gross MRR churn = $4,250 + $800 = $5,050
  2. 2 Gross churn % = ($5,050 ÷ $85,000) × 100 = 5.9%
  3. 3 Net MRR churn = $5,050 - $2,100 = $2,950
  4. 4 Net churn % = ($2,950 ÷ $85,000) × 100 = 3.5%
Result

Gross MRR churn 5.9%; net 3.5% after expansion.

Interpretation

Net churn is what actually reduces MRR. Negative net churn means expansion outweighs churn.

4

Ecommerce Lapsed Customers

Scenario

Define 'active' as purchased in last 12 months. Start of year: 5,000 active. During year 1,800 had no purchase in next 12 months (lapsed).

  1. 1 Active at start = 5,000
  2. 2 Lapsed (churned) = 1,800
  3. 3 Churn = (1,800 ÷ 5,000) × 100 = 36%
  4. 4 Retention = 64%
Result

36% of the cohort lapsed (no purchase in following 12 months).

Interpretation

Ecommerce 'churn' is often annual and based on repurchase windows. Use for LTV and retention campaigns.

Churn Benchmarks by Type

Typical ranges (your results will vary)

Type Typical Churn Notes
SaaS (B2B) 3% - 8% monthly Varies by segment and contract length
SaaS (B2C) 5% - 12% monthly Often higher than B2B
Subscription box 6% - 12% monthly Skip/cancel is common
Ecommerce (12-mo lapse) 50% - 80% annual Many don't repurchase in 12 months
Media/Streaming 3% - 6% monthly Low switching cost

How to Reduce Churn

Strategies that improve retention

High Impact

Onboarding & Activation

Ensure customers see value early. First-use success reduces early churn.

High Impact

Usage and Health Metrics

Track engagement; intervene when usage drops before they cancel.

Medium Impact

Win-Back and Save Offers

Offers at cancellation or win-back emails for lapsed customers.

High Impact

Customer Success (B2B)

Proactive check-ins, QBRs, and success plans for at-risk accounts.

High Impact

Improve Product-Market Fit

Churn often reflects unmet expectations or wrong segment.

Medium Impact

Loyalty and Retention Programs

Rewards, tiers, and benefits that increase switching cost.

Common Churn Mistakes

Errors that distort churn and lifespan

Mixing Time Periods

Using customers at start of year with churned count from one month, or mixing monthly and annual churn.

How to Fix

Use consistent period: same window for 'at start' and 'lost.' Label clearly (e.g. monthly vs annual churn).

Ignoring Cohort vs Blended

Blended churn (all customers) can hide that new cohorts churn faster or slower than mature ones.

How to Fix

Track cohort churn curves. Blended is useful for overall health; cohorts show true retention by vintage.

Counting New Customers in Churn

Including new signups in 'customers at start' when they haven't had time to churn yet.

How to Fix

Churn rate should use a defined cohort or 'customers at start of period' who could have churned in that period.

Confusing Revenue and Customer Churn

Reporting one when the other is more relevant (e.g. losing few high-value customers = high revenue churn).

How to Fix

Track both. Customer churn for count; revenue churn for MRR/ARR impact. Net revenue churn includes expansion.

How to Track Churn & Retention in WooCommerce

Three ways to monitor customer churn and retention for your WooCommerce store

Option 1: Spreadsheets

Export customer and order history to identify lapsed or churned customers manually. Requires defining an inactive window and repeated cohort analysis over time.

Pros
  • Full control
  • No additional cost
Cons
  • Time-consuming
  • Quickly outdated
  • Complex cohort logic

Option 2: Google Analytics

GA4 can show some retention and user lifecycle metrics, but has limitations with logged-in customer identity and historical cohort churn over long periods.

Pros
  • Free to use
  • Some retention views
Cons
  • Cookie-based
  • Limited customer-level churn
  • Complex setup
Recommended

Option 3: StoreRadar

StoreRadar tracks repeat purchase behavior and retention by segment, so you can see who's at risk of churning and how churn affects LTV—all in real time.

Pros
  • Automatic retention view
  • Segment-level behavior
  • Real-time updates
  • LTV by cohort
Cons
  • Monthly subscription
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Related Formulas

Churn ties directly to LTV and retention

Formula Calculation Relationship
Customer Lifetime Value AOV × Frequency × (1 ÷ Churn) Churn sets lifespan; LTV = AOV × Freq × Lifespan
Retention Rate 100% - Churn Rate Inverse of churn
Customer Lifespan 1 ÷ Churn Rate Average tenure; use same period as churn
LTV:CAC LTV ÷ CAC Churn affects LTV and thus LTV:CAC
Cohort Retention % of cohort still active each period Cohort view of churn over time

Frequently Asked Questions

Common questions about churn rate

Customer churn rate = (Customers Lost in Period ÷ Customers at Start of Period) × 100. For example, 80 customers at start of month, 12 left: (12 ÷ 80) × 100 = 15% monthly churn. Revenue churn uses (Revenue Lost ÷ Revenue at Start) × 100.

Customer churn counts how many customers left. Revenue churn measures revenue lost from those customers (or from downgrades). You can have low customer churn but high revenue churn if your biggest spenders leave. Track both for subscriptions and high-value segments.

Ecommerce often uses 'inactive' or 'lapsed' instead of formal churn. Define a window (e.g. 12 months with no purchase). Churn = (Customers who became inactive in period ÷ Active at start) × 100. Or use cohort retention and infer churn from 1 - retention.

Customer Lifespan = 1 ÷ Churn Rate (use decimal: 15% = 0.15). So 15% annual churn → lifespan = 1 ÷ 0.15 = 6.67 years. LTV = AOV × Frequency × Lifespan, so churn directly affects LTV. Lower churn means longer lifespan and higher LTV.

It depends on business type. Subscription SaaS: 3–8% monthly is common; under 5% is strong. Ecommerce: often measured as % of customers who don't repurchase within 12 months; 60–80% 'lapse' in a year is typical. Compare to your own history and segment.

Use the period that matches your billing or purchase cycle. Monthly churn is common for subscriptions. For annual contracts use annual churn. Convert: Annual Churn ≈ 1 - (1 - Monthly Churn)^12. A 5% monthly churn is about 46% annual.

See Who's at Risk of Churning

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