What inputs does the Churn & Retention Calculator need?

It takes 4 inputs: customers, arpu, currentChurn, targetChurn. Outputs returned: currentLtv, targetLtv, ltvLift, recoveredCustomersYearOne.

Can I verify the Churn & Retention Calculator with a worked example?

Yes. With customers = 1000, arpu = $30, currentChurn = 6%, targetChurn = 4%. the tool returns current_ltv = $500, target_ltv = $750, ltv_lift = $250, recoveredCustomers year 1 = 240.

Where does the Churn & Retention Calculator get its benchmark data?

Reference data is sourced from: OpenView SaaS Benchmarks 2024 (churn percentiles) (as of 2024); Paddle SaaS Benchmarks 2024 (as of 2024).

What can the Churn & Retention Calculator not tell me?

Known limitations: The widely-cited Reichheld "5% retention lift = 25–95% profit lift" claim is context-dependent and not peer-reviewed. We do not use it as a benchmark. Consult the underlying Harvard Business School working paper directly if needed. Treats logo churn and revenue churn as equivalent; they diverge for products with tiered pricing.

Methodology: Churn & Retention Calculator

1. Scope

Estimates recovered customers and revenue lift when monthly churn improves. It illustrates the sensitivity of LTV to churn; it is not a retention-programme design tool.

2. Inputs and outputs

Inputs

customers number
arpu number (currency/mo)
currentChurn percent (monthly)
targetChurn percent (monthly)

Outputs

currentLtv

arpu / currentChurn.
targetLtv

arpu / targetChurn.
ltvLift

targetLtv − currentLtv.
recoveredCustomersYearOne

Customers × (currentChurn − targetChurn) × 12.

Engine source: src/lib/churn-retention-calculator/engine.ts

3. Formula / scoring logic

current_ltv = arpu / current_churn
target_ltv  = arpu / target_churn
ltv_lift    = target_ltv - current_ltv

4. Assumptions

Churn is memoryless (exponential decay). Real SaaS retention curves are often logarithmic, giving longer tail than this formula suggests.
ARPU is flat; no expansion-revenue tailwind.
The recovered-customer figure is a steady-state difference, not a behavioural projection.

5. Data sources

OpenView SaaS Benchmarks 2024 (churn percentiles) as of 2024
Paddle SaaS Benchmarks 2024 as of 2024

6. Known limitations

The widely-cited Reichheld "5% retention lift = 25–95% profit lift" claim is context-dependent and not peer-reviewed. We do not use it as a benchmark. Consult the underlying Harvard Business School working paper directly if needed.
Treats logo churn and revenue churn as equivalent; they diverge for products with tiered pricing.

7. Reproducibility

Input
customers = 1000, arpu = $30, currentChurn = 6%, targetChurn = 4%.

Expected output
current_ltv = $500, target_ltv = $750, ltv_lift = $250, recoveredCustomers year 1 = 240.

8. Change log

2026-04-24 methodology page first published.

Worked example

Run live against the same engine this site ships (/engines/churn-retention-calculator.js). The inputs and outputs below are recomputed on every build and independently re-verified in CI — they are never hand-authored.

Input

tool: churn_retention
active_customers: 1200
monthly_churn_percent: 4
retention_lift_percent: 1.5
arpu_monthly: 129
horizon_months: 12

Output

primaryLabel: Recovered customers at horizon
primaryValue: 150.35
primaryFormat: number
summary: Retention lift compounds monthly, increasing both active customers and revenue.
metrics[0].label: Improved churn rate
metrics[0].value: 2.5
metrics[0].format: percent
metrics[1].label: Base ending customers
metrics[1].value: 735.25
metrics[1].format: number
metrics[2].label: Improved ending customers
metrics[2].value: 885.6
metrics[2].format: number
metrics[3].label: Cumulative revenue lift
metrics[3].value: 142895.68
metrics[3].format: currency
assumptionsEcho.active_customers: 1200
assumptionsEcho.monthly_churn_percent: 4
assumptionsEcho.retention_lift_percent: 1.5
assumptionsEcho.arpu_monthly: 129
assumptionsEcho.horizon_months: 12

Frequently asked questions

What does the Churn & Retention Calculator calculate?: Estimates recovered customers and revenue lift when monthly churn improves. It illustrates the sensitivity of LTV to churn; it is not a retention-programme design tool.
What inputs does the Churn & Retention Calculator need?: It takes 4 inputs: customers, arpu, currentChurn, targetChurn. Outputs returned: currentLtv, targetLtv, ltvLift, recoveredCustomersYearOne.
What formula does the Churn & Retention Calculator use?: The exact computation is: current_ltv = arpu / current_churn; target_ltv = arpu / target_churn; ltv_lift = target_ltv - current_ltv
Can I verify the Churn & Retention Calculator with a worked example?: Yes. With customers = 1000, arpu = $30, currentChurn = 6%, targetChurn = 4%. the tool returns current_ltv = $500, target_ltv = $750, ltv_lift = $250, recoveredCustomers year 1 = 240.
Where does the Churn & Retention Calculator get its benchmark data?: Reference data is sourced from: OpenView SaaS Benchmarks 2024 (churn percentiles) (as of 2024); Paddle SaaS Benchmarks 2024 (as of 2024).
What can the Churn & Retention Calculator not tell me?: Known limitations: The widely-cited Reichheld "5% retention lift = 25–95% profit lift" claim is context-dependent and not peer-reviewed. We do not use it as a benchmark. Consult the underlying Harvard Business School working paper directly if needed. Treats logo churn and revenue churn as equivalent; they diverge for products with tiered pricing.