1. Scope
Computes customer acquisition cost from total acquisition spend divided by customers acquired, plus payback-month and LTV:CAC ratio. It does not attribute spend across channels or model marketing-mix effects.
2. Inputs and outputs
Inputs
- salesAndMarketingSpend number (currency)
- customersAcquired number
- arpu number (currency/mo)
- grossMargin percent default: 80
- monthlyChurn percent default: 5
Outputs
- cac
spend / customers.
- paybackMonths
cac / (arpu × grossMargin).
- ltv
arpu × grossMargin / monthlyChurn.
- ltvCacRatio
ltv / cac.
Engine source: src/lib/cac-calculator/engine.ts
3. Formula / scoring logic
cac = sales_marketing_spend / customers_acquired
payback_months = cac / (arpu * gross_margin)
ltv = (arpu * gross_margin) / monthly_churn
ltv_cac_ratio = ltv / cac 4. Assumptions
- Spend is fully-loaded: paid ads, sales salaries, tooling, and attributed content cost.
- Customers-acquired is net-new, not re-activated.
- ARPU and margin are steady-state.
5. Data sources
- OpenView SaaS Benchmarks 2024 (CAC payback percentiles) as of 2024
- SaaS Capital Annual Survey as of 2024
6. Known limitations
- Blended CAC hides channel-level economics. Organic-heavy businesses with a small paid budget will look stronger than they are.
- LTV:CAC guidance (often quoted as 3:1) is industry lore; benchmarks from OpenView and SaaS Capital vary by stage and vertical.
7. Reproducibility
Input
spend = $20,000, customers = 100, arpu = $50, grossMargin = 80%, monthlyChurn = 3%.
Expected output
cac = $200, payback = 5 months, ltv ≈ $1,333, ltv:cac ≈ 6.7×.
8. Change log
- 2026-04-24 methodology page first published.