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CAC Payback Sensitivity Calculator

See how CAC payback months change as ARPA and gross margin vary (simple 3x3 sensitivity).

CAC payback is a simple formula, but your inputs move in the real world (pricing, mix, and margin). Sensitivity analysis helps you see how fragile (or robust) payback is.

This calculator generates a 3x3 payback grid by varying ARPA and gross margin around your base assumptions.

Prefer an explanation- Read the guide.

CAC payback sensitivity: ARPA * margin scenarios (months to recover CAC)Unit economics hub: CAC, LTV, payback, and runway (a practical stack)ARPA: how to calculate Average Revenue Per Account (formula + examples)Cohort payback curves: how to model payback with early churn

CAC

ARPA per month (base)

Gross margin (base)

ARPA step

Uses +/- step around ARPA base to create a 3x3 grid.

Gross margin step

Uses +/- step around margin base to create a 3x3 grid.

Tip: you can type commas (e.g., 10,000).

Example

Using the default inputs, the result is:

9.4 months

CAC: $6,000
ARPA per month (base): $800
Gross margin (base): 80%
ARPA step: 10%
Gross margin step: 5%

How to calculate

Enter your base CAC, ARPA per month, and gross margin.
Choose step sizes for ARPA and margin (e.g., +/-10% ARPA, +/-5% margin).
Review the payback grid and identify which lever improves payback fastest for your model.

Formula

Payback (months) = CAC / (ARPA x gross margin); Sensitivity varies ARPA and gross margin around a base case

Uses gross profit payback: ARPA x gross margin approximates monthly gross profit per account.
Assumes ARPA and gross margin are stable during the payback period (planning shortcut).
Only shows a small grid; use broader scenarios for full planning.

FAQ

Why use gross margin instead of revenue for payback-

Because payback should reflect contribution (value created after COGS). Revenue-based payback can overstate how fast you recover CAC.

What ARPA and margin ranges should I test-

Test ranges that reflect pricing/mix uncertainty. A common starting point is +/-10-20% ARPA and +/-5-10% margin, then widen if your business is volatile.

Is this the same as cohort payback curves-

No. This is a simple sensitivity tool for steady-state assumptions. Cohort payback curves model early churn and changing revenue/margin over time.

Common mistakes

Using revenue payback while CAC is fully-loaded (mismatch).
Mixing monthly ARPA with annualized CAC (time window mismatch).
Picking step ranges that are too narrow and concluding payback is stable (false confidence).

How to interpret

How to use payback sensitivity

If payback is extremely sensitive to margin, focus on COGS and variable cost control.
If payback is extremely sensitive to ARPA, focus on pricing, packaging, and upsell.
Use segment-level inputs (plan/channel) instead of blended averages when possible.