This estimator calculates an early-stage customer lifetime value (LTV) from average monthly revenue per customer, gross margin, and monthly customer churn. It is designed for pre-seed teams that need a simple, transparent unit-economics estimate before they have enough history for cohort-based modeling.
The result helps founders compare expected customer value with acquisition cost, evaluate pricing, and test how retention improvements affect economics. Because young companies often have limited data, the estimate should be treated as a planning model rather than a precise forecast.
1. Enter monthly revenue
Use the average recurring revenue generated by one active customer in a typical month.
2. Add gross margin
Enter the share of revenue remaining after direct delivery costs.
3. Enter monthly churn
Use the percentage of customers lost during an average month.
4. Review the estimate
Compare gross-margin-adjusted LTV with acquisition cost and pricing assumptions.
LTV = Monthly ARPA × Gross Margin ÷ Monthly Churn Rate
ARPA is average monthly revenue per account, gross margin and churn are entered as decimals in the calculation. Estimated lifetime is 1 ÷ monthly churn. This simple model assumes churn and revenue remain constant.
The main result is the estimated gross profit contribution from an average customer over the modeled lifetime.
Pre-seed data can be volatile; update the inputs as cohorts mature.
Given: ARPA = $80, gross margin = 75%, monthly churn = 5%.
Calculation: Monthly gross profit = $80 × 0.75 = $60. LTV = $60 ÷ 0.05 = $1,200.
Result: Estimated LTV is $1,200, with an implied average lifetime of 20 months.
LTV should reflect the value left after direct costs, not just top-line revenue.
Match the churn period to the revenue period. This page uses monthly revenue and monthly churn.
No. Zero churn makes the simple inverse-churn formula undefined and would imply an unlimited lifetime.
Use the best available observed data, then run conservative and optimistic scenarios rather than relying on one point estimate.
This estimate adjusts revenue for gross margin and expected retention, making it more useful for unit-economics comparisons.