★ How much gross profit is one customer worth?
Customer Lifetime Value (LTV) Calculator
Calculate customer lifetime value from ARPA, gross margin and churn. Free LTV calculator with the formula, a worked example and how to compare it with CAC.
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Monthly, per paying account.
Revenue minus hosting, support and COGS.
Share of customers lost per month.
Your LTV
$3,200
- Average customer lifetime: 33.3 months (1 ÷ churn).
- Gross profit per month per account: $96.
LTV = (ARPA × gross margin) ÷ monthly churn rate
LTV: $3,200.
LTV is mostly a retention number. I build the onboarding and in-product moments that make customers stay longer.
How it works
Revenue overstates what a customer is worth, because some of it pays for servers, support and payment fees. Multiplying by gross margin gives the profit each customer contributes per month.
Dividing by monthly churn turns that into a lifetime: if 3% leave each month, the average customer stays about 33 months. This is the simple, steady-state version of LTV. It assumes churn is constant, which early on it rarely is.
Worked example
A B2B tool charging $120 a month per account, with 80% gross margin and 3% of customers leaving each month.
| Input | Value |
|---|---|
| Average revenue per account | $120 |
| Gross margin | 80.0% |
| Monthly churn | 3.0% |
| LTV | $3,200 |
Benchmarks
LTV has no target on its own. It only means something next to what you pay to acquire a customer. The widely cited rule from David Skok is LTV at least 3× CAC.
How to improve it
- Cut early churn. Most customers who leave do so in the first weeks, before they reach the core value.
- Raise prices or add a higher tier for the customers who already get the most out of the product.
- Build expansion paths (seats, usage, add-ons) so revenue per account grows over time.
- Lower cost to serve: cheaper infrastructure and self-serve support lift gross margin.
Questions founders actually ask
Should LTV use revenue or gross margin?
How do I calculate LTV with very little churn data?
Why is my LTV so high?
What is a good LTV?
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Fine print
Tools: on the house.
Engineer: by the hour.
Moving them is the expensive part, and the part I'm good at: activation flows, upsell moments and the product work behind better numbers.
I'm Himanshu, an AI and full-stack engineer. I build MVPs, AI agents and the growth plumbing around them for early-stage startups.
