LTV = (Average Revenue per Customer x Gross Margin %) / Churn Rate
LTV estimates the total profit a customer delivers before they leave.
What it is
Customer Lifetime Value estimates the total profit a business expects from a typical customer across the whole time they stay, not just one sale. A common version multiplies the average gross profit per customer per period by the average number of periods a customer stays, which is the inverse of the churn rate. It is a forward-looking estimate, so it depends heavily on the churn and margin assumptions used.
Why it matters
LTV sets the ceiling on what a company can rationally spend to acquire a customer, which is why it is paired with CAC in the LTV/CAC ratio. A high LTV relative to CAC means each customer funds the cost of winning the next one with room to spare. Because it relies on assumptions, small changes in churn or margin can swing the figure a lot.
How it's calculated
Multiply the average gross profit per customer per period by the expected customer lifetime, where lifetime is approximated as 1 divided by the periodic churn rate.
How Quintarthai uses it
Gross margin, a core LTV input, is shown directly in the key-metrics grid and Ratios tab of a company's deep-analysis page, so you can pressure-test a stated LTV.
Cross-border note. LTV is currency- and assumption-dependent, so a Canadian and a US SaaS company's LTV are comparable only after matching currency and confirming each uses the same churn and margin basis; it is non-GAAP under both regimes.
FAQ
Should LTV use revenue or gross profit?
Gross profit is the more rigorous basis, because it reflects the actual margin a customer contributes, not top-line revenue. An LTV built on revenue alone overstates a customer's true value.
Why does LTV depend on churn?
Expected customer lifetime is roughly 1 divided by the churn rate. Lower churn means customers stay longer, which raises LTV; higher churn shortens the relationship and lowers it.
Check your understanding
Two analysts estimate LTV for the same company and get very different numbers. Which difference in their inputs would most plausibly explain this?
Expected lifetime is roughly 1 divided by the churn rate, so a higher churn assumption shortens the relationship and meaningfully lowers the LTV estimate.