How to Calculate Customer Lifetime Value (LTV)

Customer lifetime value (LTV, sometimes CLV or CLTV) is the total profit you expect from a customer across the whole relationship. Paired with CAC, it answers the question every growth team must be able to defend: is each customer worth more than it costs to acquire them?

The honest formula: margin-adjusted LTV

The most common mistake is calculating LTV on revenue instead of profit. Revenue-based LTV overstates value dramatically for any business with meaningful cost of goods. Use the margin-adjusted version:

LTV = ARPU × gross margin × average customer lifespan

Where ARPU is average revenue per customer per period (often monthly), gross margin is the fraction of revenue left after the direct cost of serving the customer, and lifespan is how many periods the average customer stays.

Two ways to get lifespan

1. Lifespan-based (simple)

If you know your average customer lifespan directly — say, 24 months — plug it in. Straightforward, but circular for young companies that do not yet have real lifespan data.

2. Churn-based (better for subscriptions)

For subscription businesses, derive lifespan from churn. The average lifespan of a customer is the inverse of the churn rate:

Average lifespan (months) = 1 ÷ monthly churn rate

So a 4% monthly churn rate implies an average lifespan of 1 ÷ 0.04 = 25 months. Combined with the margin formula, this gives:

LTV = (ARPU × gross margin) ÷ monthly churn rate

Churn-based LTV is powerful but sensitive: at low churn rates a tiny change swings LTV wildly, and it assumes churn stays constant, which it rarely does. Treat the output as a planning estimate, not a promise.

A worked example

ARPU is $120/month, gross margin is 80%, and average lifespan is 24 months. Then LTV = $120 × 0.80 × 24 = $2,304. If your CAC is $250, your LTV:CAC ratio is about 9:1. You can compute all of this at once — including CAC payback — in the unit-economics calculator.

Mistakes that inflate LTV

• Using revenue, not margin. The biggest and most common inflation.
• Assuming zero churn drift. Early cohorts churn faster; blending them with mature cohorts can flatter lifespan.
• Ignoring discounts and refunds. Net revenue, not gross bookings.
• Extrapolating from too little data. Predicting a 5-year lifespan from six months of history is guesswork. Use ranges.
• Counting expansion you have not earned. Upsell can raise LTV, but only model it once you have evidence it happens reliably.

Historical vs. predictive LTV

There are two broad ways to arrive at LTV, and confusing them causes most disputes. Historical LTV sums the actual margin a cohort has generated to date — accurate but backward-looking, and it undercounts customers who are still active. Predictive LTV uses the formulas above (or a statistical model) to forecast the full lifetime value, including revenue not yet earned. Predictive LTV is what you compare against CAC when deciding how much to spend, because CAC is paid upfront to capture a future stream. The trap is mixing them: comparing a fully-predicted LTV against a conservative historical CAC, or vice versa, produces a ratio that means nothing. Pick one basis and apply it consistently on both sides of the equation. For young companies with thin history, present predictive LTV as a range across optimistic and pessimistic churn assumptions rather than a single confident figure — it keeps everyone honest about how much is forecast versus observed.

How LTV drives decisions

LTV is not a vanity number — it sets your acquisition budget. If a customer is worth $2,300 in margin, you can afford a meaningfully higher CAC than if they are worth $300. The relationship between the two is captured by the LTV:CAC ratio, and the speed of recovery by the CAC payback period. For where value creation sits in the wider growth model, see AARRR pirate metrics and the North Star Metric.