How to Calculate Customer Lifetime Value

There are three ways to calculate LTV. They produce meaningfully different numbers. Use the right one for the situation.

Method 1: The simple formula (quick estimates)

LTV = Average Revenue Per Customer per Month / Monthly Churn Rate

Example: $200 ARPU / 5% monthly churn = $4,000 LTV.

Why it works: the reciprocal of your churn rate is your average customer lifetime in months. If 5% of customers churn each month, the average customer stays 20 months (1 / 0.05).

Why it lies: it assumes churn is constant. Real cohorts have higher churn in months 1-3 and lower churn after that. The simple formula overestimates LTV for products with steep early retention curves and underestimates it for products with flat retention curves.

Use it when: quick pitch math, back-of-envelope planning, sanity checks. Not for anything that matters.

Method 2: The cohort formula (accurate)

For each signup cohort, sum all revenue paid to date divided by cohort size. Track this over time to see how LTV evolves.

Example: 100 customers signed up in January 2026. By July 2026 (6 months in), they have collectively paid $180,000. LTV to date = $1,800 per customer. Now compare this cohort's trajectory against older cohorts to project the final LTV.

Why it works: uses actual revenue behavior, no assumptions about churn constancy.

Why it's harder: requires tracking each cohort separately over 12-24 months to see the shape.

Use it when: anything that will drive real decisions (acquisition budget, product investment, hiring). Also when reporting to investors or a board.

Method 3: The predictive formula (planning)

Fit a retention curve to your historical cohort data, extrapolate it forward, and calculate the area under the curve. This is the "true" mathematical LTV.

Example: retention data suggests a monthly retention curve that flattens at 3% churn after month 6. The area under that curve, multiplied by ARPU, is your LTV.

Why it works: accounts for the actual shape of your retention curve, not just averages.

Why it's harder: requires curve-fitting and some statistical work.

Use it when: long-term financial planning, cohort forecasting, projecting the impact of retention improvements.

Should LTV include gross margin?

Yes, for serious unit economics work.

LTV (gross margin adjusted) = (ARPU × Gross Margin %) / Monthly Churn Rate

For most SaaS with 70-85% gross margins, the adjustment reduces LTV by 15-30%. Compare gross-margin LTV to CAC (which is a real cash cost). If you compare unadjusted LTV to CAC, you overstate unit economics.

Common mistakes

1. Using blended churn on a fast-growing base. If your customer count is growing fast, recent cohorts have not fully aged. Their churn contribution understates true churn.
2. Ignoring expansion revenue. Customers who expand their spend over time have higher LTV than the initial ARPU suggests. Best-in-class SaaS accounts for net revenue retention above 100%, which turns "LTV" into "net LTV" - a much higher number.
3. Assuming churn is stable. Retention typically improves as cohorts age. Using month-1 churn as your denominator underestimates LTV.
4. Reporting LTV without saying which method. "Our LTV is $4K" is meaningless without context on how it was calculated.

Related concepts

• What is customer lifetime value? - the definition
• What is LTV to CAC ratio? - what to compare LTV against
• Net revenue retention - how expansion changes LTV
• MRR Simulator - interactive tool to explore how churn changes the math

To score your retention setup and see how much LTV improvement is on the table, take the 60-second Churn Health Check.