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
- 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.
- 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.
- Assuming churn is stable. Retention typically improves as cohorts age. Using month-1 churn as your denominator underestimates LTV.
- 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.