LTV Calculator

Enter the monthly revenue an average account brings in, your gross margin, and the percentage of customers who cancel in a typical month. The calculator returns customer lifetime value — the gross profit an average customer generates before churning — plus the average lifetime in months your churn rate implies. Fill in the optional CAC field and it also shows the LTV to CAC ratio, the shorthand investors use to judge whether acquisition spend earns its keep. On the defaults that reads $3,167 of lifetime margin, a 41.7-month lifetime, and a ratio of 2.8 : 1.

Where the idea came from

Businesses were valuing customers across many purchases long before anyone reduced it to a formula. Catalog houses, magazine publishers and other direct-mail firms had every reason to know what a name on a mailing list was worth over years of repeat orders, because the cost of the next mailing had to be justified against future returns rather than immediate ones. Their working shorthand was RFM — ranking customers by recency, frequency and monetary value to decide who deserved another catalogue. Consultants turned that instinct into arithmetic: Kestnbaum & Company, the Chicago firm Robert and Kate Kestnbaum founded in 1967, brought financial modeling and econometrics to mailing-list decisions and pushed the calculation of customer long-term value into general use. The term customer lifetime value appears with worked examples in Robert Shaw and Merlin Stone's book Database Marketing at the end of the 1980s, and the selection problem reached the journals in 1995, when Jan Roelf Bult and Tom Wansbeek published "Optimal Selection for Direct Mail" in Marketing Science, choosing names by equating marginal cost with marginal return.

The economic argument for retention was sharpened by Frederick Reichheld and W. Earl Sasser Jr. in "Zero Defections: Quality Comes to Services," published in the Harvard Business Review in 1990. They showed that small reductions in the customer defection rate — churn, in current language — produced outsized gains in profit: cutting the defection rate by five points raised profits 30% in an auto-service chain, 50% in an insurance brokerage and 85% in one bank's branch system, and when the credit card issuer MBNA America halved its 10% defection rate, profits rose 125%. That paper turned churn from an operational nuisance into a financial lever, the role it plays in the formula below.

A systematic academic treatment followed at the end of the decade. Paul Berger and Nada Nasr set out a series of mathematical models for customer lifetime value in the Journal of Interactive Marketing in 1998, discounting a customer's stream of future margin instead of valuing a single sale. The compact churn-based version used here belongs to the software-as-a-service era: in the early 2010s David Skok, a general partner at Matrix Partners, wrote LTV as ARPA times gross margin divided by the monthly customer churn rate in his SaaS Metrics writing on the For Entrepreneurs blog, and it was there that the three-to-one ratio benchmark and the months-to-recover-CAC payback measure passed into everyday startup use.

Where the formula comes from

LTV = ARPA × (margin ÷ 100) ÷ (churn ÷ 100)

The division by churn looks arbitrary until you see the series it replaces. A customer paying $76 of gross margin a month ($95 of revenue at an 80% margin) has a 97.6% chance of surviving any given month when churn is 2.4%, so the chance of still being a customer after n months is 0.976 to the power n. Expected total margin is 76 × (1 + 0.976 + 0.976² + …), and that geometric series converges to 76 ÷ 0.024 = $3,167. The same series gives the average survival time: 1 ÷ 0.024 = 41.7 months. One division stands in for an infinite sum, which is why the formula is everywhere — and why every assumption it makes is packed into that single churn number.

Margin belongs in the numerator because revenue overstates what a customer is worth. Of every $95 the default customer pays, $19 goes to hosting, support and payment processing before it can fund anything else. An LTV built on revenue instead of margin runs 25% high at these inputs, and far higher for AI products carrying heavy inference costs.

Three examples at different scales

A side project charges $9 a month for a niche API tool. Margin is 92% because the stack costs almost nothing, but churn runs at 6% — hobbyist customers leave quickly. Monthly margin is 9 × 0.92 = $8.28, LTV is 8.28 ÷ 0.06 = $138, and the average customer lasts 16.7 months. Search ads bring signups at roughly $40 each, putting the ratio near 3.5 : 1. Small numbers, sound economics.

A funded startup matches the defaults: $95 per account, 80% margin, 2.4% monthly churn, $1,150 fully-loaded CAC. LTV is 76 ÷ 0.024 = $3,167 and the ratio is 3,167 ÷ 1,150 = 2.8 : 1, just under the 3 : 1 line. This company has a retention question more than an acquisition problem: cutting churn to 2.0% lifts LTV to $3,800 and the ratio to 3.3 : 1 without touching the sales budget.

A mid-market scale-up pays $24,000 to land accounts worth $1,250 a month at 78% margin, and loses only 0.8% of customers monthly. Monthly margin is $975, LTV is 975 ÷ 0.008 = $121,875, the implied lifetime is 125 months, and the ratio is 5.1 : 1. Two caveats travel with numbers like this: a ten-year lifetime extrapolated from one month of churn data is a projection, not an observation, and a ratio above 5 : 1 can mean the company is buying less growth than the market would sell it.

Customer churn is not revenue churn

This formula wants customer churn — the percentage of accounts that cancel — because it values an average account. Revenue churn weights cancellations by dollars, and the two diverge whenever churn is uneven across account sizes. Picture 100 customers averaging $95 where four cancel in a month, all of them small accounts paying $20. Customer churn is 4%; revenue churn is 80 ÷ 9,500, about 0.8%. Feed the revenue figure into this formula and LTV grows almost fivefold for no real reason.

Net revenue churn is worse still: with enough expansion revenue it turns negative, and a negative churn rate here yields a negative LTV. Expansion is real value, but it belongs in a separate metric — net revenue retention — while this formula does the one job it does well, valuing the account you sign today at the price you signed it.

Reading the ratio

The 3 : 1 benchmark exists because gross profit still has other bills to pay. After acquisition cost is recovered, what remains must cover R&D, G&A and eventually profit; three dollars of lifetime margin per acquisition dollar historically leaves enough. Below 1 : 1 every customer costs more to win than they return; between 1 : 1 and 3 : 1 the model works only if churn holds and costs stay flat.

The counterintuitive case is a high ratio. 5 : 1 sounds like an achievement, and sometimes it is — the scale-up above earns it through genuinely low churn. But a persistently high ratio often says the company is underinvesting: channels return five for one and the budget never rises to meet them, while cheap channels rarely stay cheap once competitors notice. The ratio also ties directly to CAC payback. Both sides of it rest on the same monthly margin, so the ratio reduces to lifetime in months divided by payback in months: the default 2.8 : 1 is a 41.7-month lifetime over a 15.1-month payback.

What the constant-churn assumption hides

Dividing by churn assumes the rate never changes: every month the same fraction of surviving customers leaves, regardless of tenure. Real cohorts do not behave that way. Churn concentrates in the first few months, when customers who bought the wrong product discover it, and flattens among survivors who have built the product into how they work. A blended rate taken across the whole base therefore depends on the base's age mix — a fast-growing company's base skews young and churny, understating the LTV of the customers who will actually stay, while a mature base skews the other way.

Annual plans distort the measurement further. A yearly contract can only cancel at renewal, so moving customers onto annual billing drags measured monthly churn toward zero for up to eleven months, inflating LTV until it corrects abruptly. Compute churn on accounts that actually faced a renewal decision.

The formula also applies no discounting — margin earned in month 120 counts the same as month one, which flatters low-churn businesses most. Treat the output as an upper bound, and re-run it quarterly against fresh cohort data rather than trusting one snapshot.

LTV as computed here is a modeling shortcut, not a valuation of any customer base or advice on acquisition spend. See the site disclaimer.

Frequently asked questions

What is a good LTV to CAC ratio for SaaS?

3 : 1 is the figure most investors anchor on: three dollars of lifetime gross profit for every dollar spent acquiring the customer. Between 1 : 1 and 3 : 1 the business works but has little room for error, and below 1 : 1 every new customer loses money. Ratios above 5 : 1 often signal underinvestment rather than brilliance — the channels are returning five for one and the budget has not been raised to meet them.

How do I calculate LTV from monthly churn?

Multiply monthly revenue per account by gross margin, then divide by the monthly customer churn rate. At $95 a month, 80% margin and 2.4% churn: 95 × 0.80 = $76 of monthly margin, and 76 ÷ 0.024 = $3,167. The division by churn is a geometric-series shortcut for summing margin over an average lifetime of 1 ÷ 0.024 = 41.7 months.

Should I use customer churn or revenue churn in the LTV formula?

Customer churn. The formula values an average account, so the churn rate must describe accounts, not dollars. Revenue churn usually runs lower because large accounts churn less, so plugging it in overstates per-account LTV. Net revenue churn can even go negative once expansion revenue is counted, and a negative rate here produces a negative LTV, which means nothing.

Why is my LTV so high at 1% monthly churn?

Because 1% churn implies a 100-month average lifetime, and the formula adds up margin over more than eight years. At $95 and 80% margin that is 76 ÷ 0.01 = $7,600 per customer. The arithmetic is right and the projection is fragile — it assumes today's churn rate holds for a decade. Treat low-churn LTVs as an upper bound, not a forecast.

Do annual plans change measured churn and LTV?

Mechanically, yes. An annual contract can only cancel at renewal, so moving customers from monthly to annual billing drags measured monthly churn toward zero for up to eleven months with no change in actual renewal behavior. If a meaningful share of your base is on annual plans, compute churn only on accounts that reached a renewal decision in the period, or measure annually and convert.