Customer Lifetime Value Calculator

Customer lifetime value is built on margin, and revenue ruins the number

Customer lifetime value asks one question: over the whole relationship, how much money does this customer leave behind? What stays with you, not what they pay. Those are different amounts. Mixing them up is the most common mistake in the whole subject, and it survives because the result doesn't look wrong afterward. The number just comes out bigger, and nobody gets suspicious of a bigger number.

Take the default scenario on this page. A customer bills $200 a month. At 80% gross margin, $160 of that is gross profit. After $10 a month of support and dedicated infrastructure, contribution margin is $150. At 4% monthly churn, the correct lifetime value is $3,750. Run the same math on revenue and you get $5,000, a third higher, from one swapped input.

That inflation doesn't stay put. It flows into the LTV:CAC ratio, and that's where it costs you: $5,000 against a $1,200 CAC reads as 4.2:1, comfortably above the threshold everyone quotes. The real number is 3.1:1, and discounted it's 2.5:1. Same company, same month, three different verdicts. Only one of them uses money the business actually has.

That's why the calculator above keeps the revenue-based figure on screen, in red, instead of burying it in a footnote. Almost nobody knows they're making this mistake. Seeing both numbers at once is how you find out.

Where to draw the line: gross margin should absorb cost of goods, meaning hosting, payment processing, third-party licenses and anything else that scales with usage. The separate cost-to-serve field is for real costs that sit outside that line in your books, like support headcount, customer success and dedicated infrastructure. If those are already inside your gross margin percentage, leave the field at zero. Counting them twice is a quieter mistake than leaving them out, but it's still a mistake.

Lifetime = 1 ÷ churn, and the assumption under it

Average lifetime is the reciprocal of the churn rate. At 4% monthly churn the average customer stays 25 months. At 2%, fifty months. The formula is tidy and useful, and it rests on an assumption that is almost never true: that the churn rate stays constant over time.

It doesn't. Churn is heavily front-loaded. Customers who never got onboarded properly, who bought for a project that ended, or who were sold badly leave in the first few months. The ones still paying after two years have built the product into how they work, and they cancel at a fraction of the rate. Plot churn by cohort age and you get a decay curve, not a flat line.

That can push your estimate either way, depending on where your churn input came from:

• Churn measured on new cohorts and extrapolated forever understates lifetime, sometimes by a lot. It takes the worst stretch of the relationship and assumes it never ends.
• Churn measured across a mature base overstates lifetime for the customers you're signing today, because survivors who already made it past the risky window are holding that blended rate down.

Neither is a reason to drop the formula. The alternative is fitting survival curves per cohort, which is the right answer for a company with a data team and overkill for everyone else. It is a reason to treat the lifetime figure as a planning number with a wide range around it, and to distrust any decision that flips when lifetime moves 30%. If you can only measure one thing better, measure churn separately for customers under twelve months and over twelve months, and run the calculator twice.

Monthly churn and annual churn don't convert by multiplying

This is pure arithmetic, and a surprising number of spreadsheets get it wrong. You don't get annual churn by multiplying monthly churn by twelve. The correct conversion compounds:

annual = 1 − (1 − monthly)¹²

At 4% a month, the annual figure is 38.7%, not 48%. At 5% it's 46.0%, not 60%. At 8%, which sounds disastrous and is common in SMB self-serve, it's 63.2%, not an impossible 96%. Each month's churn applies to a base that has already shrunk, so the losses don't stack in a straight line. Going the other direction uses the same relationship turned around: 30% annual churn is 2.93% monthly, not 2.5%.

This is worse than a rounding error because the mistake usually happens when someone enters the number, not in the formula. Someone reads "30% annual churn" off a board deck, types 30 into a field labeled monthly, and every number downstream is off by an order of magnitude. The calculator above shows both readings of churn at all times for exactly that reason. If the number in the echo line looks absurd, the number you typed is in the wrong unit.

Why this LTV calculator shows two lifetime values

Margin ÷ churn treats a dollar that arrives in year seven the same as a dollar that arrives this month. For a customer who stays eighteen months, that shortcut does no harm. Past roughly three years, it does.

The discounted version does what finance would do. It takes the expected margin in each future period, weights it by the probability the customer is still around to pay it, discounts it back at your cost of capital, and stops at a horizon you pick. On the default scenario that turns $3,750 into $2,959, about 79% of the simple number.

The gap grows fast with lifetime, and that's the whole point. At 1% monthly churn, the average customer lasts a hundred months and the simple LTV reaches $15,000. Discounted at 10% a year over a ten-year horizon, it's around $7,382, under half. The longer the contract you're modeling, the more the undiscounted number describes a hypothetical future instead of a decision you can make today.

The calculator breaks that gap into its two causes instead of showing one lump. Part of it is truncation: value past your horizon that the simple formula counts and the discounted one doesn't. The rest is the time value of money. Those are different objections, and you can accept one and reject the other. If the horizon is doing most of the damage, extend it. If discounting is doing it, that's no modeling artifact. That's your cost of capital, and it's real.

The 3:1 LTV:CAC rule: where it came from and what it leaves out

An LTV:CAC ratio of at least 3:1 is the most-quoted benchmark in subscription businesses. Know what it is: a venture-capital rule of thumb from the early 2010s, shorthand for the fact that gross margin has to cover more than acquisition. It also has to pay for R&D, general overhead, and the customers you win and lose before they ever break even. Around three times CAC, there's usually enough left for all of that. Below roughly 1:1 you're plainly destroying value.

What the rule leaves out matters just as much. It says nothing about how the LTV was calculated. A 3:1 computed on revenue is often a 2:1 on margin, and the rule assumes margin. It says nothing about whether you can finance the CAC, which is a cash question, not a profitability one. And a ratio far above 3:1 is no reason to celebrate. A sustained 8:1 usually means a company is underinvesting in growth and leaving a market open.

Use it as a rough sanity check, and always next to payback.

CAC payback decides whether you survive the quarter

LTV:CAC asks whether a customer is worth acquiring. CAC payback asks how long your money is gone before it comes back. Unless you're sitting on unlimited cash, the second question is the one that limits you.

A business with 5:1 economics and a twenty-month payback runs out of money while growing. Every new customer eats working capital that doesn't come back inside the fiscal year, so growth itself drains the account. A business at 2.5:1 with a six-month payback recycles the same capital twice a year and compounds off a much smaller balance sheet. The first company looks better on the slide.

The calculator gives two payback figures. The nominal one is CAC divided by margin per period, the standard industry number, which quietly assumes nobody cancels before payback. The survival-adjusted one asks when the expected cumulative margin covers the CAC, counting the customers who leave along the way. It's always longer. If the CAC is bigger than the whole lifetime value, it says the CAC never pays back, instead of printing a large finite number that reads as "slow, but fine". It isn't fine.

How to fill in the LTV calculator without fooling yourself

• Take ARPU from customers who look like the ones you're signing now, not from a blended average pulled up by legacy enterprise accounts.
• Use the gross margin from your books, not the one you're hoping for. If you don't know it, revenue minus hosting, payment fees and third-party licenses, divided by revenue, is close enough to start.
• Enter customer churn, not revenue churn, because the model counts customers. If you have meaningful expansion revenue, net revenue retention tells a different story that also matters, but don't mix the two inside one formula.
• Set the discount rate to your cost of capital. For a funded company it's high, because equity is expensive. Ten percent is a common floor. Zero is a deliberate choice to see the undiscounted figure, not a neutral default.
• Load CAC fully: paid media, sales salaries and commissions, and the tools behind them, divided by customers actually won. Ad spend alone usually understates it by half or more.

What this tool doesn't do

It models one customer segment with a constant churn rate. It doesn't fit survival curves per cohort, model expansion or contraction revenue, handle several price tiers with different retention, or account for referrals from existing customers. Those effects are real, and the tool that models them properly is a data warehouse, not a web page.

Everything runs in your browser as plain arithmetic. Nothing is uploaded, nothing is logged and there's no account. That's worth saying outright, because ARPU, margin, churn and CAC together describe a company's unit economics about as completely as four numbers can.