LTV / CAC / churn calculator

Three numbers decide whether SaaS growth funds itself or quietly burns cash: what a customer is worth, what they cost to win, and how fast you earn it back. Plug in your ARPU, margin, churn, and CAC — and see the unit economics the pitch deck rounds off.

Customer LTV

$1,000

gross-margin value over a 25-month lifetime

LTV : CAC

3.3×

Healthy · 3× is the usual healthy bar

CAC payback

7.5 mo

months to earn back the acquisition cost

These unit economics work: each customer returns 3.3× their acquisition cost. With payback under a year you can reinvest in growth without straining cash.

LTV = (monthly revenue × gross margin) ÷ monthly churn. The ratio to CAC and the payback period are the two numbers that decide whether growth funds itself or burns cash. Churn is the most powerful lever — halving it doubles the lifetime, and the LTV with it.

The three numbers, and how they fit together

LTV (lifetime value) is the gross-margin profit a customer generates before they churn. CAC is what you spent to win them. The LTV:CAC ratio tells you whether each customer is worth more than they cost, and the payback period tells you how long your cash is tied up before they turn profitable. Together they answer the only question that matters early: does adding customers make you money or cost you money?

Why churn is the lever to pull first

Average customer lifetime is simply the inverse of churn — 4% monthly churn means a customer sticks around about 25 months. Because LTV scales directly with lifetime, halving churn doubles LTV. No pricing change or CAC cut compounds like that. Before optimizing acquisition, it's almost always worth fixing the leak in the bucket first.

A worked example

A $50/month product at 80% gross margin generates $40/month of contribution. At 4% monthly churn the customer lasts ~25 months, so LTV is about $1,000. If CAC is $300, the LTV:CAC ratio is ~3.3 — healthy — and payback is about 7.5 months. Now let churn rise to 8%: lifetime halves to ~12.5 months, LTV falls to ~$500, and the ratio drops to ~1.7 — still profitable, but no longer comfortable to scale. Same product, same spend; churn alone moved it from healthy to thin.

How to use it

Run your real numbers, then test the levers: what does cutting churn by a quarter do to LTV? Does a lower CAC or a higher margin move the needle more? Pair this with the SaaS Subscription Audit to find the spend to cut, and the annual-vs-monthly toolto price your own billing options the way you'd price a customer's.

Frequently asked questions

What is a good LTV:CAC ratio?

The widely-used benchmark is 3:1 — a customer should return about three times what they cost to acquire. Below 1:1 you lose money on every customer. Between 1 and 3 you're profitable but with little headroom to absorb a churn or cost shock. Much above 3 can mean you're under-investing in growth. It's a guide, not a law: the right number depends on your margins and how fast you need to grow.

How do you calculate customer LTV?

LTV = (monthly revenue per customer × gross margin) ÷ monthly churn rate. The monthly churn term sets the average customer lifetime — a 4% monthly churn implies a 25-month lifetime. Using gross-margin revenue (not raw revenue) matters, because the value of a customer is the profit they generate, not the top-line they pay.

What is CAC payback period?

It's how many months of gross-margin revenue it takes to earn back what you spent acquiring a customer: CAC ÷ (monthly revenue × gross margin). Under ~12 months is generally healthy for SaaS; longer paybacks strain cash because you're financing growth for longer before each customer turns profitable.

Why does churn matter so much to LTV?

Because lifetime is the inverse of churn, and LTV scales with lifetime. Halving your monthly churn doubles the average customer lifetime — and doubles LTV with it. That's why reducing churn is almost always a higher-leverage move than raising prices or cutting CAC: it compounds through the entire lifetime value calculation.

Independent analysis, not financial advice. Uses a simplified constant-churn model; real cohorts decay unevenly.

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