SaaS Metrics Calculator

New to the return arithmetic that LTV:CAC and CAC payback lean on? The companion guide ROI and CAGR explained works through total return versus annualised return from first principles — the same distinction between a whole-relationship figure and a per-period one that separates LTV from payback here. It sits in the wider Sumvia guides alongside the other business-math explainers, with the implementation details on the methodology page.

What each metric means

Contribution per account is ARPU × gross margin — the monthly gross profit one account generates. In the example, 100 at 80% margin contributes 80 a month; the other 20 is consumed by serving the account. (Unsure of your margin? The profit margin calculator works it out from revenue and cost, and keeps margin distinct from markup.)

Lifetime value (LTV) divides that contribution by the monthly churn rate: 80 ÷ 0.02 = 4,000. Equivalently, a 2% monthly churn rate implies an average customer lifetime of 50 months, and 80 a month for 50 months is the same 4,000. All figures on this page are computed at build time by the identical engine behind the form.

LTV:CAC compares that lifetime gross profit to the 1,200 it cost to acquire the account: 4,000 ÷ 1,200 = 3.33 — each acquisition dollar eventually returns about 3.33 dollars of gross profit. CAC payback asks the nearer-term question — how long until the acquisition cost is earned back — and answers in months: 1,200 ÷ 80 = 15. Payback is the same idea as a return on investment reaching zero, expressed on a clock instead of as a percentage.

The 3:1 convention is a rule of thumb, not a law

LTV:CAC is simply LTV ÷ CAC — how many dollars of modelled lifetime gross profit the model assigns to each dollar spent acquiring an account. A ratio below 1 means the modelled lifetime gross profit does not cover the acquisition cost; a ratio above 1 means it more than covers it, with the surplus still having to pay for the fixed costs that sit entirely outside this model (the break-even calculator handles those). The widely circulated 3:1 figure is a convention, not a law of arithmetic. A higher ratio is not automatically better, either: a ratio of 8 or 10 means each acquisition dollar maps to eight or ten modelled dollars, which can equally describe a business acquiring very few accounts at a very low cost as one acquiring at scale. The ratio reports the arithmetic; what level to aim for is a judgement it does not make.

Why simple LTV overstates for young products

The formula assumes the churn rate you enter holds forever, ARPU never changes, and future gross profit is worth the same as today's. Each assumption flatters the result. Early-tenure customers churn faster than settled ones, so a young product's measured churn understates what its first cohorts will do over a full lifetime; money arriving in year four is worth less than money arriving this quarter, and the simple model applies no discount; expansion revenue may raise ARPU later, but a young cohort has not demonstrated it yet. Treat simple LTV as a first-pass screen and re-measure as cohorts age — the CAGR calculator is the natural companion for tracking how the resulting revenue actually compounds year over year.

The monthly-vs-annual churn trap

Multiplying a monthly churn rate by twelve overstates annual churn, because each month's losses come out of an already smaller base. At 1% monthly, 99% of customers survive each month, and (1 − 0.01)¹² ≈ 0.886 of them survive the year — an annual churn of 11.36%, not 12%. The gap widens as churn rises: the example's 2% monthly rate compounds to 21.53% annually rather than 24%. The calculator always reports the compounded figure. The same asymmetry works in reverse — an annual rate converts to monthly by a twelfth root, not division by twelve — so never mix monthly and annual rates from different sources without converting properly.

A year of growth against a year of churn

Annual churn is not an abstract statistic — it is the hole next year's new revenue must fill before any of it counts as growth. At the example's 2% monthly churn, 21.53% of the revenue base disappears within twelve months, so a business that merely wants to stand still must add 21.53% of its starting MRR in new sales over the year — slightly more, in fact, since the newly added accounts begin churning too. Nudge churn to 3% monthly — a shift small enough to hide inside one quarter's noise — and the annual hole widens to 30.62%, while LTV falls from 4,000 to 2,666.67 and the LTV:CAC ratio from 3.33 to 2.22 — a change driven by churn alone, with pricing, margin, and acquisition cost unmoved. That is why churn deserves obsessive measurement while it still looks small: by the time it shows up in the top-line revenue chart, it has been compounding for months.

Reading CAC payback

Payback months measure risk more directly than the LTV:CAC ratio does, because the ratio leans on lifetime projections while payback only needs the near future to hold. The example's 15 months means each new account is underwater for over a year before contributing anything net — survivable with patient capital, dangerous without. Payback is CAC ÷ the monthly contribution and nothing else, so the longer the payback, the more cash the business must front to grow, and the more a rise in churn matters, since more accounts leave before ever paying back their acquisition.

Which input is worth improving first

The four inputs do not pull on the three outputs equally, and knowing which output each one moves is the practical value of the model. Rerunning the example three ways, changing one input at a time:

Halve churn (2% to 1% monthly) — LTV doubles from 4,000 to 8,000 and the ratio from 3.33 to 6.67, yet payback stays at exactly 15 months, because churn appears nowhere in the payback division. A retention program can transform long-run economics while doing nothing visible to near-term cash recovery.
Cut CAC by a quarter (1,200 to 900) — payback drops to 11.25 months and the ratio rises to 4.44, yet LTV is untouched at 4,000, because what a customer is worth has nothing to do with what one cost to find.
Raise ARPU by a quarter (100 to 125, margin and churn unchanged) — the only single move that improves all three outputs at once: LTV 5,000, ratio 4.17, payback 12 months. Pricing feeds the monthly contribution, and the contribution sits inside every formula on this page.

The mechanics fall out directly. CAC and price are the only inputs payback can see, so they are the two that move how fast acquisition dollars come back. Churn appears nowhere in the payback division but sits in the denominator of LTV, so it owns the long-run figure almost by definition. The same fact read the other way: a change in retention cannot move the payback number at all, because the model places churn outside that calculation entirely.

A worked month, output by output

To watch all four inputs pass through the engine in a single run, take a second fictional account — none of these numbers are targets or recommendations, only labelled example inputs. It bills 60 a month at a 75% gross margin, loses 2.5% of accounts a month, and costs 480 to acquire. The same function behind the form turns those into the six figures below when this page is built:

Contribution per account — 60 × 75% = 45 of gross profit a month.
Expected lifetime — 1 ÷ 0.025 = 40 months, the average tenure a constant 2.5% monthly churn implies.
Lifetime value — 45 a month across 40 months (equivalently 45 ÷ 0.025) = 1,800.
LTV:CAC — 1,800 ÷ 480 = 3.75.
CAC payback — 480 ÷ 45 = 10.67 months; the division does not come out whole, so the displayed figure is the engine's full value rounded for the screen.
Annual churn — 1 − (1 − 0.025)¹² = 26.2%, the compounded equivalent of 2.5% a month rather than the 30% that multiplying by twelve would wrongly suggest.

Change any one of the four and re-run, and only the outputs that input feeds will move — exactly as the three single-input scenarios above show with the first example. The arithmetic is identical whether it runs here at build time or in your browser when you type your own figures.

Frequently asked questions

What goes in the "revenue per account" field?

The average monthly recurring revenue per paying account — total MRR divided by the number of accounts. Annual contracts should be divided by twelve first, and one-time setup fees left out, because every other figure here is a monthly rate.

Why does the calculator refuse a churn rate of zero?

The simple LTV formula divides the monthly contribution by the churn rate, so zero churn would declare every customer infinitely valuable. No real product keeps every customer forever; if churn is genuinely tiny, enter the small positive rate you actually measure and read the large-but-finite result with appropriate suspicion.

Is a 3:1 LTV:CAC ratio a requirement?

No — 3:1 is a widely circulated rule of thumb, not a law of arithmetic. The ratio is simply LTV ÷ CAC: at 3, each acquisition dollar maps to three dollars of modelled lifetime gross profit; at 1, one dollar maps to one; below 1, the modelled lifetime gross profit does not cover the acquisition cost at all. A higher ratio means more modelled gross profit per acquisition dollar and a lower one means less — what level to aim for is a judgement the arithmetic does not make. The example inputs land at 3.33.

Is 1% monthly churn the same as 12% per year?

No. Churn compounds on a shrinking base: after the first month only 99% of customers remain, so the second month's 1% removes slightly fewer customers than the first. Over twelve months, 1% monthly works out to 11.36% annually — computed as 1 − (1 − 0.01)¹², not 1% × 12.

Why is LTV based on gross margin rather than revenue?

Because serving a customer costs money — hosting, support, payment processing. A customer paying 100 a month at an 80% gross margin contributes 80 toward everything else, and it is that 80, not the 100, that eventually repays the acquisition cost. Revenue-based LTV flatters every figure downstream of it.

Why does cutting churn not improve CAC payback?

Because payback divides CAC by the monthly contribution — 1,200 ÷ 80 = 15 months in the example — and churn appears nowhere in that division. Halving the example's churn doubles LTV from 4,000 to 8,000 yet leaves payback at 15 months. Payback measures how fast one surviving account repays its cost; churn decides how many accounts survive long enough to finish repaying.

How does expected customer lifetime relate to the churn rate?

The engine reports expected lifetime as 1 ÷ the monthly churn fraction. At the example's 2% monthly churn that is 1 ÷ 0.02 = 50 months, and multiplying the 80-a-month contribution by those 50 months reproduces the LTV of 4,000 exactly — the two LTV routes are the same arithmetic. It is an average implied by a constant rate, not a prediction about any individual account.

Does the calculator discount future cash flows?

No. The simple model adds up the monthly contribution across the whole expected lifetime at face value, treating a unit of gross profit arriving years from now as equal to one arriving this month. Genuine discounting would lower every LTV figure; because this tool applies none, read its LTV as an undiscounted upper bound rather than a present value.

Figures are processed locally and never transmitted. This is an arithmetic tool using the deliberately simple constant-churn model, not a valuation or investment advice — it reports what your four inputs imply, nothing more. Implementation details are on the methodology page.

SaaS unit economics