Customer LTV Analysis
Lifetime value, LTV:CAC and CAC payback, calculated from your inputs and read back with the decision each number implies.
Run a Customer LTV Analysis
Every figure is calculated from your inputs, not generated. Free, no sign-up.
Average recurring revenue per account, per month.
After direct delivery cost. Enter 78 or 0.78 — both work.
Logo or revenue churn, whichever your model uses. Enter 4 or 0.04.
Fully loaded sales and marketing cost per new customer.
Your own view of customer tenure — used for the capped figure.
We will frame the interpretation around your question rather than a generic summary.
- Analysis (completed)
- Context (completed)
- Inputs
- Review
- Generate
- Result
- Export
What this tool does
Customer lifetime value is the number that decides whether growth is worth paying for. The standard calculation takes the contribution a customer generates each month — revenue multiplied by gross margin — and divides it by monthly churn, giving the value of a customer before you have paid to acquire them. Set against acquisition cost it produces the two ratios that matter most: LTV:CAC, where below 3x is generally considered fragile, and CAC payback, the months before a customer has returned its own cost. This calculator does the arithmetic in Python rather than asking a model to do it, so every figure is exact, and it reports both the perpetuity figure and one capped at your expected lifetime — because a formula that assumes a customer never leaves is not a forecast.
How to use it
- 1Enter monthly revenue per customer. Use recurring revenue per account, not total revenue divided by customers after the fact.
- 2Enter gross margin after direct delivery cost. Both 78 and 0.78 are accepted.
- 3Enter monthly churn on the same basis your own model uses — logo or revenue — and stay consistent across runs so the trend stays readable.
- 4Add acquisition cost fully loaded, including sales and marketing. Understating CAC is the most common way these numbers flatter a business.
A worked example
What a real run looks like
Input — a mid-sized operator, not a generic prompt
Monthly revenue per customer 1,200. Gross margin 78%. Monthly churn 4%. CAC 3,100. Expected lifetime 24 months.
What comes back
Monthly contribution 936. LTV 23,400 on the perpetuity method and 22,464 capped at the 24-month lifetime you supplied — the closeness of the two is itself the finding, because it means the churn and lifetime assumptions agree. LTV:CAC 7.55x against the 3x floor, and CAC payback of 3.3 months against a 12-month B2B target. The interpretation then answers the question you asked: with payback this short, the constraint on growth is sales capacity, not paid-spend efficiency.
Frequently asked questions
How is customer lifetime value calculated?
The standard contribution-margin form: monthly revenue per customer multiplied by gross margin, divided by monthly churn. That gives the value of a customer before acquisition cost. The calculator also reports a capped figure based on expected lifetime, because a perpetuity formula assumes a customer never leaves.
What is a good LTV:CAC ratio?
Three to one is the common rule of thumb. Below 1x the business loses money on every customer acquired; between 1x and 3x unit economics are fragile. Above 5x may mean you are under-investing in growth rather than running an excellent business.
What is a good CAC payback period?
Under 12 months is the usual B2B target, and under 6 months for self-serve. A payback beyond 18 months means growth is funded for a long time before it returns cash, which strains working capital as you scale.
Are these figures calculated or generated?
Calculated. The arithmetic runs in Python on our servers and is pinned by automated tests, so the numbers are exact. The written interpretation around them is AI-generated and instructed to use only those figures.
Is this LTV calculator free?
Yes. The ConsultantAI customer LTV calculator is free and requires no sign-up.
Need this on your own engagement?
The free tool covers the framework. A full ConsultantAI project turns it into a cited, board-ready deliverable built from your documents — market sizing, a financial model, or a complete deck, with every figure sourced.