Customer Lifetime Value Calculator
What's a customer worth — really? Plug in AOV, frequency, lifespan, and margin to compute CLV plus the LTV-to-CAC ratio.
How often a typical customer buys from you per year.
How many years the average customer stays active.
For the LTV-to-CAC ratio.
Result
AOV × frequency × lifespan. Pre-margin.
What the customer is actually worth to your bottom line.
Healthy. Most SaaS aims here.
The formula
CLV = AOV × purchases per year × lifespan years × gross margin
This is the simple version. More sophisticated formulas use cohort retention curves and discount cash flows to net present value — useful for valuation, overkill for week-to-week marketing decisions.
Why simple LTV beats fancy LTV for marketing
Fancy LTV models (predictive, ML-driven) almost always produce a number 2–4x bigger than the simple cohort-based number. That number gets used to justify higher CAC, which gets approved by finance because the ratio still looks fine. Six months later, the actual cohorts under-perform the prediction and CAC was already raised. This pattern is so common it has a name: LTV inflation.
Use simple historical CLV for marketing-budget decisions. Save the predictive models for retention prioritization.
FAQ
What's the difference between CLV and LTV?⌄
They are the same thing — Customer Lifetime Value = LifeTime Value. Use whichever your team prefers; just be consistent.
What's a healthy LTV-to-CAC ratio?⌄
For SaaS, the consensus benchmark is 3:1 or better. Below 1:1 you're losing money per customer; 1–3:1 means you're alive but unhealthy; 3–5:1 is solid; >5:1 sometimes means you're under-investing in growth.
Should I use predictive or historical CLV?⌄
For ad-budget decisions, use historical (cohort-based) — the actual revenue a customer cohort has generated to date, projected forward conservatively. Predictive CLV is great for retention prioritization but tends to inflate the number used to justify higher CACs.
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