Customer Lifetime

What it measures

The expected number of months an average customer remains active before cancelling, derived purely from the churn rate. It is a duration, not a dollar value: a 2% monthly churn rate implies an average customer lifetime of 50 months. The figure assumes a constant churn rate going forward and treats every customer as identical regardless of contract value, so a $500/month account and a $50K/month account each contribute the same expected lifespan. It measures how long you keep customers, not how much they are worth while you keep them.

Why it matters

Customer Lifetime is the time horizon underneath every lifetime-value and payback calculation. You multiply it by gross margin per customer to estimate what a customer is worth, and you compare it to your CAC payback period to decide whether acquisition spend pays off before customers leave. Investors read it as a durability signal: a long lifetime means revenue compounds and acquisition costs amortize over many months, while a short lifetime means you are forever refilling a leaky bucket. Because it is the direct inverse of churn, it translates an abstract churn percentage into an intuitive answer to "how long do customers actually stick around?"

How to read it

Read Customer Lifetime as the average runway you have to recover acquisition cost and earn margin from a customer. Longer is better — a 50-month lifetime gives you far more room to profit than a 12-month one. Watch the cadence carefully: a lifetime derived from monthly churn is in months, so always state the unit. Because the relationship to churn is non-linear, small churn improvements at low churn levels create huge lifetime gains: dropping monthly churn from 2% to 1% doubles lifetime from 50 to 100 months, while dropping from 10% to 9% barely moves it. Compare lifetime to your CAC payback period — if customers churn before you recoup acquisition cost, unit economics are broken. Always sanity-check the implied lifetime against your actual cohort retention curves, since the formula assumes churn stays flat forever, which it rarely does.

What good looks like

Watch-outs

• Mixing churn cadences. Inverting a monthly churn rate gives months and inverting an annual rate gives years — confusing the two produces a 12x error in lifetime and every downstream LTV figure.
• Using revenue churn instead of logo churn. Customer Lifetime measures how long accounts stay, so it must be built from logo (customer) churn; revenue churn measures dollar attrition and answers a different question.
• Trusting the steady-state assumption. The formula assumes churn stays flat forever, but real cohorts churn fast early then stabilize — always validate the implied lifetime against actual retention curves before building plans on it.
• Blending dissimilar cohorts. A single company-wide churn rate hides that SMB customers may last 12 months while enterprise accounts last 60 — segment by tier and contract type before inverting, or the average lifetime misleads.

Worked example