Customer lifetime value is the ceiling on what you may spend to win a customer — but only if you compute it in profit, not in revenue. This LTV calculator uses the standard model: average purchase value × purchases per year × years the customer stays, with a gross-margin toggle that converts the flattering revenue figure into the gross-profit figure your ad budget is actually paid from. It is an estimate model — a way to think with numbers, not a prediction about any individual customer.
There is a full Spanish version of this calculator: Calculadora de LTV — Valor de Vida del Cliente.
The model
LTV = average purchase value × purchases per year × customer lifespan in years. Multiply by your gross margin percentage and you get profit LTV. The three inputs should come from your real data: average order value from your store platform, purchase frequency from a cohort of customers over a full year (not from your best month), and lifespan from how long customers actually keep buying — for many young stores the honest answer is “we don’t know yet”, in which case run the model at a cautious 1–2 years and again at your hoped-for figure, and plan with the cautious one.
Worked example
Average purchase $45, 4 purchases a year, 3-year lifespan: revenue LTV = 45 × 4 × 3 = $540. At a 30% gross margin, profit LTV = $162. The difference is not academic: at a CAC of $135 the revenue figure suggests a comfortable 4:1 ratio, while the profit figure says you recover your acquisition cost with only $27 to spare — before fees, support and returns have eaten anything. The calculator shows both, plus the per-year and per-month revenue, so you can sanity-check the model against what a customer actually brings in each month ($15 in this example).
Where the model misleads
It assumes a typical customer who buys steadily and then stops — real customers arrive in cohorts, buy in bursts and churn unevenly. It ignores the time value of money (revenue in year 3 is worth less than revenue today, and discounting it properly would lower the figure). And averages hide shape: if 10% of customers generate 60% of revenue, a single average LTV describes almost nobody. Use the output as a planning range and segment it — new vs returning, channel by channel — before you let it set an ad budget.
What to do with it
Divide profit LTV by your CAC (the ratio calculator linked below does exactly this), and use per-month profit to judge payback: a customer worth $4.50 of monthly gross profit against a $135 CAC pays you back in 30 months — longer than many of them will stay. Raising frequency or lifespan is usually worth more than raising the ticket, because both multiply the whole model.
A quick reality check you can run
Before trusting any LTV figure, test the model against a real cohort: take customers acquired in one month a year or more ago, add up what they actually spent in their first twelve months, and divide by how many there were. If that realised first-year value per customer is far below the model’s per-year revenue line, the model’s frequency or lifespan input is a hope rather than an observation, and every decision downstream — the ratio, the ad budget, the payback — inherits the error. Stores with subscriptions can shortcut this: monthly revenue per subscriber × gross margin ÷ monthly churn rate gives a margin LTV with the same meaning (a $20/month subscriber at 70% margin and 5% monthly churn is worth 20 × 0.7 ÷ 0.05 = $280 in gross profit), and comparing the two models on the same business is a good way to catch an optimistic input in either.
Related tools
Versión en español: Calculadora de LTV: Valor de Vida del Cliente con Ticket, Frecuencia y Margen · CAC Calculator · LTV:CAC Ratio Calculator.
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