acquisition spend ÷ unique newly acquired customersDefine the spend boundary and customer identity policy. A platform-reported new-customer count can differ from a deduplicated commerce or CRM customer cohort.
Calculator
Model payback for one acquisition cohort
Use one cohort definition, reporting currency, and contribution-profit policy. Month 0 is the first purchase. Repeat contribution begins in month 1 and is reduced by the same retained-active rate each month. Inputs stay in your browser and are not submitted or stored.
Formulas
What the calculator is doing
monthly contribution per active customer × retained-active rateⁿThe model applies one constant retention curve and one constant monthly contribution amount. Real cohorts usually vary by month, segment, product mix, and season.
first-purchase contribution + sum(month 1 … month n contribution)Contribution should use a documented cost boundary after refunds, COGS, fulfillment, payment fees, and other included variable costs.
earliest point where cumulative contribution ≥ CACThe calculator interpolates within the first month that crosses CAC. If the cohort does not cross CAC in the selected horizon, it reports that boundary directly.
first purchase + monthly contribution × retention ÷ (1 − retention)For retention below 100%, this geometric limit shows whether the simplified lifetime model can ever recover CAC. It is not a predicted customer lifetime value.
Assumptions checklist
Define these before sharing payback
- New-customer identity.Define the lookback window, identity keys, guest-checkout treatment, account merges, and whether unknown customers are excluded. Count unique people or customer records, not purchase events.
- Acquisition spend boundary.State whether CAC includes only paid-media spend or also agency fees, creative production, discounts, sales commissions, and other acquisition costs.
- Cohort assignment.Group customers by a defined first-order or acquisition date and keep the same brand, market, channel, store, and currency scope across spend and profit.
- Contribution-profit policy.Document revenue, refunds, COGS, fulfillment, payment fees, and other variable costs. Revenue or gross margin alone usually overstates cash recovery.
- Timing convention.This model puts first-purchase contribution in month 0 and repeat contribution in later months. Change the model if collections, returns, subscriptions, or fulfillment create different cash timing.
- Retention and censoring.A recent cohort has not had time to mature. Separate observed months from projected months and do not treat one constant retained-active rate as measured future behavior.
- Attribution and incrementality.Allocating acquisition spend to a cohort does not prove the campaign caused every customer. Use experiments or another defensible causal method when incremental CAC is the decision metric.
Interpret the result
What this calculator can and cannot tell you
Can: expose the unit economicsShows how CAC, first-purchase contribution, repeat contribution, and retention interact.
Can: test scenariosLets you compare payback under clearly labeled retention and contribution assumptions.
Can: flag impossible paybackShows when the geometric lifetime contribution never reaches CAC under the entered assumptions.
Cannot: validate the inputsDoes not know whether spend, customer identity, refunds, COGS, or repeat orders are complete.
Cannot: predict retentionA constant retained-active rate is a scenario simplification, not a forecast or confidence interval.
Cannot: prove causalityObserved new customers and allocated spend do not establish incremental acquisition.
Cannot: replace cash planningContribution timing is not collections timing and excludes fixed expenses, financing, and tax.
Cannot: replace cohort analysisUse actual month-by-month cohort contribution when sufficient history exists.
Primary sources: verify customer and cohort definitions
The payback model is a Metric Hive modeling convention. Validate how each source identifies new customers, cohorts, orders, and repeat behavior before mapping source data into it.
Related guides
Build the profit and cohort inputs
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Map orders, refunds, COGS, fulfillment, payment fees, and paid media into governed profit.
Ecommerce profit metrics glossary
Keep revenue, margin, contribution, and customer value definitions separate.
Keep CAC, cohorts, and contribution profit on explicit contracts
Metric Hive can preserve customer lifecycle, cost, revenue, and acquisition assumptions across governed datasets. It cannot turn incomplete identity, attributed media claims, or a simplified retention curve into causal proof.