Unit Economics Review
Find out if your business actually makes money per customer — and when.
A clear read on CAC, LTV, margin and payback, with the lever that fixes it.
Unit economics flatter their author: definitions drift, averages hide cohorts, and the deck version of CAC rarely survives an audit. So the Forensic Accountant re-derives the numbers from their definitions, the Data Skeptic hunts the cohort behaviour underneath the averages, and the CFO judges whether the machine makes money at scale. The Pricing and Retention Strategists own the two levers that usually fix broken economics, and the Devil’s Advocate argues the bear interpretation of every ratio.
Review our unit economics. I need the honest picture, not the optimistic one. THE NUMBERS: [revenue per customer, gross margin, CAC, retention/churn, payback period, any cohort data you have] THE MODEL: [how you charge, the sales motion, the channels] Debate: 1. Are these numbers real and consistently defined, or are we flattering ourselves. 2. LTV:CAC and payback — healthy, fragile, or fantasy. 3. Where the economics break as we scale (rising CAC, churn, support load). 4. The single biggest lever — pricing, retention, margin, or acquisition cost. 5. The cohort behaviour underneath the averages. FINAL SYNTHESIS: - A plain-language verdict on whether the unit economics work, and at what scale. - The numbers we cannot trust and need to re-measure. - The one lever that most improves the economics, with the expected effect.
An illustrative excerpt for a hypothetical brief of this type: A subscription meal-kit company reports LTV:CAC of 4:1 in its board deck, but blended CAC mixes paid and organic, and LTV is computed from the twelve-month-old cohorts only. Every real run is generated fresh from your specifics, debated across rounds, and audited before the verdict.
Two definitional problems make the 4:1 unusable. Blended CAC averages cheap organic customers into the paid number — on marginal paid spend, the true acquisition cost is what the next dollar buys, and that is what decides whether to scale spend. And LTV from the oldest cohorts assumes today’s customers behave like the early adopters. Recompute both before this ratio appears anywhere.
The cohort curves in the appendix contradict the headline: recent cohorts churn faster in their first eight weeks than the old cohorts did. If that trend holds, the real forward-looking LTV:CAC is materially below the deck number. The average is not lying, exactly — it is answering a question nobody should be asking.
The interesting fact is where the churn concentrates: the first month, around the moment the novelty fades and the price renews. That is not an economics problem, it is an onboarding problem wearing an economics costume — the highest-leverage fix is the week-three experience, not the acquisition budget.
Synthesis of the numbers as they stand: paid-marginal CAC against realistic forward LTV puts payback well past a year, which this balance sheet cannot fund at the current growth plan. The honest verdict is that the economics work at a slower spend level while the retention fix is proven — that is a strategy, not a failure.
Prefer drop-and-go? Use the Unit Economics Review tool — team pre-seated, included with Plus.
Which numbers do I need before running this review?
Revenue per customer, gross margin, CAC (split paid versus blended if you can), churn or retention by cohort, and the payback period as you currently calculate it. Imperfect data is expected — identifying which of your numbers cannot be trusted is explicitly part of the deliverable.
My LTV:CAC looks great — why would I stress-test it?
Because the flattering version of the ratio is the default output of every dashboard: blended CAC, average LTV, oldest cohorts. If the number survives re-derivation from definitions, you get to trust it — and a stress-tested 3:1 is worth more in a board meeting or a fundraise than an unexamined 4:1.
Does the review tell me what to fix, or just re-audit the maths?
It commits to the single biggest lever — pricing, retention, margin or acquisition cost — with the expected effect and the reasoning, because “improve everything” is not a plan. In the example above, the verdict names week-three onboarding, not ad spend, as the fix.