DTC Contribution-Profit & True-CAC Payback Calculator
First-order ROAS hides the number that actually pays salaries. Enter your AOV, gross margin, variable cost, CAC, and repeat rate to see contribution profit per customer, the true payback in orders, and the break-even repeat rate your brand needs to make money.
A direct-to-consumer order is worth its contribution margin — AOV × gross margin − variable cost — not its revenue. Subtract CAC and the first order usually loses money by design. This calculator shows exactly how underwater order one is, how many orders it takes to pay CAC back, and the repeat rate at which a customer finally turns a profit. It ends with one number: contribution profit per acquired customer.
Enter your numbers
The defaults are illustrative — a mid-AOV consumables brand — and set up to teach: the first order loses money, but a healthy repeat rate turns the customer profitable. Change every field to your own figures.
| Order | Cohort still buying | Cumulative contribution | Status |
|---|
How to use this calculator
- Enter AOV and gross margin honestly.Use your trailing average order value and the margin left after cost of goods only. Discount-heavy brands should use the post-discount AOV they actually bank.
- Put every variable cost in one field.Shipping, fulfillment, payment fees, and a returns allowance all scale with orders — they belong in variable cost per order, separate from CAC.
- Use blended CAC, not platform-reported.Total sales and marketing spend divided by new customers. Platform-reported CAC understates the real cost after iOS signal loss.
- Slide the repeat rate.Watch the break-even line. Below the break-even repeat rate every customer loses money; above it, profit compounds with each repeat order.
- Read the payback table, then export.See exactly which order pays CAC back, copy a share link, download the CSV, or print a one-page PDF for the planning meeting.
RGM Expert Says
The first thing we do with a direct-to-consumer brand is delete the ROAS screenshot and rebuild the P&L one order at a time. A 2.5× first-order ROAS looks like a win until you subtract cost of goods, the shipping label, the payment fee, the returns you quietly eat, and the acquisition cost — and discover the first order lost money. That is not a failure; for most DTC brands it is the design. You spend to buy the customer on order one and make the money back on orders two, three, and four.
Which is why the number we actually manage to is the one this calculator ends on: contribution profit per customer. It folds contribution margin per order and the repeat behavior into a single figure that a CFO will sign. The break-even repeat rate is the companion insight — the retention you need before acquisition even makes sense. When a brand is losing $8 on the first order, as the default here does, a 23% repeat rate is the line between a business and a slow-motion cash fire. Raise AOV with a bundle, lift margin, or drive the second purchase sooner, and that line moves in your favor fast.
The trap we see most is scaling acquisition against first-order ROAS while the repeat rate quietly sits below break-even. It feels like growth — revenue climbs — but every new customer deepens the hole. Fix the contribution math first, prove the second order compounds, and only then pour fuel on acquisition. First order buys the customer; the second order is the business.
How it works
Every figure comes from four simple steps. First, the contribution margin per order — what one order contributes before you count acquisition cost:
Next, the true payback — how many orders it takes to earn back CAC:
Then the contribution profit per customer. Using a geometric repeat model, an acquired customer is expected to place 1 ÷ (1 − r) orders, where r is the repeat rate:
Set that to zero and solve for r to get the break-even repeat rate — the retention at which a customer just covers acquisition cost:
- CMorder — contribution margin per order, after COGS and all variable costs but before CAC. If it is zero or negative, no repeat rate ever turns a profit.
- r — the per-order probability of another order. Expected lifetime orders = 1 ÷ (1 − r); a 50% repeat rate implies two orders on average, 75% implies four.
- Payback order — the first whole order at which cumulative contribution turns positive, i.e. ⌈ CAC ÷ CMorder ⌉.
Contribution margin and CAC payback are standard unit-economics arithmetic. The geometric repeat model (expected orders = 1/(1−r)) is a deliberately simple, illustrative approximation — real cohorts decay on their own curve — so treat the lifetime figures as a directional model (RGM analysis), not a forecast. We build the real cohort curve on your data.
First-order ROAS is the most expensive number in DTC
Customer acquisition got dramatically more expensive: SimplicityDX found acquisition cost rose roughly 222% over eight years, to the point where brands lose about $29 acquiring the average new customer. When the first order loses money, the entire business case rests on what happens next — and first-order ROAS, by definition, cannot see it. A brand optimizing to ROAS is optimizing to the one metric that ignores COGS, shipping, fees, returns, and most of CAC.
The fix is to manage contribution profit and repeat rate instead. The average ecommerce repeat purchase rate is about 28%, and roughly half of repeat buyers return within 30 days — a window most brands leave wide open. The economics of that second order are overwhelming: the probability of selling to an existing customer is 60–70%, versus 5–20% for a new prospect (Farris et al., Marketing Metrics). A repeat order carries almost no acquisition cost, so nearly all of its contribution margin drops to the bottom line.
That is the whole reason this calculator exists: to move the conversation from a flattering ROAS to the two numbers that decide whether a DTC brand survives — how much an order truly contributes after every variable cost, and how often customers come back. Get those right and acquisition becomes an investment with a known payback. Get them wrong and scaling spend just buys a bigger loss.
Rules of thumb for reading the numbers
Use these as sanity checks, not targets. They come from widely cited public sources; your own data always wins where you have it.
| Signal | Rule of thumb | Read it as |
|---|---|---|
| Repeat purchase rate | ~28% average; 40%+ top brands | Below ~20% and your economics lean hard on the first order |
| CAC payback | Recover CAC within 1–3 orders | Longer payback needs deeper pockets and higher retention |
| LTV : CAC | Roughly 3:1 or better | Below it, growth costs more than it returns |
| Cart abandonment | ~70% documented average | Recovery flows are cheap contribution you already earned |
| Existing vs new buyer | 60–70% vs 5–20% purchase probability | The second order is far cheaper than the first |