The dashboard was never built to tell you the one thing you need to know: is this spend making the business bigger. This is the finance that connects your ad account to your bank account, ending in one number: the exact return to set in the platform so the whole business stays profitable, not just the screen.
The ad account is not the business. It reports numbers about itself.
A founder called me on a Tuesday. His Meta dashboard showed a 7x. He had been scaling on that number for months, adding budget every week because the dashboard kept rewarding him. The problem was his bank account. Flat. Revenue had barely moved in a quarter while spend nearly doubled.
When the account looks strong and the business does not feel it, the cause is almost never the ads. It is the measurement, the margin, or the cash. And it starts with the difference between revenue and profit.
Bigger, louder, far more stressful to hold.
Half the revenue. Double the profit. The asset I would rather own.
Chasing revenue and trusting that margin will widen later is how founders end up three years on with a much bigger, much more fragile company making the same profit they always did. Every section here feeds one final calculation, and the last one hands you the number to set in the platform.
Ask a brand its margin and it hands you the on-paper margin, price minus factory cost, while calling it the real one. The two are not close, and the gap decides whether your ads make money.
Take a $100 t-shirt. The factory charges $30, so the brand says 70%. That is the on-paper margin. It ignores everything else it costs to deliver the shirt. Load it all on and the real margin is closer to 24%.
The numbers the calculator hands you, and what each one is telling you to do.
Your break-even floor is 1 divided by your real margin. At a 40% margin that is 2.5x. Any campaign under it is losing money before overhead. One number tells your whole team where the floor is.
Now watch a discount move that floor. Costs fixed in dollars do not move when the price drops, only the price does, so margin collapses far faster than the discount.
| Scenario | Price | Margin | Break-even floor |
|---|---|---|---|
| Full price | $100 | $40 (40%) | 2.5x |
| 30% off | $70 | $10 (14%) | 7x |
A single 30% coupon pushed the required return from 2.5x to 7x, nearly three times harder, and dropped the break-even ad budget per sale from $40 to $10. Reserve deep discounts for stuck stock, where clearing it at break-even turns dead inventory back into cash. Protect margin with bundles and gift-with-purchase instead.
When your target looks too high to reach, you do not have one problem, you have five levers, and they are not equal. The calculator ranks them for your exact product so you fix the one that moves the number most, not the one that is easiest to talk about.
Your cost to acquire a customer means nothing until you pair it with the gross profit on the first order. A $120 cost is spectacular against $1,800 of first-order profit and a disaster against $40. Same number, opposite verdicts.
And pair it with new-customer profit, not the average. The average is inflated by returning customers who spend more. On new customers only, order value is lower and, if your front end leans on discounts, margin is lower too.
The efficiency metric that survives scrutiny is lifetime gross profit to acquisition cost, time-boxed at 90 and 180 days so it cannot rise forever and justify any spend. Use gross profit, not revenue, because you can only spend the profit.
Lifetime gross profit per customer divided by what they cost to acquire. Scale budgets in the zone.
Enter your current return and the calculator gives you a one-word verdict, the same one I use to decide whether to add budget on Monday morning.
At your current return and monthly spend, the calculator also translates the verdict into this month’s dollars: the contribution you are making now, and the net profit you would make at target. The gap between them is what is on the table.
Your numbers are only half the story until you see them against your category. The calculator compares your real margin, returns, average order value, repeat rate, and new-customer cost to your vertical’s range, each with a cited source.
| Metric | Typical range |
|---|---|
| Real gross margin | 50 to 65% |
| Returns | 20 to 40% |
| Repeat purchase rate | 20 to 28% |
| Average order value | $50 to $120 |
| New-customer cost | $40 to $110 |
Everything above collapses into one calculation, and the exact figures to type in.
You know your real margin, your overhead share, and the net profit you want to keep. The share of revenue left for ads, and the return that share demands, fall straight out.
share for ads = real margin % − overhead % − net target % target ROAS = 1 ÷ share for ads ad budget per sale = price × share for ads
Hit 5.9x and, after ad spend, overhead, returns and every other cost, you keep 12% net per order. The break-even floor underneath it is 2.27x. The space between 2.27x and 5.9x is your cushion. Where it goes:
| Setting | The number |
|---|---|
| Meta purchase campaigns, cost cap (Meta’s name for your ad budget per sale) | $13.60 |
| Meta value optimization, ROAS goal | your target ROAS, calibrated |
| Google PMax / Shopping | tROAS = target · tCPA = ad budget per sale |
Your attribution setting. Your target is measured against real new-customer revenue; the platform reports an attributed number. On 7-day click with no view-through the two sit close, which is why that window is the standard. If your account runs looser settings, measure the gap (platform-reported over actual, trailing 30 days) and multiply your target by it.
The prospecting split. Your target is a blend across all spend, but remarketing mostly harvests demand that was already coming. If remarketing is r of your spend, prospecting alone must clear target divided by (1 minus r). At 20% remarketing, a 5.9x blend means prospecting carries 7.4x.
The repeat relaxation. If your measured lifetime profit to cost sits at 2.0 or better, the first order does not have to carry the whole target. Your ad budget per sale rises to your 90-day gross profit per customer divided by 2. Modelled retention relaxes nothing, only measured cohort data counts.
It computes everything here from your own inputs: real margin, break-even floor, the ranked levers, your benchmarks, the verdict, and the exact target ROAS and ad budget per sale to set in Meta.
The signals playbook is the other half: the conversions and events to send Google and Meta so the algorithm actually optimizes toward this target instead of guessing. Coming soon.
Yehonatan Tav. I run paid media for ecommerce and consumer brands spending $50,000 to $500,000 a month, as one connected system: the ads, the creative, the funnel, and the measurement. I wrote this because the gap between what the ad account reports and what the business earns is where most of the money is won or lost, and almost nobody looks at it straight.
Every figure in the examples is invented to show the math, not a benchmark or a claim about your business. Run the logic on your own numbers.