Where does your next ad dollar stop paying?

Upload your daily spend and revenue history. This fits a diminishing-returns curve to your own numbers, shows the marginal return on the next dollar, and tells you the monthly budget where profit peaks.

Currency

1 Your data ?

Daily rows of date, ad spend and revenue. A Meta Ads Manager export (broken down by day) works as-is.

Drop a CSV here or click to choose a file

Needs at least a month of daily history. Nothing leaves your browser.

Paste from a spreadsheet instead

Copy three columns (date, spend, revenue) straight from Sheets or Excel, headers optional.

2 Assumptions

The margin drives where "worth it" ends. The rest is optional but sharpens the read.

Contribution margin ?60%

Known organic daily revenue ?optional, blank = fitted

NZ$

Average order value ?optional, unlocks marginal CAC

NZ$

Client / brand nameshown on the printed report

No data loaded yet

Upload a CSV, paste from a spreadsheet, or hit "Load demo data" to see the tool working.

3 Spend vs revenue curve ?

Blue is revenue, green is ad-driven profit at your margin. The Optimal line sits where the green profit curve peaks, not where revenue flattens.

Daily Weekly average Fitted curve Ad-driven profit Optimal spend Current spend

4 Marginal return ?

What the next dollar returns at each spend level. Below the breakeven line, a marginal dollar costs more than it makes at your margin.

Marginal ROAS Breakeven at your margin Optimal spend Current spend Burning money zone

5 Recommendation

Optimal spend is where marginal ROAS equals breakeven at your contribution margin.

Optimal monthly spend ?

–

Revenue at optimal ?

–

monthly, including baseline

Marginal ROAS now ?

–

return on the next dollar today

On the table ?

–

6 Scenario

Slide a monthly budget and compare it with where you are now and where the curve says to be.

Scenario monthly spend ?–

	Current	Optimal	Scenario

7 Fit quality ?

How much weight this curve deserves before you move real budget.

How this is calculated

Daily rows are averaged into weekly bins, then a saturation curve R(S) = B + a × ln(1 + S/c) is fitted by grid search over c with least squares solving a and B. B is your organic baseline (fitted, or pinned if you enter it). Marginal ROAS is the slope a ÷ (c + S). Optimal daily spend is where marginal ROAS hits breakeven at your contribution margin m, which solves to S* = m × a − c. Monthly figures use 30.4 days.

This is observational response-curve fitting from your own history. It is not a geo-holdout or conversion-lift test, and it assumes your attribution setup stayed consistent across the window. The curve is only drawn to 1.5× your highest observed spend because beyond that it is guesswork. For a definitive read on incrementality, run a proper holdout. We can help with that.

Two things that sharpen the read: (1) if you run more than one paid channel, upload total paid spend across channels against total store revenue (Shopify or GA), not one platform's attributed numbers, so the baseline and the curve reflect the whole business; (2) big promo periods (BFCM, sale weeks) lift revenue for reasons that are not spend, so if a sale dominates your window, expect the curve to flatter spend and read the optimum conservatively.

This curve is fitted from your own history. Want it measured properly?

Something New runs incrementality-led Meta accounts for eCommerce brands: creative, offer and funnel managed weekly against marginal return, not blended ROAS.

Book a strategy call Free ad account audit

Blended ROAS tells you the average of every dollar you have already spent. The only number that should set your budget is the marginal return, what the next dollar brings back. That is what this curve estimates.