What is diminishing returns in ad spend?
Diminishing returns means each extra euro of ad spend brings less extra revenue than the one before. Judge the next euro, not the average. If it returns less than your break-even ROAS, usually 1 divided by your margin, the extra spend loses money.
By Joris van Huët, Founder & CEOUpdated 7 min read
Run the numbers for your store: the free break-even ROAS calculator.
Diminishing returns in ad spend means each extra euro buys less extra revenue than the one before, usually because the likeliest buyers are reached first. What counts is the next euro, not the average. If it brings back less than your break-even ROAS, it loses money while the average still looks fine.
What one store's data shows
One store's anonymised GA4 export, 1 January 2024 to 21 August 2026. It holds shares of revenue only: no ad spend, no order counts.
| What the export shows | Value | Source cell |
|---|---|---|
| Break-even ROAS at a 40% margin (1 divided by 0.40) | 2.5x | Break-even sheet, 40% margin row |
| Journeys with 1 touch (0.5 days to buy) | 79.5% of revenue | Journeys sheet, 1 touch row |
| Journeys with 4 to 9 touches (16.9 days to buy) | 5.4% of revenue | Journeys sheet, 4-9 touches row |
| Journeys with 10 or more touches (16.0 days to buy) | 3.0% of revenue | Journeys sheet, 10+ touches row |
Start with what the file lacks. With no ad spend in it, the export cannot draw a spend curve for any channel. Anyone who shows you this store's diminishing returns from this file drew the curve themselves.
What it does hold is the bar. On the Break-even sheet, a 40% margin gives a break-even ROAS of 2.5x, because 1 divided by 0.40 is 2.5. The row is arithmetic for one example margin, not a result. At that margin, every extra euro of spend must bring back 2.5 euros of revenue just to pay for itself.
The Journeys sheet shows where revenue sits. Journeys with 1 touch hold 79.5% of revenue on the Journeys sheet and take 0.5 days to buy. Journeys with 10 or more touches hold 3.0% and take 16.0 days, also on the Journeys sheet.
Read down the sheet and the shares fall as touches rise. It looks like a diminishing returns curve, and it is not one. The rows sort journeys by length, not by how much was spent to create them.
What the rows can hint at is where extra spend lands. If more budget mostly adds touches for people already on their way, it pushes them down this sheet. In this one store, journeys of 4 to 9 touches hold 5.4% of revenue on the Journeys sheet. Multi-touch journeys are 3,656 of the 3,670 distinct path sequences on the Journeys sheet, yet hold about a fifth of revenue. Lots of paths, a thin slice to fight over.
What the export cannot show is the thing you want: what the next euro on Meta or Google bought. That takes weekly spend next to weekly sales, or a test that moves spend on purpose.
Why does average ROAS hide diminishing returns?
The ROAS in Ads Manager or Google Ads is an average: the revenue the platform credits, divided by everything you spent. Google's Meridian guide calls ROI a historical, channel-wide average and marginal ROI the return on the next dollar spent. Diminishing returns live in the second number, and dashboards show you the first.
For illustration, take one campaign at two budget levels, with a 40% margin:
| Weekly spend | Revenue the platform credits | Average ROAS |
|---|---|---|
| €5,000 | €20,000 | 4.0x |
| €6,000 | €21,500 | 3.6x |
Say the platform is right: then the extra €1,000 brought €1,500 of revenue, a marginal ROAS of 1.5x. If your margin is 40%, that slice returned €600 of margin for €1,000 of spend. For illustration, the dashboard now shows about 3.6x and nobody panics, while the top €1,000 a week loses €400.
None of this is new. Google's researchers wrote that advertising usually has lag effects and diminishing returns, which plain linear regression struggles to capture. A platform can count the average from its own clicks. The next euro takes a model or a test.
What can a response curve not tell you?
A response curve plots extra revenue against spend, and it is the right picture. It still has blind spots.
It only knows the spend you tried. Meridian's guide says its saturation estimate rests on the observed range of media data, and extrapolation needs caution. If you never spent above a level, the curve above it is a guess.
Not every curve bends from the first euro. Meta's Robyn fits saturation with a Hill function whose shape runs between C and S. An S-shaped channel shows rising returns before falling ones, so a timid test budget can look worse than a real one.
Season moves demand and spend together. If you spend most in your busiest weeks, high spend arrives with high demand. The curve then hands the season's sales to the spend and flatters the top of the budget.
Lag splits the effect across weeks. Spend this week can sell next week. Meridian counts lagged effects from earlier ads inside each period, so a short window can mislead.
Credited revenue is not caused revenue. A curve drawn on a platform's own credited revenue shows how its credit grows, not how your sales do. Draw it on total store sales.
What to do this week
- Write down your break-even ROAS. In Shopify, go to Analytics > Reports, click the Category filter, choose Profit Margin and open Gross profit by product. Divide 1 by your gross margin. Pass: one number that every channel's next euro must beat. Fail: the report is empty because products lack a Cost per item, so add costs first.
- Line up spend and sales by week. In Google Ads, segment the Campaigns table by Week. In Meta Ads Manager, use the Breakdown icon and By time. In Shopify, group Total sales over time by week, and cover about a quarter. Pass: you find weeks at clearly different spend levels. Fail: spend barely moved, so your history cannot show a curve and you need a planned step.
- Ask Google Ads where its curve bends. In the Tools menu, open Performance Planner, select the plus icon, pick your campaigns and select Create. On the Draft plan page, raise spend and watch the forecast. Pass: you can see where extra value per extra euro drops below your bar. Fail: the campaigns are unforecastable, so trust your weekly sheet instead.
Check the homework. Your GA4 Attribution paths export already holds the evidence. Causality Engine reads that one file and shows what each channel caused next to what last-click gave it, in 1 to 2 minutes, for €99 once (excluding VAT), refundable within 30 days. Check the homework
Sources, 1 October 2026: Incremental Outcome, ROI, mROI & Response Curves (Google); Media saturation and lagging (Google); Bayesian Methods for Media Mix Modeling with Carryover and Shape Effects (Google Research); Robyn: Key Features (Meta); Profit reports (Shopify); Use segments in your tables (Google); Navigate to breakdowns in Meta Ads Manager to understand ad performance (Meta); Setting and comparing time ranges for your reports (Shopify); Create and edit a plan with Performance Planner (Google); About cross-channel budgeting (Google)
Related answers
Frequently asked questions
Is diminishing returns the same as ad fatigue?
No, though they often arrive together. Fatigue is the same people tiring of the same ad over time, and fresh creative can fix it. Diminishing returns is extra budget reaching people less likely to buy, and a new ad does not create more likely buyers.Does a falling ROAS always mean diminishing returns?
No. Season, a price change, a tracking change or a learning phase after a big edit can all pull ROAS down at the same spend. Diminishing returns is narrower: the next euro returning less at a higher spend level, with everything else held still.Can GA4 show where my ad spend stops paying?
Sometimes. GA4's cross-channel budgeting has Scenario plans with a response curve that compares ROI at different budget levels. Google says the feature may not be available to your property. Where it is missing, a weekly sheet of spend and total sales does the job.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- AnalyticsAnalytics is the systematic computational analysis of data. It reveals customer behavior and measures campaign performance.
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- DashboardsDashboards are graphical user interfaces that provide at-a-glance views of key performance indicators (KPIs). They monitor campaign performance and visualize attribution insights.
- Google AdsGoogle Ads is an online advertising platform where advertisers bid to display ads, service offerings, and product listings.
- Marketing MixThe marketing mix is the set of actions a company uses to promote its brand or product. It traditionally includes product, price, place, and promotion.
- Marketing Mix ModelingMarketing Mix Modeling (MMM) is a statistical analysis that estimates the impact of marketing and advertising campaigns on sales. It quantifies each channel's contribution to sales.
- Media Mix ModelingMedia Mix Modeling is a statistical technique that measures the collective impact of marketing and advertising on sales. It uses historical data to inform budget allocation.
- Profit MarginProfit margin measures profitability, calculated as net income divided by revenue and expressed as a percentage.