Diminishing returns in advertising mean ROAS goes down as spend goes up, almost every time. This happens because ad platforms serve the best leads first, so scaling spend eventually reaches less qualified audiences or repeats ads more often. Without mapping each channel’s saturation curve, brands assume one scales like another and overspend past the payoff point. This video explains why performance curves differ by channel, platform, and outcome.
Why Diminishing Returns in Advertising Make ROAS Fall as Spend Rises
Diminishing returns in advertising make ROAS fall as spend rises, because there’s no version of scaling that avoids it: the answer to whether ROAS goes up, stays flat, or falls is almost always that it falls. In this video, John Wallace, CEO of LiftLab, explains that tripling spend does not translate into tripling revenue, no matter how convenient that would be. Marketers already feel this as plateau, fatigue, or saturation; economists just call it diminishing returns.
Wallace reframes why this happens in terms of what ad platforms are actually doing on a brand’s behalf: serving the best-matched leads first, using everything they know about an audience. The catch is they’ll never tell you when those best leads run out, at which point they either start serving less qualified audiences or increase ad frequency to the same people. Detecting that shift requires knowing the specific shape of your own performance curve, which varies by channel (TikTok looks different from Meta), and by outcome (website sales behave differently than in-store, wholesale, or marketplace sales). Wallace describes mapping these curves, down to the channel, tactic, and campaign level, as LiftLab’s core mission.
In this video, you’ll learn:
Why increasing your advertising budget often leads to a decrease in ROAS
The distinction between infinite scaling and the reality of platform saturation
How advertising partners prioritize lead quality and when they shift to less efficient strategies
The importance of identifying unique performance curves for different brands, audiences, and channels
Why outcomes vary across different marketing objectives and sales platforms
TIME STAMPFull Video Transcript: Diminishing Returns in Advertising Explained
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In this video, John Wallace explains why ROAS declines as ad spend scales, and why every channel’s saturation curve looks different.
[0:00 – 0:17] The Impact of Increased Spend on ROAS
What happens to the ROAS, does it go up, does it stay the same, and does it go down? I know there are always some smart folks that say it depends, but no, if you have to pick, like on a standardized test, the best answer here, and the answer that we get 90% of the time, and it’s the right answer, this is not a trick question: the ROAS will go down.
[0:18 – 0:36] Marketing Dynamics and Diminishing Returns
Set another way, you know it would really be convenient if we could triple our spend and automatically triple our revenue, but unfortunately it doesn’t work that way. In marketing, we call these things like plateau or fatigue or often saturation. In economics, it’s just called diminishing returns, and it’s something that we feel as marketers, we know it’s happening.
[0:37 – 0:49] The Reality of Ad Platform Scaling
If this answer C were not true, it would imply something like this, that that ad platform just scales infinitely, right? That it will just go up and to the right forever, and we know that that’s not the case.
[0:49 – 1:18] Managing Advertising Partnerships
I would actually posit that you don’t want that. What you want is these partners over here to use all the data they have about their audiences, to use all the algorithms and engineering that they have, to give you the best leads first, and they’re doing that on your behalf. They’re your partners. What they’re not going to tell you is when they run out of those leads, and when they do, they’re either going to serve ads to less qualified leads, or they’re going to keep serving ads and jack up the frequency on the best leads.
[1:18 – 2:15] Deciphering Performance Curves
That’s something that you need to be able to detect. The way that you do this here is to know for your brand and your targeting and your audience and your price point, when you spend on these different channels, what’s the shape of this curve? It’s going to be different for your TikTok spend than it will be for your Meta spend. And then these curves are also different depending on the outcome that you’re looking at. You’ll have a different shape of this curve, or different saturation, or different diminishing returns, when you’re looking at your website sales versus the shape of that curve when you’re spending on, say, Pinterest. What’s the shape of that curve for driving sales in your stores, or in the wholesale channel, or in marketplaces like Amazon? So that’s really the North Star at LiftLab: it’s helping brands to understand what the shape of these curves is, up and down across the media plan, different ad partners for different outcomes, at the channel level, like these channels, like, you know, call it Facebook prospecting, at the tactic level, and all the way down to the campaign level.
Key Lessons: Mapping Diminishing Returns Across Channels and Outcomes
Marketing reality: Scaling ad spend is subject to the economic principle of diminishing returns rather than infinite, linear growth.
Platform behavior: Ad partners prioritize top-tier leads first, but will shift to lower-quality audiences or increase ad frequency once prime leads are exhausted.
Channel dynamics: Every marketing channel and tactic follows a unique performance curve that requires distinct analysis to optimize.
Data-driven strategy: Brands must accurately detect saturation points to avoid wasted spend and maintain effective campaign performance.
Outcome variability: Performance metrics change based on the specific goal, whether it is website sales, in-store purchases, or marketplace engagement.
