Understanding a point of diminishing returns in marketing

Imagine a marathon runner moving through a 26.2-mile course. Conventional wisdom suggests their energy will steadily diminish over time—starting strong, maintaining a decent pace through the middle miles, and then gradually slowing as fatigue sets in during the final stretch. This is the classic diminishing returns curve we all expect to see, potentially with a clear point of diminishing returns as their energy flags.

But any experienced runner knows the reality is far more nuanced. Runners often get a “second wind” several miles in. The enthusiastic crowd at mile 20 might temporarily boost their pace. A fellow competitor might spark a competitive surge. Marketing campaigns work in surprisingly similar ways. While the concept of diminishing returns is fundamentally sound, the real-world application is far more complex. For marketers, that may mean you’re missing out on ROI by expecting the smooth curves of textbooks instead of the twists of reality.

The basic concept of diminishing returns in marketing

The idea of diminishing returns comes from economics. This principle states that after a certain point, adding more of one input while keeping other production factors constant yields progressively smaller increases in output. (You’ll see this called both diminishing returns and diminishing marginal returns.) In marketing terms, this translates to: the more you spend on a campaign, the less additional revenue each new dollar generates past a certain point.

The traditional diminishing returns curve in marketing looks something like this:

• Initial spending generates substantial returns as you reach the most receptive audiences
• Mid-level spending continues to drive growth, but at a decreasing rate because you’ve already hit the point of diminishing returns
• High-level spending yields minimal additional returns as the most convertible audiences have already been reached

This concept forms the foundation of marketing efficiency metrics like ROAS (Return on Ad Spend) and helps marketers determine optimal budget allocation. Intuitively, it makes sense—you can’t keep increasing your marketing budget infinitely and expect the same level of returns. Well, except it’s a lot more nuanced than that, and the law of diminishing returns doesn’t translate perfectly to marketing.

Why marketers are already familiar with this concept

If you’ve worked in marketing for any length of time, you’ve encountered diminishing returns, whether or not you used that specific term. You’ve likely:

• Noticed how your best-performing campaign started delivering less impressive results as you increased spend
• Observed click-through rates decline as ad frequency increases
• Seen conversion rates drop when scaling audience targeting beyond your core demographics
• Watched CPAs (Cost Per Acquisition) rise as you push campaigns beyond optimal spending levels

Platform dashboards often visualize this effect through saturation curves or efficiency metrics. We use saturation curves in our dashboard, too. Budget allocation discussions inevitably circle around the question: “At what point does additional spend on this campaign become inefficient?”

This intuitive understanding influences many marketing decisions, from setting campaign budgets to determining when to launch new creative or target different audiences.

The oversimplification problem

While the basic concept is valid, most discussions about the point of diminishing returns in marketing oversimplify the reality. Here’s why that’s problematic:

Traditional models typically assume:

• A single campaign operating in isolation
• (Which also means no top of funnel campaigns bringing in more ideal customers)
• A static marketplace with no competitive shifts
• Linear consumer behavior with predictable responses
• A smooth, continuous curve with one clear peak efficiency point

None of these assumptions hold true in today’s complex marketing landscape. Modern marketing environments are dynamic ecosystems. Multiple campaigns interact across channels, consumer behavior evolves constantly, and external factors regularly disrupt expected patterns.

It’s easy to see how diminishing marginal productivity is a thing in factory production. Within your factory, you control all the inputs, the entire production process. There’s no consumer psychology involved in optimizing how much product your factory can create. Your factory is also an isolated ecosystem. But none of those things hold for paid media campaigns.

The reality of campaign performance

One of the most overlooked aspects of campaign performance is that diminishing returns curves aren’t always smooth with a single efficiency peak after which are diminishing marginal returns. In reality, campaigns can have multiple points of peak efficiency.

Consider these scenarios:

• Audience Threshold Effects: A campaign might perform well with a small budget reaching core fans, then experience declining returns as you expand beyond this audience. However, once you reach sufficient scale to target a new valuable segment, performance might improve again before eventually declining.
• Creative Fatigue and Revival: Campaigns often see initial strong performance, followed by diminishing returns as audience fatigue sets in. However, refreshing creative or making seasonal adjustments can create a second performance peak, essentially resetting the diminishing returns curve.
• Budget Scale Thresholds: Some platforms and campaign types have efficiency thresholds where performance improves once you cross certain spending levels. This creates a “stair-step” pattern rather than a smooth curve, with multiple points of optimized efficiency.

These multiple efficiency peaks mean that what appears to be a point of diminishing returns might actually be a temporary valley before another performance peak. Marketers who understand this complexity can avoid prematurely reducing spend on campaigns that could reach new efficiency peaks with continued investment.

The multi-campaign reality

Modern brands rarely run just one campaign. They typically operate:

• Multiple campaigns within the same channel
• Campaigns across different channels and platforms
• A mix of upper and lower funnel marketing tactics
• Various creative approaches simultaneously

Each campaign has its own diminishing returns curve, and these curves interact with each other in complex ways. For example:

• A seemingly saturated prospecting campaign might still be driving essential new users into your retargeting funnel
• A Meta campaign with apparently diminishing returns might be increasing the efficiency of your branded search through halo effects
• Two campaigns might appear to be hitting diminishing returns individually, but together they reach audiences that neither could efficiently target alone

This multi-campaign reality means that examining the diminishing returns of any single campaign in isolation provides an incomplete picture. The true measure of efficiency must account for how campaigns work together within your overall marketing ecosystem.

Cross-channel consumer journeys

Today’s consumer rarely experiences a brand through just one marketing channel. They might:

• See a YouTube ad that creates awareness
• Encounter a display retargeting ad that maintains interest
• Click on a paid search ad when ready to purchase
• Convert after receiving an email promotion

In this environment, evaluating diminishing marginal returns on a channel-by-channel basis misses the bigger picture of how channels interact to guide the customer journey. A Facebook campaign might appear to hit diminishing returns when measured in isolation, but it could be significantly improving the performance of your Google Ads campaigns by creating awareness and consideration.

Cross-device behavior further complicates measurement. A consumer might view your ad on mobile, research your product on a tablet, and complete the purchase on a desktop. Traditional single-channel diminishing returns analysis would fail to capture this complex journey.

Campaign interactions and halo effects

When multiple marketing campaigns run simultaneously, they create complex interactions that influence overall performance. These interactions include:

• Halo Effects: When one campaign creates benefits that spill over to other marketing efforts. For example, a TV campaign might boost the performance of your paid search ads by increasing brand awareness and search volume.
• Synergistic Effects: When two campaigns work better together than either would alone. For example, a combination of prospecting and retargeting campaigns might create a funnel that’s more efficient than the sum of its parts.
• Competitive Effects: When campaigns compete for the same audience or inventory, potentially creating internal competition that reduces overall efficiency.

These interactions mean that the diminishing returns curve for any individual campaign is constantly being reshaped by the performance of other marketing activities. A campaign that appears to be approaching the point of diminishing returns might actually be enabling other campaigns to perform better.

At Prescient AI, our modeling captures these halo effects, measuring how campaigns impact not just direct conversions but also organic traffic, branded search, and direct traffic—providing a more complete picture of true marketing impact.

How external factors reshape diminishing returns

Just as a marathon runner’s performance can be influenced by weather, crowd support, or competitors, your marketing campaign’s diminishing returns curve can be dramatically reshaped by external factors:

• Competitive Shifts: If your main competitor suddenly pauses their campaign or exits your market, your campaign’s efficiency might unexpectedly improve.
• Viral Moments: If your product suddenly becomes popular on TikTok or another social platform, your paid campaigns might experience improved performance as they benefit from increased organic interest and relevance.
• Seasonal Changes: Consumer behavior changes throughout the year can cause fluctuations in your campaign’s performance curve, creating temporary efficiency improvements during high-demand periods.
• Market Disruptions: Economic shifts, industry news, or regulatory changes can alter how consumers respond to your marketing, potentially improving efficiency where you previously saw diminishing returns.
• Algorithm Updates: Platform algorithm changes can suddenly make previously inefficient spend levels perform better (or worse).

These external factors mean that what appears to be a point of diminishing returns today might not be one tomorrow. The dynamic nature of marketing environments requires ongoing evaluation rather than one-time optimization decisions based on static models.

Clarifying diminishing returns vs. saturation

Marketers often use the terms “diminishing returns” and “saturation” interchangeably, but they represent different (though related) concepts:

• Diminishing Returns refers to the economic principle where additional investment yields progressively smaller benefits. This is a gradual process—returns don’t disappear, they simply decrease incrementally.
• Saturation represents a point where a market or audience has been so thoroughly exposed to your marketing that additional exposure produces negligible results. Saturation is effectively the end stage of diminishing returns.

The key difference: Diminishing returns is the journey, the point of diminishing returns is the inflection point, and saturation is the destination. A campaign experiencing diminishing marginal returns still generates value (just less efficiently), while a truly saturated campaign generates minimal additional value.

It’s also worth noting that true saturation is rare in digital marketing—what often appears to be saturation may simply be a temporary efficiency decline before another peak, or the result of failing to refresh creative or targeting strategies.

Better approaches to understanding marketing efficiency

Given the complexity of diminishing marginal returns in modern marketing, how can marketers make better decisions? Here are some approaches:

• Holistic Measurement: Look beyond individual campaign metrics to understand cross-campaign and cross-channel effects. Advanced Marketing Mix Modeling (MMM) approaches, like those offered by Prescient AI, can capture these complex interactions.
• Dynamic Optimization: Rather than making one-time decisions based on static diminishing returns curves, continuously evaluate and adjust campaigns based on real-time performance data and changing market conditions.
• Longer Measurement Windows: Extend your analysis timeframe to capture delayed impacts and halo effects that might not appear in short-term performance data.

The goal isn’t to ignore these effects and charge past the point of diminishing returns—it’s to understand them in the context of your overall marketing ecosystem rather than in isolation.

Practical applications for marketers

How can you apply these insights to your marketing strategy? Here at Prescient AI, we like these practical approaches:

Before reducing spend on a campaign with apparent diminishing marginal productivity:

• Check whether it’s driving performance improvements in other campaigns
• Consider if it’s building an audience for future remarketing
• Evaluate if it’s contributing to organic traffic or branded search growth
• Assess whether performance fluctuations might be temporary

To test for multiple efficiency peaks:

• Gradually scale spending beyond the apparent point of diminishing returns for limited test periods
• Monitor for performance improvements after pushing through efficiency plateaus
• Test different creative approaches before concluding a campaign is truly saturated

To account for external factors:

• Regularly reassess campaigns that previously hit diminishing returns to see if market conditions have changed
• Develop contingency plans for rapidly scaling spend when competitive or seasonal factors create favorable conditions

Wrapping it up…

The most sophisticated marketers understand that diminishing returns exist but recognize them as one factor in a complex system rather than a simple rule to follow. They look beyond individual campaign metrics to understand how their marketing activities work together as an ecosystem. Adopting this more nuanced view of diminishing marginal returns can help marketers avoid premature optimization decisions, identify hidden opportunities for growth, and ultimately build more resilient and effective marketing strategies.