The formal concept of diminishing returns first surfaced in the works of prolific 17th and 18th-century economists. However, diminishing returns are somewhat of a component of our human experience - you could even call it a law of nature.
If you’ve ever put so much effort into something just to see the returns hit a brick wall and dwindle away, you’ve experienced diminishing returns! The longer you do something and the more input you put in, the more likely you will reach a point where your effort has less impact.
Below is the classic curve used to illustrate diminishing returns.
The steepest part of the curve denotes rapidly increasing returns, then reaching the point of diminishing returns (blue dotted line). At the peak of the curve, the point of maximum yield is obtained, also called the saturation point. After that, the curve descends into negative returns. Negative returns won’t always follow diminishing returns - the curve may simply flatten out and plateau over a long period of time.
Fundamentally speaking, diminishing returns are defined as increasing inputs resulting in marginal product decreases after obtaining a certain optimum threshold. Increasing input will increase returns until a certain point, where the response curve begins to flatten out and decrease.
Diminishing returns describe what happens when input or investment returns a diminishing outcome relative to that input, thus rendering additional input low impact or eventually worthless.
It's perhaps unsurprising that this term is used in advertising, marketing, data science, machine learning, etc. In all of these cases, doubling efforts will not always double returns, and pushing input to excess is likely inefficient once a certain output level is obtained.
What are the three stages of diminishing returns?
Diminishing returns usually feature three stages or phases. They are:
- Increasing returns, when output rises equal to, or above input.
- Diminishing returns, when output begins to diminish relative to input.
- Negative returns, when output decreases below input.
Four examples of diminishing returns
Take a factory employing new workers to operate machines and create more products. So long as there are enough machines for additional employees to operate, adding another employee to increase the workforce from one to two people doubles the output.
Suppose you’ve got 50 employees; adding another will increase output by just 2%. The output will continually diminish relative to the input until the yields are the maximum possible for the number of employees. Once you’ve employed enough workers to operate all machines effectively, the point of maximum yield is obtained.
After that, adding further employees may decrease output as those employees begin to bump into each other and disrupt each other’s work. At this point, the diminishing returns of employing new workers transition into negative returns.
In the above factory, each worker may produce 100 units per hour for approximately 40 hours. However, in the 41st hour, the worker's output may drop to 90 units per hour as they become tired and overworked. At this point, returns are diminishing per unit of input.
Another real-life example is an engine. As an engine heats up, it burns fuel more efficiently, which causes rapidly increasing returns and exponential growth in performance.
However, once the engine begins to heat, approaching maximum performance yield, it requires more fuel, which costs more. Eventually, the engine is so hot that performance begins to decrease. It’d probably be best to let off the accelerator and obtain a sweet spot of performance returns relative to investment.
Diminishing returns are described in physical education and sports science. Fitness increases rapidly in the first stages of training, but then peter out as the body approaches its peak physical fitness. Eventually, fitness returns on physical exercise begin to diminish. If you keep pushing the body beyond this point of maximum yield, returns might eventually diminish as pain, inflammation, and other ailments affect the body’s physical condition.
Diminishing returns in marketing
Practically any marketing campaign can (and likely will) exhibit diminishing returns at some point. Unless you have unlimited cash, identifying the point where your marketing spend exhibits diminishing returns enables you to fine-tune campaigns to obtain optimum marketing ROI.
Would you rather spend $1,000 for an ROI of 5 or $10,000 for an ROI of 6? With those figures, at some point between spending $1,000 and $10,000, the revenue return for every dollar spent on marketing has diminished rapidly. By gaining visibility over your marketing response curve, you can optimize campaigns to navigate diminishing returns.
In other words, each dollar has less and less impact past a certain threshold. Of course, if profit margins are still healthy, it might be wise to push past diminishing returns until maximum yield is achieved, but this is rarely an option. There might be situations where it’s beneficial to sell more products even when marketing returns are diminishing, e.g., to keep competitors out of a space, or to circulate new products for reviews and social proof.
Calculating diminishing returns in marketing
Calculating diminishing returns can be simple, in the case of a smaller eCommerce retailer or Amazon or Etsy seller who is advertising a handful of products, or a small SaaS provider with a single subscription product.
In this situation, the goal is to find your break-even CPA or RoAS, and push your marketing spend until your CPA begins to jump up without significant impact on conversions. For RoAS, your return will plateau, and if it falls back towards your breakeven point, your campaign is experiencing diminishing returns.
Diminishing returns in CPA
It’s perhaps more conventional to locate diminishing returns using CPA. For example, increasing your Facebook ad spend from $500 to $1,000 might expect to double your conversions. However, in reality, your returns will probably diminish, and you’ll see a lower return on your conversions past a certain threshold.
Here’s an example: a company increased ad spend from $500 per day to around $4,000, which saw their CPA rise around 80% from approximately $2.50 to $4.50. The company will likely see its CPA rise by around $1 for every $1,163 they spend.
By creating a marketing response curve or non-linear media mix model (MMM), (aka. marketing mix model), it should be relatively simple to view how a curve plotting conversions/revenue vs. spend flattens out with ever-increasing input.
This is typical in well-optimized campaigns that target optimal placements in the least competitive areas first, thus exhibiting exponential growth in conversions with increased spending, until eventually, the campaign expands into increasingly competitive territory. At this point, returns tend to diminish.
Diminishing returns in RoAS
Here's a more retail-focused example. If we apply diminishing returns to selling on Amazon, for example, we can use RoAS. Firstly, it’s necessary to calculate RoAS together with your COGs and break-even point to find your minimum RoAS.
- Product sale price: $20
- COGs including fees: $10
$20 - $10 = $10 profit, which is a 50% profit margin (profit margin = profit/revenue). If you make your $10 COGs, you break even.
Now you have your margin, your minimum RoAS is the most you can spend on advertising while profiting from the campaign.
Product sale price/break-even point = minimum RoAS
So, for the above example, $20/$10 = $1 minimum RoAS. Your return on advertising spend must be $1 minimum.
With a minimum RoAS of $1, you’ll need to compare the actual RoAS figure to the minimum RoAS to gauge the profitability of an advertising campaign. In this case:
- A RoAS exceeding $1 indicates that your ad campaign is profitable after COGs. If you spend $10 on ads to make $10, you break even. So, if you make more than one dollar on the dollar, you profit.
- A RoAS below $1 means that your ad campaign is not profitable. You’ll make a loss on your ad spend.
- A RoAS of precisely $1 means you’re breaking even from your ad spend.
Now, suppose you optimize your ad spend and strategy, re-allocating budget, tweaking keywords, etc, and you find that pushing your ad spend is resulting in a higher RoAS. Your RoAS might be $5, meaning for every $1 you spend on advertising, you make $5. Your products only cost 20% of their final sale price - this is a good situation to be in.
At this point, spending $1,000 results in $5,000 returns. You decide to up your investment to $1,500 and notice you’re now only returning $5,500. Then, you increase your investment to $2,000 and you’re still only returning $5,600.
At this point, your returns are diminishing rapidly. It may be that $5,600 or thereabouts is your maximum yield from that particular marketing mix. If you input more money, you might make a little more, but each dollar has a minimal impact. Observe your RoAS and analyze when it begins to fall in relation to spend, adjusting for other factors as best you can.
The Efficient Frontier
Another econometric term, the efficient frontier, is defined as a portfolio that offers the highest returns for a given level of risk. Conversely, delivering below the efficient frontier means the portfolio (in this case, a marketing mix) is failing to work hard enough for the specified level of risk.
The efficient frontier applies to a diminishing returns response curve, in that marketers can use such a graph above to indicate that spending around $1,600 per day will likely not yield more conversion than a lower overall spend. There is a cost:benefit trade-off at play - creating a graph that illustrates diminishing returns helps marketers negotiate their spending for maximum efficiency.
Of course, creating a model like this involves generalizing future results on past data, so it won’t take short-term changes into account.
For example, new competitors entering the market, significant changes to marketing channels and strategies, and many other internal and external changes will impact return on ad spend. Non-linear marketing models can build in factors such as seasonality, but it’s pretty much impossible to predict every factor that influences a marketing campaign.
Summary: Diminishing returns
In its simplest form, the econometric law of diminishing returns cites that as investment in a particular area increases, the rate of return from that investment, after a certain point, can’t continue to increase, assuming other variables remain constant.
In marketing and marketing, diminishing returns is used to describe how conversions/revenue eventually begin to flatten in relation to marketing spend.
In other words, conversions/revenue/CTR/other target measurements become increasingly less responsive to marketing input and spend. Each dollar spent has less and less impact.
It might still be sensible or shrewd to push ahead with increased spend even when returns start to diminish, e.g. to clear stock, keep competitors out of a market, obtain more reviews or circulate more products for social proof. H
However, locating sweet spots in the efficient frontier will help you optimize your marketing mix and keep CPA at an acceptable level.