How to Run an Ad Unit Exhaustion Analysis (1)

How to Run an Ad Unit Exhaustion Analysis Using AdNgin

Even the best banner ads become less effective the more you see them. An ad that’s fresh and noticeable one day will gradually blend into the background the more often you see it, leading to a phenomenon advertisers refer to as banner blindness, ad exhaustion or ad fatigue.

Just like you feel tired after a long day, your ads can begin to feel exhausted after they’ve been displayed to a specific audience too often.

If you’ve heard the term “ad exhaustion analysis” or “ad fatigue” before, you either spend way too much time on Warrior Forum or you’re an experienced media buyer.

If you’re not any of the above, ad exhaustion analysis is the process of testing ad creatives — the design and text of ads — to learn more about which perform the best not just on the first impression, but over time as users are exposed to them repeatedly over a specific period of time.

ad fatigue analysis

What is ad exhaustion analysis used for?

Usually savvy advertisers with ninja like qualities will perform these tests frequently. However, large publishers are quickly adopting new tactics to increase ad revenue and catapult their ad operations into the innovative front lines of Ad Tech.

With dozens or hundreds of employees and a very comprehensive list of expenses, they’re under a huge amount of pressure to maximize the revenue they earn from direct advertising clients and networks.

For those less than mammoth websites, a period of low eCPMs or reduced CTR results in a slightly lower profit for the month. For a big company, it could spell disaster for investors and employees alike.

But that doesn’t mean that money matters more to them than it does to you. Right?!

So let’s lift back the curtain on their operations. We can usually see that direct ad buys make up the majority (or at least a significant portion) of their ad revenue. As such, optimizing this source is a crucial part of optimizing earnings as a whole.

Optimizing creative exhaustion is one of the best ways to do this. By alerting advertisers to any negative changes in CTR, publishers that depend on CPC-based advertising can increase their earnings, all while helping their advertisers achieve their goals.

It’s a win-win situation: publishers benefit from higher clickthrough rates and a stronger effective CPM, while advertisers get more traffic and better results from their advertising spend.

As an AdSense publisher, you can apply the principles of ad exhaustion analysis to earn more from your traffic and generate a higher RPM from AdSense, even if you don’t have the traffic of a Diply, BuzzFeed, or BBC.

google adsense optimization

How Google AdSense publishers can perform an ad exhaustion analysis using AdNgin

  1. Performing an ad fatigue analysis for specific advertisers
  2. Performing an ad fatigue analysis for ad unit sizes
  3. Performing an ad fatigue analysis for ad placements

If you’re using Google AdSense, it’s easy to write off ad exhaustion analysis. How can you benefit from ad exhaustion testing if you sell ad space on your website through a network? You can’t really ask your advertisers to improve their ad copy when it’s performance is less than stellar now can you?!

Well, the principles laid down by the big publishers can be used very effectively to guide you in your AdSense optimization, even if you can’t control the exact creatives that are shown on your website.

Using AdSense, you can still control which advertisers you let onto your website, which ad sizes you choose to display, and in which placements you choose to show them.

1. Performing an ad fatigue analysis for specific advertisers

With a little bit of digging into your AdSense data, you’ll discover that some of you website’s advertisers earn you a higher RPM than others. By filtering out low-earning advertisers, you can raise your RPM and earn more from your website’s traffic.

To do this, you don’t actually need AdNgin but don’t tell our boss we told you. Just log into your AdSense account and remove any advertisers that don’t perform well using the Advertiser URLs filter in “Allow and block ads.”

2. Performing an ad exhaustion analysis for different ad sizes

Could you earn more from AdSense by replacing your 300×250 ad units with 336×280 units? If you don’t test, you’ll never know. AdNgin lets you test different ad sizes to learn which perform better, helping you optimize your website’s ad units for a higher RPM and more revenue.

Performing an ad exhaustion analysis for different ad sizes is simple.

First, if you don’t already have an AdNgin account, create a free account or ask for a demo to learn more about how AdNgin can help you optimize your website’s AdSense earnings.

If you do have an AdNgin account, connect your AdSense account to the AdNgin optimization platform using our REST API. If you use WordPress, you can install our plugin. If not, you can place the JavaScript snippet from your AdNgin account on your website to get started.

Once you’ve finished installing AdNgin:

start your ad exhaustion analysis by navigating to the Experiments page in our interface.

Click “Add Experiment” to create your new experiment.
Performing an ad exhaustion analysis for different ad sizes

Open the Editor, then drag and drop new AdSense units onto the page to create a new layout.

drag and drop new AdSense units onto the page

Once you’ve dragged the ad units on the page, select the first ad group and click the + icon to add a new ad unit to each group. Make sure you choose a different size for the second ad unit so that you can compare their performance.

add a new ad unit to each group

Now that you’ve created your experiment, it’s time to determine how much traffic you’ll send to your existing page (control) and your experiment. The more traffic you send to each variation, the more reliable your data and insights will be.

You can set the percentage of traffic being sent to your control version through your setting page:

set the percentage of traffic being sent to your control version

Once you’ve sent traffic to each variation, you’ll be able to see which achieves the higher RPM and earns the most revenue. You can monitor your experiment from the AdNgin dashboard to keep track of progress or use Google Analytics custom dimensions to track our experiments’ performance in your GA dashboard.

google analytics adngin ad exhaustion

Using this data, you can optimize your ad sizes to increase your earnings and generate more revenue from your website.

Performing an ad exhaustion analysis for different ad placements

The placement of your AdSense ad units can have a huge effect on your average clickthrough rate, RPM and total earnings. Running an an exhaustion analysis for ad placement is a simple process using, again, AdNgin Experiments.  

Start by following the same process as you would for an ad size analysis. Click the Experiments link in the AdNgin interface, then click “Add Experiment” to create your new experiment.

Performing an ad exhaustion analysis for different ad sizes

Open the Editor, then drag and drop AdSense units onto the page to create a new layout. Now here’s the difference: place each ad group in a different location on the page so that you can test the effects of different ad placements on clickthrough rate and RPM.

test the effects of different ad placements on clickthrough rate and RPM

Decide how much traffic to send to your control and how much to send to your experiment, then wait for your experiment to run its course, which usually takes about two weeks for significant results, depending on the levels of traffic.

Just like before, you can monitor your experiment’s progress and performance from the AdNgin dashboard.

AdNgin Dashboard for Optimizing Google AdSense

Once your experiments are complete

We cannot stress enough just how important it is to run these analyses on your ad units. It does a lot more than just make you look like you’re running with the big dogs. It actually produces results. You can check out our case studies page to see for yourself how other publishers used AdNgin Experiments to perform ad exhaustion analyses that improved their RPMs by up to 217%, as was the case for Trendelier.

You can also combine testing for size and placement as well as other elements into a single variation. But we know that seeing is believing so here’s a screenshot of what an ad exhaustion analysis looks like on a live website:

online arbitrage case study


This experiment ran for, one of the largest buzz content websites worldwide. Happy experimenting 🙂

The complete guide to UX for AdSense publishers

  • Why should AdSense publishers care about UX?
  • ​How to improve UX and increase ad revenue
  • How to improve CTR by using less ads​


I’m Head of Marketing Operations at AdNgin. Before coming to AdNgin, I was a marketing professional focused on SAAS business models. When I’m not working, which is rare, I sail and hang out with my son, Jonathan, and wife, Meital.
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  • But does not Adsense generally serve the best performing Ads for any given page. That is my understanding! (Happy (sort of lol) to be corrected if I am wrong.)

    • Hey David,
      Thanks for commenting. Always happy to respond to your Qs.

      I have an answer but it’s a long one. First, Google is an exchange between supply and demand sides and, like any relationship, it can be difficult to keep both sides satisfied all the time. Google is constantly optimizing every ad impression to find the ad that will produce the best ROI (or whatever goal the advertiser has if any) for the advertiser and the highest CPC/RPM for the publisher. The process takes time and Google can’t maximize performance for everyone all the time (although they do a pretty good job when compared to other exchanges). Second, Google can only optimize within the limits provided by the advertiser (creatives, campaign settings, etc.) and the publisher (ad sizes, placements, type, device, content, channel optimization, etc.) so if you want Google to maximize your revenue you have to first provide them with the optimal conditions and for that you need to constantly be testing and optimizing 🙂

      • Eyal
        Firstly, thanks for taking the time and trouble to put me right. Understand all you say – and you have cleared up a misconception I have had for the last – errr – many years!
        So for me – basically the cut/equation is – time spent optimizing against revenue I can earn long-term by writing. Fortunately I do not have to do much in the way of research for my particular niche on the www, so writing is quite productive!
        (Maybe I am just a little too comfortable!!!)
        Love your posts – the writing, innuendos, and ‘tangent-ing’ but returning to ram home the points. Now feeling guilty about taking up your time – really!
        Thanks again for the input.