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Ad Fatigue in a Digital Analyst’s Perspective: Audiences Are NOT the Ones Exhausted


Community Advisor


Ad fatigue—your audiences got tired with your ads. This is the simplified definition. But after observing ads for the past half a decade, I realised it is NOT the audiences that got exhausted, but the ad serving machine.

Below example is an ad with media buying objective optimised for CPC.

Ad fatigue.png

 In the above chart, here is the outline of events:


Ads Serving Machine: Reaching Audiences

Audiences: Engaging with the Ads


The machine is trying to reach as many audiences as possible especially during the learning phase (first seven days).

Clicks ‘reward’ the machine, as seen on increasing Clickthrough rate (CTR)


The machine experiences ‘fatigue’ in reaching new audiences from Day 8.

Audiences reached from Day 1-7 are the same audiences within the estimated pool of audiences, the proportion of clicks from impressions dropped from Day 8.


The machine maintained the daily Reach between Day 8-9.

CTR did not stay at the same level as Day 5-7, note that this campaign’s KPI is 0.80% CTR. But the CTR dropped and plateaued on second week of the campaign.


The machine exhausted the reach from week 2, hence, it further decreases from week 3.

Lower CTR does not ‘reward’ the machine enough. Note that the audiences reached by the ads on weeks 2 and 3 are the same people reached by the ads on week 1.

Why Reach?

You may wonder why I used Reach as an example in this discussion, it is more actionable than Impressions. Moreover, as an analyst, I believe we need to focus on metrics that ads value and depth to our insights, rather than vanity metrics.

Reach is tricky, that’s why in the above example, the maximum Reach for this campaign is 90k or 60% of its estimated audience size. It depends on which platform but a 30% of estimated audience reached is optimal. I recommend that you set a benchmark data for reach % for each of your ad platform too. This way, you’ll understand whether your ads are reaching enough users, not just ‘impressing’ users.

How does this ad serving machine fatigue affect your website analytics?

Here are ways to investigate the effect of this machine fatigue to your website:

  1. In the freeform table, use the Last Touch Channel Dimension
  2. Add the Week dimension per channel
  3. Right click on the data, then Visualise each to see the downtrend

Fatigue x Website analytics.png

Above are the typical impact to your website analytics once the ad serving machine reaches fatigue.

Which Top 4 Website Metrics Decline with Ad Serving Machine Fatigue?

  • Total Entries
  • First time Entries
  • File Download Rate
  • Average time on site

Bounce rate may be affected too since the lesser the traffic, the bounce rate is lower, but not always. And sometimes, page views per visit is affected as well though less obvious, this is especially noticeable if your landing page is an educational site where content is expected to be sticky for users to stay and continue consuming, or a navigational page for more publications. 

Got a question? Drop in the comments, and let’s talk!

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