Ad blocking is all the rage now, after years of talking about viewability and ad fraud.
However, ad blocking is not just the topic du jour, it is actually closely related to ad fraud and
viewability too. Many people still view these as separate topics and have dealt with them using separate vendors, policies, and practices. But these should be approached holistically and managed that
Fraud bots don’t use ad blocking
Let’s first take a step back and look at the root cause of digital ad fraud -- bots.
Bots are automated browsers that are programmed by cybercriminals to do a specific set of tasks, like hit Webpages to cause ad impressions to load and then click on them.
These activities are
tracked in site analytics and other metrics used to judge the effectiveness of digital advertising, such as clicks and click through rates. But if the visits and the clicks are all fraudulent, then
the analytics are all messed up and any optimization efforts using these corrupted numbers would be wrong.
The fraud bots that deliberately cause ads to load will not use ad
blocking, while human visitors do use ad blocking. Therefore, if there is a large portion of traffic coming from these bots, then the average rate of ad blocking observed will be lower than it should
Put another way, as fewer ad impressions are served to real humans (because they have ad blocking turned on) then a greater proportion of the impressions bought and sold in programmatic ad
exchanges will be coming from bots -- even ones that look and act very much like humans.
Just citing an average rate of ad blocking without also measuring bot activity will be incomplete and
The cash-out sites that fraud bots visit have higher viewability
Fraud bots are also part of a larger ecosystem set up
for digital ad fraud (see:Digital Ad Fraud Ecosystem). This ecosystem includes cash-out sites -- websites whose sole purpose is to carry ads. When impressions and clicks are generated on the site, the
site owner makes ad revenue. The bots mentioned above are used to cause the fraudulent impressions and clicks on these sites.
Since these sites are designed for fraud,
they don’t play by the rules that normal publishers must play by. For example, instead of arraying the ads across the page (some above the fold and others below the fold) these fraud sites can
simply cheat and stack all ads, one above another, all above the fold. In this way, they trick viewability measurement systems so that the entire site appears to have higher than average
Debunk common assumptions and measure bots along with ad blocking and viewability
Knowing the above, it should now be clear
that lower average ad blocking could be a good thing. But if this is due to a large portion of traffic coming from fraud bots, then the lower average rate is deceptive. And a simple, single number for
ad blocking is not enough; it must be measured along with bots to get a more accurate picture.
Also, higher average viewability could be a good thing. But if it is measured in isolation of
measuring for fraud and bots, then it could also be misleading.
A good rule of thumb is that any measurement that is too high or too low should be treated as highly
suspicious. And any rolled-up average number should be treated as incomplete -- fraud hides easily in rolled-up averages.
In the case of ad blocking and viewability, it is crucial to also
measure for bot activity, to understand if the analytics are accurate and reliable. Otherwise, optimizing your media campaigns based on bad data will only make it worse.