![]() Note the “white gap” in the ad network measurement. So if you don’t positively measure for humans, in addition to detecting bots, you’re “missing out,” as it were. But as you can see from the chart above, there could be many other things, other than humans - like not measurable, unknown, etc. Most people assume the other 90% is human. Measuring only for bots might give you a number like 10% IVT. Measuring for humans (dark blue) is important, as it is clearly visible that some ad networks had more humans than others. You Must Measure for Humans, In Addition to Bots / IVT In contrast, publishers were tagged with on-site tags, where the code was installed on pages just like Google Analytics. In other words, ads were tagged and displayed across thousands of sites in those ad networks. The ad networks were measured with an in-ad tag. Note how different the ad networks colors and percentages look, compared to publishers. Without going into any technical details here, have a look at the following chart from 2016 when we did one of the first industry wide studies. You can’t do anything with just a percentage IVT number as many site owners have told me.Īnother shortcoming of existing IVT detection vendors is that they don’t differentiate between on-site measurement (code on the page) versus in-ad measurement (code in the foreign ad iframe). Those are useless because they are not actionable. Other current fraud verification tech platforms only measure for IVT and give you a number. Note that we measure for humans (dark blue) in addition to measuring for bots. Dozens and dozens more look similar to this. The example above is just one good, mainstream publisher. Fraud bots will load pages on long tail sites that pay them for traffic. This is because they have large human audiences, they don’t buy traffic, and fraud bots won’t waste their time causing pages to load on these sites because they don't get paid. Good publishers don’t have rampant amounts of bots on their sites. ![]() What’s A Good Bot Benchmark? Zero, If Possible But if your paid campaigns deliver users to your site that bounce less, stay longer, and look at more pages, compared to your own organic benchmarks, then add budget to those campaigns so you will get more of the right kind of user to your site. Do your paid marketing campaigns over-index, match, or under-index these benchmarks? If the paid marketing campaigns cannot deliver users that are at least comparable or better than your own organic traffic, then it may be wise to spend less on those campaigns. So the characteristics of time on site, bounce rate, and pages per session would serve as good benchmarks for what real, human visitors look like and do on your site. Users who searched for something on Google and then clicked through on an organic search result probably wanted to be there. I recommend you use those characteristics as the benchmarks for judging the efficacy of your paid digital marketing campaigns. Instead of comparing your analytics to industry wide benchmarks, look at their own organic traffic. Any comparisons would be apples to oranges. And this is why industry wide benchmarks are meaningless and not applicable to your specific situation. The benchmarks for a medical journal site are entirely different from those of a travel booking site. The user was doing research and trying to book a hotel so they looked at dozens of pages. Their time on site might be much higher, and the number of pages also much higher. For a travel booking site, the user may do a search for hotels and then click to check out a few of the search results. The number of pages for that session may be one page and the time on site relatively low, because they found their answer and left. ![]() For example, for a medical journal site, doctors come to read one article to get answers they need at that moment and then they leave. A “good” bounce rate, time on site, and number of pages per session is entirely different depending on the nature of the site or the industry vertical to which it belongs. Let’s take simple things like bounce rates, time on site, and number of pages per session all of these are readily available in Google Analytics. ![]()
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