Richard Golian

1995-born. Charles University alum. Head of Performance at Mixit. 10+ years in marketing and data.

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My blog is full of bots and AI agents

Why nobody can say with certainty how many of their website visitors are human
Richard Golian
Richard Golian · 179 reads
Hi, I am Richard. On this blog, I share thoughts, personal stories, findings and what I am working on. I hope this article brings you some value.

Some time ago I wrote about how I developed my own analytics tool. I built it to respect personal data protection. So much so that it does not even need the visitor's consent. I also wrote about the problems I had to solve during development and how AI helped me along the way.

The first version already had built-in bot detection and flagging of suspicious behaviour (probable bots). It was not enough. Visits, especially direct visits, were strangely high and took an odd share of the total traffic. So I decided to dive back into the topic and improve my own analytics.

Now, after tuning it to a reasonable level, I read with interest posts where someone claims that 20% of the visits on their website are bots and 80% are humans. I have replied to a few of them, on Threads for example, saying that I used to think the same. Today I would say that on your website too, the opposite ratio is closer to the truth.

How did I arrive at this view?

My analytics tool: a switch to hide AI agents and a note that year-over-year data is understated
My analytics tool. A switch to hide AI agents, and a note that the year-over-year comparison is understated for now, while older data still contains bots from before the filter.

What did the first version of my analytics identify as a bot?

The first version stood mainly on two things. The first was simple. I know the list of known robots and I look for their names in the browser header. Googlebot, GPTBot, ClaudeBot, Amazonbot and others. The second was a browser that does not send the page language. That tends to be a quiet sign that there is no human behind the visit.

This catches the obvious ones. But a new group of visits appeared that it does not catch. These are programs that pretend to be a regular browser. There is no bot name in the header. They have the parameters of a human. The original filter does not expose them.

Why scroll no longer proves a human

It occurred to me that I would recognise a human by activity on the page. Scrolling, reading, clicking. There was a time when a robot would not do this.

That no longer holds. These new programs actually run the page. They scroll through the article, click a button, behave almost like a human. Scroll tells me the visit showed some activity. It does not tell me whether a human was behind it.

Bot detection: several signals at once

So I stopped looking for one signal and started combining them. None is enough on its own. But when I put several together, a score emerges. It lets me mark a visit as a probable AI agent even when no single signal gives it away.

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Summary

Bots and AI agents now form the majority of web traffic, not the minority. My first bot detection relied on a list of known robots and a missing browser language. But scrolling and clicking no longer prove a human. So I moved to five groups of visits, including the unverified ones I count on neither side. The 80% human figure that most analytics tools show probably no longer holds.

Common questions on this article's topic

What percentage of internet traffic is bots?
Reports such as the Imperva Bad Bot Report put automated traffic at more than half of global web traffic in 2025. And that is only the detectable share. The real share is probably higher, because some agents can no longer be reliably distinguished from humans.
How can you tell a bot from a human visitor?
One signal is not enough. Modern programs send a normal browser header, scroll and click. It is more reliable to combine several signals into a score that exposes a probable agent even when no single signal gives it away.
Why does scrolling not prove the visitor is human?
Because today's automated browsers actually run the page, scroll through the article and click buttons. Scroll shows activity, not a human.
What are random URL parameters like ?subject= or ?utm_source=?
They are traces of programs that attach their own random code to the address as an internal tag or a test. They can be recognised by the unreadable value, not by the parameter name, so a real campaign never gets excluded.
How accurate is Google Analytics about bots?
Most analytics tools, including Google Analytics, filter only the bots they can detect and count the rest as people. That is why the share of humans they report is overstated. Confirmed humans are often just a few per cent, machines over half, and a large share remains unverified.
Richard Golian

If you have any thoughts, questions, or feedback, feel free to drop me a message at mail@richardgolian.com.

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