11% of My Search Console Impressions Are Competitor-Monitoring Bots

I was looking at Search Console last week, trying to work out whether any of my blog posts had started ranking, and one page looked like good news. /blog/social-listening-tool-for-founders, 69 impressions, average position 7.1. Page one. For a site that mostly sits on page five, that's the kind of number you screenshot.

It should have bothered me sooner that it was such an outlier. The pages either side of it in the report look like this:

One page at position 7 in a neighbourhood of 50 to 80. Either I'd written something unusually good, or something was wrong with the number.

So I filtered to that page and read the actual queries. They look like this:

"awario" -site:reddit.com -site:twitter.com -site:x.com -site:wykop.pl
-site:tripadvisor.com -site:youtube.com -site:yelp.com -site:booking.com
-site:facebook.com -site:instagram.com -site:tiktok.com

Nobody types that. That's a machine. And 56 of that page's 69 impressions, 81% of them, come from queries shaped like it.

What the numbers look like

I run CueScout, which scans Reddit for threads with buying intent, so I write a fair amount about social listening tools. That means my pages mention brand names like awario, brand24, talkwalker. Which, it turns out, is enough to get me swept up in whatever those companies (or their customers) are running against Google all day.

Over the three-month window in Search Console, the whole site got 777 impressions and 6 clicks. Filtering to queries that contain -site::

87 of 777 is 11.2%. Zero clicks across all 87, which is what you'd expect from something that's parsing the results page rather than reading it.

The position column is the part that actually matters. These queries resolve at an average position of 6.9 while everything else I have averages 53. They are, by a distance, my best-ranking "traffic", and they represent nobody. Every one of them pulls the site-wide average position toward a number that looks like progress.

That's how a page ends up reporting position 7.1 without a single human having seen it.

There are at least two of them

Fifteen distinct queries had -site: in them. Reading through, they split cleanly into two groups by their exclusion list.

The first group always ends with the same eleven domains, in the same order, including wykop.pl (a Polish link-sharing site) and the review triple of tripadvisor.com, yelp.com, booking.com:

"octolens" -site:reddit.com -site:twitter.com -site:x.com -site:wykop.pl
-site:tripadvisor.com -site:youtube.com -site:yelp.com -site:booking.com
-site:facebook.com -site:instagram.com -site:tiktok.com

The second group uses a different set, notably fb.me, youtu.be, vm.tiktok.com and t.co, which is a list built by someone thinking about URL shorteners rather than review sites:

-site:facebook.com -site:fb.me -site:youtube.com -site:youtu.be
-site:youtube.be -site:twitter.com -site:instagram.com -site:tiktok.com
-site:vm.tiktok.com -site:t.co -site:x.com -site:reddit.com "sprinklr"

An exclusion list is a fingerprint. You build it once, you bolt it onto every query the product runs, and it never varies. Two lists means two products.

The one that convinced me these are tool-generated rather than a diligent human is this:

"brand24" -"24-7" -"24/365" -"24/7" -"brand 24 apparel" -"brand 24-hour"
-site:reddit.com -site:twitter.com -site:x.com -site:wykop.pl ...

Someone sat down and worked out that tracking the brand "Brand24" pulls in noise about 24/7 support hours and a clothing company called Brand 24 Apparel, and wrote negative keywords for each. That's a configuration screen, not a search box.

The full list of brands being tracked across both fingerprints: octolens, awario, awario.com, brand24, talkwalker, talkwalker alerts, sprinklr, consensus ai, plus the bare category terms "social listening tools" and ("reddit monitor" or "reddit monitoring") and ("tool" or "software" or "app" or "tools" or "platform").

So: social listening tools, monitoring social listening tools. My pages are collateral because I happen to write about the category.

What I'd actually do about it

Nothing, to the bots. They're reading public search results and I have no lever there, and honestly I'd be doing something similar if I needed that data.

The thing to fix is your own reporting. In the Performance report, Add filter, Query, "Queries containing", type -site:. That shows you the noise. Flip it to "Queries not containing" and you get something closer to your real numbers.

For me the difference is not subtle. Average position 53 is the honest read of where this site stands. Anything better than that is bots flattering me. And "new query appearing under position 20" is a signal I'd been using to decide what to write next, which means for a few weeks I was letting scrapers pick my content calendar.

If you write about any named product category, check yours. I'd genuinely like to know whether 11% is normal, high, or embarrassingly low.

What this doesn't show

It's one small site. 777 impressions over three months is not a lot of data, and if you have real traffic your percentage will almost certainly be lower, because this is a roughly fixed volume of robot queries divided by a much bigger denominator. The absolute number of bot impressions is probably the more comparable figure than the ratio.

I can't prove which vendor is behind either fingerprint. The wykop.pl exclusion in the first group is suggestive, since it's an odd domain to care about unless you're Polish or serving Polish customers, and at least one company in that brand list is Polish. That's an inference from a domain list, not evidence, and I'm not going to name a culprit on that basis. The honest claim is narrower: two different automated systems, both tracking the same competitive set.

Search Console also warns that "chart totals and table results might be partial when filters are applied," so treat the 87 as approximately right rather than exact. And filtering on -site: only catches this one shape of machine query. Anything scraping Google without operators looks identical to a person in my data, so treat 11% as the low end of the range.