Yes, indeed. Now, does GA's sample actually have significant bias? If it does, then showing the practical effects should be easy for experts at a competing company, don't you too think so?

> Now, does GA's sample actually have significant bias?

Yes it does. Both for the adblock https://backlinko.com/ad-blockers-users and the consent banner https://www.advance-metrics.com/en/blog/cookie-behaviour-stu...

I looked at the page page's numbers and arrived at the opposite conclusion.

Take the top graph on the first page: countries. I've worked at two places where I had insight into web access and logs and such. I shouldn't go into too much detail so I'll pick a different pair of neighbour countries: if France and Germany were target markets, the difference in ad blocker usage would not change any decisions. Germany has a higher share ad blockers, and because of that a graph comparing the two countries might be 3% away from reality, but 3% wouldn't affect any decision. 3% difference in flows of money might, but 3% on something that doesn't reflect money? Not a chance.

Sure, if you have a list of countries that spans 10-40%, but choose two entries that are 1% apart... then I guess you wouldn't see the difference. But I'm not sure you're providing a great example here.

Thinking back on the discussions and decisions I remember, they all concerned countries that were similar to each other, and in a sense they were discussed precisely because of that. In theory you might have Indonesia as your home base and pick Ghana as your second market (the most different countries in that table), but in my experience people pick a country near/similar to the one they already know, where they already have some success. So yes, I think France/Germany a great example.

Further, I suspect that because they're similar in many other ways, they're also similar on that graph. It's not just a coincidence.