I think the term is A-B testing. When a company wants to see what effect a change will have, they don’t force it on everyone at once, just on a certain number of people (A), and then see what happens compared to the rest (B).

https://upload.wikimedia.org/wikipedia/commons/2/2e/A-B_testing_example.png

This is why you’ll always get people saying, “Huh, I haven’t seen that. It’s not doing it for me on [browser].” They’re in the (B) group…for now.

The data the company wants is to know if, do the test people like the change (or are at least willing to tolerate it)? Or do they spend less time on the site? If so, how much? If the results are within their predictions, they’ll expand the testing until everyone is in (A).

There can also be A-B-C-D-etc testing, where some people who get the blocking windows would be able to close it, and some wouldn’t. How many of each ended up disabling their adblock?

This also helps to “boil the frog”, where they can slowly get people used to the idea that this is happening, rather than having a whole wave of surprised outrage at once.