Thanks for the addition. Well when I refer to the "old Google" I am not sure where to draw the line, it may have started earlier than the recent G+ integration anyway. It has more to do with my perception of an "old Google" organization which used to be open to user feedback rather than the more recent one, blatantly pushing changes with seemingly no passion about their established user base opinion.

I may be wrong. To confirm whether things changed or not, we'd need to get Google insiders to speak out on that subject.

My history of closely scrutinizing Google products doesn't go back very far, so I couldn't say where the line between their old and new approach might be drawn. It also might be something that varied between product teams...

There is another possibility, that direct (verbal) user feedback is discounted as being "anecdotal" and not included when making "data driven" design decisions. But as you mentioned, this is all speculation without an insider's POV.

My intuition, however, is that their data-driven technique over-optimizes the various minutiae while allowing broader flaws to persist. I'd chalk that up to a lack of design vision to guide the testing.

It seems that the design elements were built progressively, while adding new features, by getting user feedback on what works and what did not. That was partly the reason why "Google Labs" existed in the first place.

I think there was a clear line drawn at least with the G+ integration, since they started consolidating the appearance of all services under the same UI and same color codes. There is a now a clear "design vision" in Google (even if it clearly sucks bad) and it's clearly not as Engineers-driven/Fonctionality-driven as before. Having Icons without text next to it is not just a style issue: it's a well known flaw in terms of usability. Everyone knows icons+text are superior to icons only. Especially when your icons are dark grey on light grey background. No differentiation whatsoever. I can't believe someone was actually paid to do this.

We use testing to discover when what "everyone knows" is wrong.