If anything there often appears to be a negative correlation with increased data collection and product quality, in my experience.

I figure it must be due to an abdication of responsibility-- absent information, the product must at least appeal to someone working on it who is making decisions about what is good and what isn't, and so it will also appeal to people who share their preferences. But with the power of DATA we can design products for the 'average user' which can be a product that appeals to no single person at all!

Imagine that you were making shirts. To try to appeal to the most number of people, you make a shirt sized for the average person. But if the distribution of sizes is multimodal or skewed the mean may be a size that fits few or even absolutely no one. You would have done better picking a random person from the factory and making shirts that fit them.

When your problem has many dimensions like system functionality, the number of ways you can target an average but then fit no one as a result increases exponentially.

Pre-corporatized open source usually worked like fitting the random factory worker: developers made software that worked for them. It might not be great for everyone, but it was great for people with similar preferences. If it didn't fit you well you could use a different piece of software.

In corportized open source huge amounts of funding goes into particular solutions, they end up tightly integrated. Support for alternatives are defunded (or just eclipsed by better funded but soulless rivals). You might not want to use gnome, but if you use KDE, you may find fedora's display subsystem crashes out any time you let your monitor go to sleep or may find yourself unable to configure your network interfaces (to cite some real examples of problems my friends of experienced)-- you end up stuck spending your life essentially creating your own distribution, rather than saving the time that you hoped to save by running one made by someone else.

Of course, people doing product design aren't idiots and some places make an effort to capture multimodality though things like targeting "personas"-- which are inevitably stereotyped, patronizing, and overly simplified (like assuming a teacher can't learn to use a command prompt or a bug tracker). Or through efforts like user studies but these are almost always done with very unrepresentative users, people with nothing better to do then get paid $50 to try someting out, and you learn only about the experience of people with no experience and no real commitment or purpose to their usage (driving you to make an obscenely dumbed down product). ... or by things like telemetry, which even at their best will fail to capture things like "I might not use the feature often, but it's a huge deal in the rare events I need it." or get distorted by the preferences of day-0 users, some large percentage of which will decide the whole thing isn't for them no matter what you do.

So why would non-idiots do things that don't have good results? As sibling posts note, people are responding to the incentives in their organizations which favor a lot of wheel spinning on stuff that produces interesting reports. People wisely apply their efforts towards their incentives-- their definition of a good result doesn't need to have much relation to any external definition of good.