To provide a personal anecdote; I don't like using Microsoft products and always look for an open-source, unixy replacement when at home. I complain about Microsoft (products, economy, & policy) at almost every opportunity. And in the same breath I will wholeheartedly recommend the same Microsoft product that I personally wouldn't use to a client in need. The ubiquity and quality of Microsoft products is too significant to ignore. If I were to recommend one of my neckbeard alternatives I would certainly get support calls about it all the time.
But if you only ever went by my social media posts you would think I absolutely hate Microsoft and vehemently refuse to use their products. That's not the case. I just don't get excited enough about Microsoft as a business to go parroting their marketing and waving their flag. The good balances the bad enough that I stay with the brand, but human negativity bias still exists and I've got to complain. The product is too ubiquitous to ignore.
A useful concept for people to remember as it applies everywhere. Particularly as we get drawn into tribal politics, it would be better for people to remember that the opposition is not uniform and consists of many different viewpoints. For someone who wants to be divisive, it is trivial to cherry pick examples of bad behavior ("hypocritical") by pretending that those you disagree with must all share exactly the same priorities and opinions.
Individual pieces of feedback can be valuable, but if you let it do the driving then you can end up making changes that worsen your product. You become subject to the will of the most vocal critics at any given moment.
People are more motivated to comment when they're upset about something, so it ends up looking like everyone here hates everything big tech does, when it may be that a small number of people hate decision X, a small number of people hate decision Y, and most people either like them or don't care.
You often hear complaints that big tech drives people to extreme viewpoints through algorithms. But the natural human algorithm of putting more effort into the negative than the positive seems to lead to the same outcome.