Not a stupid question. These products tend to offer a lot more functionality and flexibility in terms of how you consume your data. Different analysis possibilities, fancy ML models, custom dashboards, etc.
Also more control over how the data is ingested (sampling or not, etc.)
These products feel more suited to teams building rich apps/webapps where as GA seems to have its roots in sites that are more "content-based" (news sites, etc.).
And for many, not sending the data to Google is an advantage in and of itself.
I'll also add that product analytics software is built more towards measuring depth of engagement: How many times has this user returned to our site? What is the average LTV of this cohort? What is cohort X's n-day retention compared to cohort Y? What features have correlation to those differences? Did this experiment lead to improvements in retention - 30 days later?
Google isn't built to go that deep. Sure you can see that 3% of users have used feature X, but you can't really effectively dig in and see how upstream or downstream actions and events influence each other. Sure you can create some custom segments on a sessions/user level - but that quickly turns complex and unwieldy if you have several segments, cohorts and funnels. Also there are a lot of charts that are just plain better in product analytics tools. Retention charts, funnels and path diagrams are obvious examples.
At my previous employer we were using GA and it's very flexible. We were able to track all DOM interactions by just configuring the included js. Although, querying that later with tools engineers can use and build is a whole different story.
Also more control over how the data is ingested (sampling or not, etc.)
These products feel more suited to teams building rich apps/webapps where as GA seems to have its roots in sites that are more "content-based" (news sites, etc.).
And for many, not sending the data to Google is an advantage in and of itself.