That is what I noticed for mobile analytics (firebase analytics) as well. It's nice looking at the daily active users and such, but you don't really get any actionable data from it.
For me, a much better approach would be my own analytics, tailored to my product using simple sql statements.
For example how many of my users are tracking mainly dividends vs tracking their portfolio? To get such data I would have to invest more time into setting the right firebase analytics flags than just creating a BI Dashboard that uses one sql query under the hood.
I had similar frustrations with google analytics and decided to do the same.
Are there best practices to follow? I just have a table with: id, id of thing being accessed, user email, time, event enum, and notes.
It works well enough, and I have a python script to query the table and aggregate and print graph or print the results. But it would be great if there was some "bring your own data" dashboard that would let me view the time series w/ things like filters
Wow, looks good. I am planning to build something similar but with risk/quant analytics that I am familiar with from Capital Markets. I have mostly worked around traders in my day job.
I am going to build a risk management app, for your stock portfolio. Not a quant fond. Please do not invest your money in a quant fund, all such constructions are based on the assumptions that the market dynamics an be analysed and that they then stay the same for the lifetime of the fund which is very rarely the case.
For me, a much better approach would be my own analytics, tailored to my product using simple sql statements.
For example how many of my users are tracking mainly dividends vs tracking their portfolio? To get such data I would have to invest more time into setting the right firebase analytics flags than just creating a BI Dashboard that uses one sql query under the hood.