I've done a lot with GA over the years, and it's kind of like Photoshop -- powerful, overwhelming, and the results of years of things being bolted on. And like Photoshop, knowing the tool doesn't necessarily mean you can create a pleasing result, instead it helps to know what you want out of it.
To get a good result you need to know how to work with, and (perhaps more importantly) not be misled by your analytics data. That is, there's a body of knowledge outside of "How to use GA" that will make you 100x more effective at actually getting a result with your data in GA.
Topics that are worth reading up on & thinking about: - Statistical significance, even at a very simple level (so you have a sense of when you're just looking at noise, & how much data you need to make informed decisions). For example, compare engagement stats by browser (or even browser version) for a given site/app, and notice the difference. 99.9% of time this is just noise. - How to report simply and effectively -- all the instrumentation in the world won't help if you can't pull it out in a meaningful way. - How to work within your organisation or team to effectively run controlled experiments to measure changes in behaviour (if that's what you want to do). I.e., if you have the data, what are you going to do with it?
Above all you need to be really, really skeptical of your data. If it looks too good to be true, it probably is. If it looks wrong, it probably is. Measuring human behaviour is hard; measuring human behavior combined with fragile technology is harder, and measuring human behavior and identifying meaningful ways to change it is well, you get the idea.
That said, everyone starts somewhere, so keep it simple, feel your way through it, make lots of mistakes, keep reading, and keep learning :)
Also, Avinash Kaushik is the go-to authority on analytics as a discipline. His work leans towards the marketing side of things, but there's lots to learn for UX and design too.
I've done a lot with GA over the years, and it's kind of like Photoshop -- powerful, overwhelming, and the results of years of things being bolted on. And like Photoshop, knowing the tool doesn't necessarily mean you can create a pleasing result, instead it helps to know what you want out of it.
To get a good result you need to know how to work with, and (perhaps more importantly) not be misled by your analytics data. That is, there's a body of knowledge outside of "How to use GA" that will make you 100x more effective at actually getting a result with your data in GA.
Topics that are worth reading up on & thinking about: - Statistical significance, even at a very simple level (so you have a sense of when you're just looking at noise, & how much data you need to make informed decisions). For example, compare engagement stats by browser (or even browser version) for a given site/app, and notice the difference. 99.9% of time this is just noise. - How to report simply and effectively -- all the instrumentation in the world won't help if you can't pull it out in a meaningful way. - How to work within your organisation or team to effectively run controlled experiments to measure changes in behaviour (if that's what you want to do). I.e., if you have the data, what are you going to do with it?
Above all you need to be really, really skeptical of your data. If it looks too good to be true, it probably is. If it looks wrong, it probably is. Measuring human behaviour is hard; measuring human behavior combined with fragile technology is harder, and measuring human behavior and identifying meaningful ways to change it is well, you get the idea.
That said, everyone starts somewhere, so keep it simple, feel your way through it, make lots of mistakes, keep reading, and keep learning :)
Also, Avinash Kaushik is the go-to authority on analytics as a discipline. His work leans towards the marketing side of things, but there's lots to learn for UX and design too.
Good luck!