Hi! Could anyone advice a guide/set of articles of how to learn using GA, for solving basic UX tasks, creating funnels, tracking behaviour, etc. GA Academy is good, something else?
Following this thread.
Gonna write a medium post on it! Gonna publicly say here I want to have it ready by next Wednesday so I'm held accountable.
I'm expecting you post the link to the article here by Wednesday, man!
The NN Group has a really great article with practical examples and short tutorials. https://www.nngroup.com/articles/analytics-reports-ux-strategists/
Something like this is really helpful! Thanks! So it's like a cookbook, recipes how to use such a powerful tool as GA, without been overwhelmed with it's complexity.
May I add the idea of also learning to use Google Tag Manager, it helps you a lot to set up useful events a lot easier .. which helps in tracking behaviour, etc. Going through Simo Ahava's blog is helpful.https://www.simoahava.com/
First recommendation is to address very specific goals before you even poke around in GA. Then you can find out which data points tell this story.
The most common use case for landing pages is setting up event triggers for a check out form and seeing how far people get down your funnel. Setting up GA for a product is going to involve a lot more.
It's funny how:
- important this topic feels
- little I feel I know of it
- much I struggle with it when I open the bloody thing
Other than basic analysis of bounce/exit/browser/os/conversions and some in-page analytics I don't get very far with the tool.
The good news is that those are generally very important in determining whether something is effective or not.
The bad news is that I feel there should be a lot more possible with it. Might be a UI issue.
I'm doubling you on your points, adding one more: - strong gut feeling that I'll benefit of utilizing GA more It's like an Adobe AE these days, you're not going to switch to motion design, but have to learn what's 'just enough'.
Can't recommend it because I haven't read it but I've been to a talk by the author and he knows his stuff. Could be worth picking up - http://www.lukehay.co.uk/the-book/
Thanks! Adding to my read-list
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.
Really interested in this. I started thinking about it recently and so far I've applied Google's HEART framework. Wrote about it here https://blog.paystack.com/building-paystack-product-analytics-3f9be65edcdc
I would recommend checking out the Segment Academy starting with this post: https://segment.com/academy/intro/how-to-create-a-tracking-plan/
While they do give examples from their product (it's great by the way) the fundamentals of data analytics are transferrable. I fully agree with Dexter W that identifying the questions you want to answer with analytics data is more important than the tool itself.
Hey, despite not having any particular GA oriented guide to provide I do have some personal experience to share in how to go about using analytics tools to UX advantage.
From my perspective the first thing I wanted to gather was what to measure and how to measure it, basically defining the UX KPI's I wanted to observe. This goes beyond the "regular" ones like Conversion, Acquisition, etc. I wanted to answer more specific UX questions, such as: which terms are been searched? Which tabs are been explored? Do people add items from the list or the detail page?
We've created a spreadsheet on Google Docs with 3 sheets: 1) The first one was for all the direct metrics I wanted to gather (bottom bar taps, add to cart from different places, etc) 2) The second one was the funnels I wanted to create from those metrics, for instance: add to cart > open cart > begin checkout > checkout steps > purchase. 3) The last one was for KPI's that required custom calculation to achieve, such as Product traffic vs Conversion rate.
THEN we've teamed up with developers to check how easy it was to register all those events and which metrics were actually event parameters, in order to tackle this part we delved into the GA documentation in order to find the right tool for each of this metrics,
During this process not only we discovered a ton of nice features of GA, but we've found out that some visualizations we needed we're built into it (looking from this perspective we should've done this sooner), to mention a few: 1) The User Flow feature is very nice to see user navigational behavior and bounce rates 2) Creating filtered views of users that belonged to a certain group to evaluate differences in the product use.
The good thing is that now we've familiarized enough with the act of how to measure stuff that it's easy to change platforms without much impact. In some other products we've used Firebase with Fabric to substitute GA, and it was much easier to do so.
Thanks for sharing your experience, Lucas! I do like the User Flow feature also. There couldn't be a silver bullet, as the products are different of course. Creating funnels is probably the most important tool to get some ideas on user behaviours.
I’m product owner at Taglayer. While it doesn’t immediatly compete with GA, it offers a simpler interface for basic site analytics. It also comes with a visual editor, which lets you change your website without any coding skills required.
You can check it at https://taglayer.com Let me know what you think. :)
Funny, I just recently created a bunch of confusing regex so I could at least drill down by viewport, and thought that it would be nice if there was a guide to sort this stuff out properly for designers.
Take a look at the documentation https://support.google.com/analytics/?hl=en#topic=3544906 Also at Google Academy for Ads https://academy.exceedlms.com/student/catalog?search=analytics&content_type=&duration=&sort=
I prefer Heap Analytics to GA personally. It's a lot easier to set up, create events, create funnels, etc.
Yes, there are tons of them, HotJar to mention. But essentially I find them as improved GA. Often paid.
I've setup GA on pretty much every project I've worked on for the last 8 years. It's a handy thing to have up and running for basic metrics about your website/app. But to be honest, I find GA actually to be quite onerous in determining the kinds of things that UI/UX Designers would like to know. My advice would be to make sure you look at something like https://www.fullstory.com/ which captures all the little details and unexpected behaviours that are really important to understand. Without this kind of detail, you can very easily read GA data wrong.
Bravo, good thread!
Just want to follow the thread! I'm a new UX designer and I'm really interested in analytics. Now I have got my head around Appsee I'd love to try learn more about GA!
Interested in this thread
Hello! We've written a cool free eBook - Getting Started with Google Analytics https://www.templatemonster.com/blog/free-ebook-getting-started-with-google-analytics/