Reid asks, “are you saying that we should use properties in the same way we would use views in UA? And if so, does that mean a separate tag for each property in GTM?”
To understand the layout of Google Analytics 4 and where stuff has or has not gone, we have to understand the design philosophy. GA 4 looks at events done by users, so all the settings are centered around those. Views aren’t focused on either, so aren’t in the application; that’s something we now do in Google Data Studio.
Likewise, segments still exist, but they’re now in the Analysis hub and are limited to Google Analytics 4 only. If you want to replicate the segments functionality of GA 3, you’ll need to use event parameters and values, constructed in Tag Manager, to permanently tag that traffic as of this writing.
Can’t see anything? Watch it on YouTube here.
Listen to the audio here:
- Got a question for You Ask, I’ll Answer? Submit it here!
- Subscribe to my weekly newsletter for more useful marketing tips.
- Find older episodes of You Ask, I Answer on my YouTube channel.
- Need help with your company’s data and analytics? Let me know!
- Join my free Slack group for marketers interested in analytics!
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
In today’s episode Reed asks, Are you saying that we should use properties in the same way we would use views and Universal Analytics? And if so, does that mean a separate tag for each property in Google Tag Manager, this is in reference to Google Analytics for.
To understand the layout of Google Analytics for and where stuff has or has not gone, we have to understand the design philosophy around it.
So Google Analytics for really just like Firebase Analytics, which if you’re familiar with Firebase, for app measurement, Google Analytics for is basically extending Firebase to the web.
It is a market contrast to the way that Google Analytics three, aka Universal Analytics function, which was still an offshoot of the really the old, urgent analytics software at Google acquired back in 2005, right, so Google Analytics four is not just a version change in software is a completely different piece of software.
It does not share the same code base, it does not share any of the, the the legacy stuff that has been with Universal Analytics really forever.
And so part of that is that we have to understand there’s a new hierarchy.
Let’s go ahead and flip over here.
So this is Google Analytics three, if you remember, you have sort of a hierarchy of the account, which is the logical organization, you have the property, which is a logical website.
And then you have the view, which is the logical division within your company, that would be looking at a Google Analytics data in a certain way.
When we look at Google Analytics for the and the admin, for that, we see a very different view of the world, right, we have the account, which is still the logical entity, we didn’t have the property, which is the logical collection of users, that’s really important.
And then within that, you think of things like data streams, which are individual pieces of data about groups of users.
Now, why this matters is that the view is administrative, right? There’s nothing here that is unique to the user that you would be doing user level stuff with.
Whereas in g4, they acknowledge that we’re saying, Yeah, there’s no view because all that admin stuff should be somewhere else.
It doesn’t belong in Google Analytics.
So let’s look at a few of these things and see, where did they go? goals? Pretty straightforward goals has become conversions.
Right? So if we go into analytics, here, we have our conversions.
And the conversions come from events, right? So we specify where you can either automatically detect many events, or build custom events, either in Google Tag Manager or in Google Analytics and denote them as conversions.
So that’s a user level thing.
And that’s now done in the main application.
We have things like content groupings, that’s administrative that does not exist here at all, that would be something that we would do in reporting, if we want to in Google Data Studio, and to some degree can be done in, in Google Analytics for by building comparisons, right? comparisons are kind of the in application ad hoc way to build what we used to call segments and a lot of ways, right, well, you can look at dimensions and metrics and and and group things together.
For for logical ad hoc analysis, we look at filters.
Filters are done at the data stream level now, and there are not many right now.
There are, I believe, honestly, like, IP filters, let’s take a look here.
I just have some measurement stuff, I believe you can.
I don’t remember where it is in here.
Oh, there is cross domain tracking.
So modify events, create events, configure domains, that’s where you do your cross domain stuff, and define internal traffic.
So you can do modification of tagging stuff within there.
You can also access some of the stuff through the API.
Channels don’t exist at all in Google Analytics for that the concept I guess, didn’t work out.
And understandably so when, if you’ve done any work with Google Analytics, three, you know, what a pain it is.
To get channels to function correctly with the default channel groupings have been such a hot mess for so long, because people are inconsistent about how they do source and medium tagging, right.
Anyone who’s worked with any agency any To have more than one, you know that the UTM tracking source, medium tracking is just a free for all.
And that makes it really difficult to do any kind of analysis because there’s no consistency, right? So half of the time, half your social traffic was miscategorized as referral traffic, and things like that.
So Google just got rid of it entirely.
Now you have these choices, medium source, source, medium combo campaign, and then a few other things here.
Which means that if you’re looking at things like source medium, this gives you an awful lot of data.
Now, is it as conveniently grouped together? No, not anymore.
But is it something that you can look at and see now logical clusterings? Yes, you can see, you know, Twitter and Facebook, LinkedIn, and so on, and so forth.
So channel groupings, kind of got ecommerce, ecommerce as a whole big bag of arms, there is there’s actually a great post by a CMO Ahava, that is like 40 pages long on all the differences between Google Tag Manager, Google Analytics three and Google Analytics four when it comes to setting up e commerce and how much of it has to be done within Google Tag Manager.
So if you have not read seamos blog, go to Sema hava.com.
And he’s got a huge amount of stuff on it.
calculated metrics, again, mostly administrative segments, were an administrative thing that still technically exists in Google Analytics for, you have to go into the analysis hub for them.
And inside the analysis hub, you can build segments, but they’re unique to Google Analytics, for as far as I know, I have not been able to replicate getting them into Google Data Studio.
So if you want to do for example, social media traffic, you can still put together the you know, these crazy regex is and build all your let’s see, all your traffic comparisons, let’s do a traffic comparison here.
Let’s put in our social media traffic as another segment.
And so you can still do that.
If you want to be able to pass the data from application to application meaning from Google Analytics to say Google Data Studio, that’s no longer the case, you used to be able to do that.
But now, if you look inside of Google Data Studio in the GA for connector there, you really have a couple of different things.
And it depends on how you use segments did you use segments to essentially be a type of filter, if so now, you just use the filters.
If you use as a logical group of users, you would now build that in Tag Manager with events and parameters or event parameters and values, and then pass those parameters and values to analytics and then to Data Studio so that you could create those analytical segments.
So it requires you to rethink how you use the segment and decide, is it just a filter? If so you can replicate it natively in Data Studio? Is it a logical grouping of users that you need to have cross platform cross application functionality that needs to be denoted in the event at the time the event is created.
So it’s a very different way of thinking about these things.
But what used to be in the view, is now in a bunch of different places, and a lot of that has been offloaded to other functions.
If you use views for logical groupings inside of your company, you don’t want to create new properties, that’s just a mess waiting to happen.
What you want to do is offload that segmentation of your internal use to Google Data Studio.
That’s where, you know, you create a dashboard for accounting, you create a dashboard for HR, you create a dashboard for the inbound marketing team, you create a dashboard for the PPC marketing team.
And that’s the logical way to handle what used to be digging into it and letting him have it every 40 people have access to Google Analytics, it’s really not intended for that anymore.
It’s now an analysis tool.
And Data Studio is the reporting tool.
A lot of people got used to using Google Analytics for reporting.
And that’s not its function anymore, at least from what I can tell.
Now, I also have no internal knowledge of how Google debated isn’t based on what we can see in the application.
So it’s a good question.
I would not set up more than one property for more than one distinct user base.
Instead, use the different features and use the the applications that are there to make those distinctions now, I’ve got follow up questions, leave them in the comments box below.
Subscribe to the YouTube channel in the newsletter, we’ll talk to you soon take care want help solving your company’s data analytics and digital marketing problems.
This is Trust insights.ai today and let us know how we can help you
You might also enjoy:
- Google Analytics: A Content Marketing Engagement Test
- Best Practices for Public Speaking Pages
- Six Types of Marketing Demand Generation
- The Year of the Yin Metal Ox
- Transformer les gens, les processus et la technologie - Christopher S. Penn - Conférencier principal en science des données marketing
Want to read more like this from Christopher Penn? Get updates here:
Get your copy of AI For Marketers