Are you looking to replicate UA views in GA4?
Google Analytics 4 has officially replaced Universal Analytics. The good old UA views are unavailable in GA4. How can we live with that? We’ll show you how to replicate UA views in GA4 by segmenting your data.
We’ll learn how to achieve similar results as views using five different workarounds. These workarounds will help you understand the structure of GA4. You’ll learn how to navigate the interface in the absence of views and the limitations of the free version.
Spoiler alert: Creating an exact equivalent is impossible, and all workarounds have limitations.
Here is an overview of what we’ll cover:
- GA4 Account Structure
- What are Universal Analytics Views?
- Segmenting Data with Comparisons
- Segmenting Data with Filters
- Segmenting Data with Explorations
- Segmenting Data with Looker Studio
- BigQuery for Advanced Data Exploration
Let’s dive in!
GA4 Account Structure
One of the most frequently asked questions nowadays is: “How should I structure my GA4 account?” Should I create properties and streams? These are great questions, especially considering the challenge we face with the absence of views.
There are three main pillars of GA4: account, property, and stream.
Within an account, you can create properties. Similarly, within properties, you can create streams. One important thing to note is that streams do not equal views that were in Universal Analytics.
To look at our property in Google Analytics, go to the Admin section. On the left side, we have a column with everything related to the account. On the right, we have settings related to our property.
You can create data streams within a property.
Notice that there is a huge blank space on the right side of our screen. This area is where views used to live in Universal Analytics, and perhaps the creators of the tool chose to preserve the structure. In Google Analytics 360, you have sub-properties that can act similarly to views.
To access this feature, you must get the paid version of GA4. We’ll only focus on the free version in this tutorial, so we will not cover sub-properties.
What are Universal Analytics Views?
UA views are subsets of data. Below are examples of views in a Universal Analytics property.
First, we have the master view, a working view where you would apply multiple filters to configure it. Next, the test view would serve as your testing environment. Finally, the raw data view has your plain data.
Another example could be having separate views for different language versions of your website. For example, your website could have an English version, German version, Dutch version, etc.
We used to have views in Universal Analytics, but now they are unavailable. So, what can we do here? We have two options: get the paid version or accept this challenge and stick with the available features in GA4.
As of now, we do not have views in GA4, so we can only do workarounds to replicate UA views in GA4.
Segmenting Data with Comparisons
Let’s state our problem first.
Here, we have our main website for MeasureSchool.
Next, we also have the URL live.measure.school.
Here is where we conduct live training for a limited group of people, those who availed of our MeasureMasters membership.
Although we have different links and seemingly different domain names, these are part of one user journey. We track everything under one property and one stream.
However, how can we view the data separately?
In Universal Analytics, we would have created a separate view for these two URLs.
As we do not have these in GA4, we need to be creative. The first workaround we can do is to use comparisons.
Here, you can see our Pages and screens report.
To look at a specific subset of data, click Add Comparison or Edit Comparisons.
Next, click Add new comparison.
Let’s create a comparison for the live training link. Select the Hostname dimension and live.measure.school for the dimension value. Finally, click Apply.
We have the comparison values in orange and the data for all users in blue. We can already look at the specific subset of data.
However, we should note that we cannot save this comparison. It will not persist in our reports. If we close this report and reopen it, this comparison will not be available, which is a definite limitation. Additionally, the conditions you can provide are a bit limited.
These are the disadvantages of comparisons. This approach is for when you want to look at a subset of your data and aren’t interested in viewing it again.
What if we want a less temporary approach?
Segmenting Data with Filters
We can use filters in our standard reports in GA4.
Say you want to look at the same pages and screens report, but only for the live training link.
First, click Customize Report.
Next, click Add Filter.
Put the condition to include Hostname = live.measure.school. Then, click Apply.
Now we can view the data only for our live training link.
đź’ˇ Top Tip: Check out our guide on How to Customize Your Google Analytics 4 Reports for a complete guide on all the views and settings you can customize in your standard reports.
The good thing here is that we can save this report. Click Save → Save as a new report.
Give the report a descriptive name, then click Save. You can also add a description.
Let’s go back to our standard reports. If we double-check here, we cannot see our report. Why is it not available?
First, let’s confirm if we have successfully saved our report. Go to the Library.
Here, we can see our filtered report. To see it in the reports tab, we have to add it to our collection. Click Edit Collection under the Life cycle group.
Look for our report, then drag it under the engagement topic.
Finally, click Save → Save Changes to Current Collection.
Now, let’s go back and double-check if it is indeed available now. Voila! We can now see our custom report.
The second way to segment your data is to add filters to your report.
If you want to dive deeper and want to answer specific questions with your data, we can create an exploration report.
Segmenting Data with Explorations
The third way to replicate UA views in GA4 is to utilize exploration reports.
Go to the Explore tab.
Here, we have already created a report which is a simple Free-form exploration report.
Add the event name dimension and event count metric to your free-form exploration report. You should get a view like this one.
Again, let’s say we want to look at data only for live.measure.school. For this, we need to create a new segment.
Click + beside the segment section.
Next, click the Event segment.
Again, set the condition to Hostname contains live.measure.school. Provide a name and description. Finally, click Save and Apply.
GA4 will then automatically add this segment to your report.
Now, we can look at this specific subset of data for our analysis.
There are also some limitations here. Each time you create a new exploration report, you will need to make this segment from scratch. You cannot share these segments between your explorations, unfortunately.
These three methods on how to replicate UA views in GA4 are how you can deal with UA views within the tool. If this does not satisfy your needs, we can go further, using other external tools like Looker Studio or BigQuery.
Segmenting Data with Looker Studio
Let’s start with Looker Studio.
Here, you can see a simple report for our testing purposes.
🚨 Note: Looker Studio has a native Google Analytics connector. Check out our guide on the Looker Studio connectors to learn how to use your GA4 data in Looker Studio.
Here, we can see the data altogether, but say we want to filter it out somehow. One option is to create a filter.
Go to File → Report settings.
Scroll down a bit, and you’ll see the filters section. Click Add a Filter.
Next, click Create a Filter.
Provide a name for the filter. Next, set the filter to “Include Hostname Equal to (=) live.measure.school.” Finally, click Save.
With filters, you can work with that specific subset of data.
Setting a filter at the report level is one option.
In the next option, first, delete the filter by clicking âś•.
Let’s filter our report differently.
What if the viewer of the report wants to have more control over the data and have the means to look at the whole data set and the subset of data for the live.measure.school?
In this case, we can add a control. Click Add a Control → Drop-down List.
Place this data control at the upper-right corner of the page. Next, change the control field to Hostname.
Click the data control and select live.measure.school.
Now, we can see the same numbers as when we implemented the filter.
This method of learning to replicate UA views in GA4 may not satisfy your needs because Looker Studio can be quite limiting.
In this case, the GA4 BigQuery expert will come to our rescue!
BigQuery for Advanced Data Exploration
Here is the BigQuery interface.
BigQuery is a data warehouse that offers you so much flexibility and control over your data. The great thing with GA4 is that we finally have a free connector available. Before, it was only possible with the paid version. This is a considerable improvement of the tool.
Additionally, the speed in BigQuery is simply brilliant! We can query through large sets of data within seconds. Using BigQuery is another workaround for dealing with views. It requires more advanced skills, such as knowing SQL.
đź’ˇ Top Tip: Check out our guides on How to Use the GA4 SQL Tool for BigQuery and How to Use BigQuery with ChatGPT to get you started with BigQuery.
We have multiple resources here on our website and YouTube channel. We also have a super beginner-friendly and extensive five-hour course in the MeasureMasters membership.
We recommend taking one because the tracking landscape is changing, and BigQuery can offer many advantages.
Here, we’re working with the data. We can define the data set we want to work with. You can model your data and export it to a separate view.
You can also visualize your data in Looker Studio, without facing quota limitations.
Summary
To summarize, let’s clear up a common misconception: GA4 data streams do not equal UA views. We do not recommend creating multiple web streams in one property. If you don’t want to analyze your data together, it is better to create separate properties.
You can utilize comparisons, filters, and segments to work with your subset of data within GA4. If you require more flexibility in handling your data, other solutions involve external tools like Looker Studio and BigQuery.
These are five different ways to replicate UA views in GA4. These workarounds are not perfect, but we hope you can find one here suitable for your needs.
Check out the Google documentation for the UA view-related features in GA4 properties. If you find yourself missing the features of Universal Analytics, consider these Top 5 GA4 Alternatives and see if one fits your needs better.
Have you tried any of these solutions? What workarounds do you use to replicate UA views in GA4? Let us know in the comments below!