Channel Grouping in Google Analytics 4 vs Universal Analytics

Channel grouping in Google Analytics 4 is different from channel grouping in Universal Analytics. On the one hand, Google Analytics 4 has lots of new predefined groups, which should improve automatic traffic categorization. On the other hand, the ability to create custom channel groups has disappeared. This can complicate the work of marketers and analysts. Marketers will have to adjust their campaign tagging methods so that campaign traffic is properly allocated to the new groups. Meanwhile, analysts will need to create custom channel groups manually and repeat this procedure each time a new report is needed.

In this article, we discuss channel grouping features in Google Analytics 4 and what to do for those who are accustomed to using custom grouping in their reports.

Compared to Universal Analytics, Google Analytics 4 has 19 more default channel groups:

You can compare the terms and conditions for grouping channels in the Help Center of Universal Analytics and Google Analytics 4.

Some channel groups remain unchanged, such as Direct and Organic Search. Some groups in Google Analytics 4 have been given broader definitions, such as Email, Affiliates, and Paid Search. Some groups were not in Universal Analytics at all, such as Paid Social, Organic Social, and Video.

Additionally, all channels in Google Analytics 4 are divided into four subgroups:

1. Channels for manual traffic
2. Channels for Google Ads traffic
3. Channels for Display & Video 360 traffic
4. Channels for Search Ads 360 traffic

What else is different about channel grouping in Google Analytics 4?

• You cannot create custom channel groups.
• You cannot add new channels to the default channel group.
• You cannot edit the rules for the default channel group.

Unlike Universal Analytics, Google Analytics 4 is case insensitive in UTM tags. Therefore, it will attribute google / cpc and google / CPC to the same channel group.

Open Google Analytics 4 and go to the Reports section in the tab on the left:

Open the reports in the Acquisition section:

Choose the Traffic acquisition report, which contains all summaries of channel groupings:

To view statistics in terms of channel grouping, select Session default channel group in the drop-down list:

In this report, you will find:

• a breakdown of users by channel group by day
• the total number of users by channel group for the selected period
• a detailed table with data on the main metrics (sessions, users, events, conversions, etc.)

By grouping channels according to your own rules, it will be more convenient for you to analyze their effectiveness and see the whole picture.

With Universal Analytics, you can set up channel groups according to your UTM structure. Google Analytics 4 is not as flexible — you need to adjust the UTM structure to match the channel groups.

Obviously, correct UTM markup will matter more in Google Analytics 4 than in Universal Analytics. And the more employees and partners you have involved in marking campaigns, the more difficult it will be to bring it all into the right form and a unified structure.

Unlike the default channel group, a custom channel group can be applied to historical data. This way you can fix possible errors in UTM markup.

Let’s summarize the benefits of custom channel grouping:

• Transparency — You can group channels according to your own logic that is understandable to you and not rely on a conditional black box.
• Fewer problems with UTM tags and possible errors in them
• Possibility to change the channel grouping logic for historical data

When is it appropriate to use custom channel grouping?

1. You’re using a custom traffic source and/or channel.
2. Google Analytics shows several different referrals for the same channel in reports. For example, Facebook. With the help of custom grouping, all these referrals can be combined into one Facebook group.

3. Different traffic sources are part of the same marketing channel. For example, Google Analytics can report traffic from email as Newsletter/email, owox.com/referral, and freemail.co.uk/referral.
4. Your facebook/cpc campaigns fall into the Paid channel group by default, but you need to separate them into a Paid Social group.
5. You want Google Analytics reports to be understandable to all employees and partners, even those who are not very familiar with the analytics system.

In Google Analytics 4, it is not yet possible to create a custom channel grouping as we are used to doing in Universal Analytics. Perhaps this option will be added in the future. For now, you can build a report on Google Analytics 4 data with your own channel grouping in three ways:

1. Use special Exploration Reports in Google Analytics 4.
2. Connect Google Analytics 4 data to Looker Studio (formerly Google Data Studio) and set grouping conditions there.
3. Upload data from Google Analytics 4 to Google BigQuery and group channels there.

Let’s take a closer look at each of the methods.

In Google Analytics 4, you can use Exploration Reports to group channels according to your conditions and view statistics. For example, you can group Facebook sources:

To do this, open the Explore section.

Select Free form:

Specify the settings for the report:

Where:

• 1 is the name of the report.
• 2 is the period for which you want to view statistics.
• 3 and 5 are parameters in the context of which you will view statistics. To group channels, use the Session source/medium parameter.
• 4 and 6 are metrics of interest.
• 7 is the filter by sources to be grouped. On the screen is an example for Facebook. Using the filter and its conditions, you can group any sources.

After completing these settings, you will get a table with statistics on grouped channels:

Another way to customize channel grouping is to connect Google Analytics 4 data to Looker Studio (formerly Google Data Studio) with a built-in connector and set grouping conditions there. It won’t be as reliable as Google BigQuery, but if you need a quick solution, you can use this implementation.

To connect data to a report, open Looker Studio and select Blank Report:

In the opened window, select the data source. In our case, it’s Google Analytics:

Select a Google Analytics 4 account and resource to connect it to Looker Studio, and click the Add button:

Set grouping conditions:

Method 1: Use source field settings:

Method 2: Open the list of report sources:

Click Edit for the Google Analytics source:

Add a new field:

Fill in the settings for the new channel grouping field. To do this, use the CASE WHEN formula (example for grouping Facebook sources):

1 – specify the field name

2 – fill in the grouping conditions

3 – click the Save button to save the new field

Example for grouping different channels:

Click Done and go to the report visualization settings using the new field:

It’s not possible to edit historical data in Google Analytics. Therefore, if your UTM tags were configured incorrectly and you sent traffic data to the wrong channel group in Google Analytics 4, you cannot fix this in the system interface. Luckily, you can upload the required data to Google BigQuery and use SQL to correctly group channels.

Another plus of grouping channels in Google BigQuery is the ability to automate the process and significantly save analysts’ time on preparing reports. OWOX BI will help you with this.

What is the problem about?

To build reports, data from different sources must be correctly processed and combined. Data preparation is a process. It’s not enough to prepare a report (or even a lot of reports). Data must be updated regularly, and changes to reports are made permanently. All this is now done by the hands of analysts, which takes a long time and requires the help of SQL queries and scripts.

If you build reports on raw, non-business-ready data, you may encounter a lot of recurring problems: finding errors and causes of discrepancies will take a lot of time, and the channel grouping logic will need to be constantly duplicated in all SQL queries. If you decide to change the logic — for example, move one channel to another group — then all requests will need to be redone. With data transformation and modeling, this task is solved before a report is built.

How OWOX solves these issues

OWOX BI collects raw data and automatically converts it to the format you need according to your company’s data model. Due to seamless data collection and preparation, you don’t have the risk of human errors and poor execution quality. Moreover, you have full control over the whole data flow and can see any errors as they appear.

Automated SQL-based transformations and UI scheduling empower your teams to transform data. No engineering skills or complex tools required. If you need to change the grouping of channels, for example, it’s enough to change the grouping once at the model level and it will be applied to all reports. You don’t need to manually change everything and then look for discrepancies.

In addition, OWOX BI collects traffic sources for each user visit and not just for the first visit as Google Analytics does. This will give you the flexibility to define conversion sources and channel scoring.

Currently, there is only a manual way to import ad cost data into Google Analytics 4. You can automate this process and save valuable time, using the solution from OWOX BI.

Important! If you plan to import advertising costs to Google Analytics 4, then you need to add the required parameter utm_id (campaign identifier) to the links of your advertisement campaigns.

In Google Analytics 4, there’s no way to set up custom channel grouping. You can build a report on Google Analytics 4 data with your own channel grouping in several ways:

• Use special Exploration Reports in Google Analytics 4.
• Connect Google Analytics 4 data to Looker Studio (formerly Google Data Studio) and set grouping conditions there.
• Upload data from Google Analytics 4 to Google BigQuery and group channels there using SQL.
• Use OWOX BI Transformation.

The first three methods involve the manual work of analysts, which must be repeated every time a new report is needed. To automate the process and save time, you can create a data model using OWOX BI Transformation. Use prebuilt SQL transformations (or create your own) to make raw data business-ready and get insights faster.