Universal Analytics had many pre-built reports that you could use. Google Analytics 4 has few, but almost any report available in Google Analytics Legacy can be built in Google Analytics 4 Explore and even more. 

For instance, many analysts used Free Form exploration to build the Landing Page report until Google implemented it in GA4. 

Therefore I dedicate this article to explaining how to use Free Form report in Google Analytics 4. If you want to learn a bit more about GA4 Explore reports, don’t hesitate to read other articles in this series:

1. Funnel Exploration
2. Path Exploration
3. Cohort Exploration
4. Segment Overlap
5. User Explorer
6. User Lifetime 

So, let’s get started with what’s a Free Form report and when you should use it. 

What is Free Form report, and when should you use it?

Free Form report is some kind of Google Sheets or Excel sheet where you can select columns and rows, and apply filters and segments. After adjusting it, you can visualise the data using one of the 6 visualisation techniques. You can also use custom dimensions and metrics in this report; the metrics you import into GA4 will also be available. 

This report allows you to conduct ad-hoc analyses and better understand your mobile app or website visitors. Moreover, you can use machine-learning models to determine anomalies (outliers) of your metric values and many more. If you need to find something extraordinary and want to look deeper into users’ profiles, you can do it as well by clicking the right button of your mouse and selecting “View Users” (User Explorer report). 

This outstanding feature will allow you to do much stuff without leaving the Google Analytics 4 interface. I highly encourage you to try it in action and practice using it. Below you can find the instructions on how to use it. 

GA4 Free Form Report Interface

First, in order to create the Free Form report in Google Analytics 4, you should take a few actions:

After these steps, you should modify the settings to see what you need. For this article, I will use the publicly available GA4 property that stores ecommerce data.  If you are not an Ecommerce business, you can change the events. All instructions below will apply to any company.

I will check how much traffic and revenue US citizens generate from Google Ads campaigns.

I recommend you follow my article and make the necessary adjustments in GA4 Free Table report.

So, as you can see in the screenshot above, the report consists of three parts. The first part is called “Variables”, the second “Tab Settings”, and the last one “Report View”.

Report part #1 – Variables

Let’s start with the first one. It consists of the following elements:

1. Exploration Name
2. Dates range
3. Segments
4. Dimensions
5. Metrics

1.1 Exploration Name

Exploration Name allows you to specify the report’s name and save it in Google Analytics 4 to access later. You don’t need to click on any button. GA4 saves the name and the report automatically whenever you exit the report. 

Let’s title it “Google Ads US Performance” 

1.2. Date ranges

You can use date ranges to extend the dates of your report or limit it to one date. GA4 Exploration allows you to see the data up to yesterday. If you are interested in real-time (today’s data), you should enable BigQuery integration. Let’s select the last 30 days. 

1.3 Segments

The segments feature allows you to select a group of users for the analysis. 

For this report, I will create a segment that stores only users whose first default channel grouping was Paid Search. 

You can use (custom) dimensions and metrics in Google Analytics 4 to create more advanced segments. 

1.4 Dimensions

This section allows you to add as many dimensions as you want. You can use the dimensions to break down your data afterwards (by adding more rows and columns) or create filters. 

For our case, we import the following dimensions:

1. Country
2. First user medium
3. First user source
4. First user default channel grouping

1.5 Metrics

Apart from importing and using dimensions, you can also use metrics. When you import metrics, you can see the whole number of metrics available for this report. 

As I told above, we will use “Total users”, “Active Users”, “Event count”, “Ecommerce revenue”, “Transactions”, “Conversions”, and “User engagement”. 

After I imported all dimensions and metrics, I got this view.

After understanding the first part of the report, let’s look at the second.

Report part #2 – Tab Settings

The second section of the segment exploration report is “Tab Settings”. It consists of the following sections:

1. Technique
2. Visualization
3. Segment comparisons
4. Pivot
5. Rows
6. Columns 
7. Values (+ cell type)
8. Filters

It’s a vast topic, but let’s start with the first one. 

2.1 Technique

This feature could be used to jump from one report to another of Google Analytics 4 Explore functionality.

2.2 Visualization

This section allows you to use different types of visualisations. The default one is a table view but you can switch to:

1. Donut chart
2. Line chart
3. Scatterplot
4. Bar chart
5. Geo map.

Of course, it’s up to you to decide which one you need to use but, in general, I would stick to the following:

First, use a donut chart to see the percentage of the total audience if the dimension doesn’t have more than 6 values. For instance, you can be interested in what devices users use and whether mobile traffic generates more than 50% of the overall revenue. Since device type includes four values: desktop, mobile, tablet and smartTV. A donut chart can be the most appropriate option.

Second, use a bar chart to see the percentage of the total audience if the dimension has more than 6 values. For instance, countries. This variable can have 100+ variables for your GA4 property, and the donut chart isn’t the best option. The bar chart or geo map is the best one.

Third, you should use a line chart to see the metric change over time. It also allows you to detect anomalies (outliers) and analyse what caused that.

Fourth, scatterplot, if you want to see how one numerical metric depends on another, for instance, new users and transactions and then break down them by country, you can use this report.

Fifth, if you want to see a breakdown of the metric by geo dimension (region, country, city, etc.), consider using a geo map. It’s easy to comprehend this report for the majority of people.

Although different visualisation options can be easy to use, some of them require additional knowledge because they can have additional settings. Therefore, you should read additional articles above. For our sample chart, we will use “Table” visualisation.

2.3 Segment comparisons

This is where you apply the segment you created in section 1.3. To apply the segment, you should drag and drop it from section 1.3 to section 2.3. When you create the new segment, it’s automatically applied after you save it.  Remember that segments and filters are the most crucial elements of your visualisation. 

2.4 Pivot

When you use more than 2 dimensions in rows or columns, you can pivot them. When you pivot them, you change the column to the row or the row to the column. You can select if you want to use the first or last row/column. I recommend you play a bit with that to understand it. It can be a helpful feature to visualise data better.

2.5 Rows

Every table has rows and columns. You can add up to 5 rows in Free Table to break down the data. Since we are interested in the US traffic, we can add “Country” into rows and remove “City”. 

There are a few more options in this section that you can change. “Start row” lets you specify from which row you want to start. For instance, you can want to miss the first 5 rows and start from 6. 

You can also change the number of rows to show from 10 (default) to 500. If your data includes more rows, export the report as .CSV or Google Sheets and get all rows there.

If you use a few dimensions in rows, you can find “nested rows” helpful. It groups the rows of one dimension in one. For instance, you can see the US, all its cities, the UK, and all its cities, instead of UK and US cities mixed. 

2.5 Columns

You can also add columns to your report. In order to do that, you should drag and drop dimension from section 1.4 to section 2.5. The navigation also allows you to select from which column you want to start and how many of them you want to see. So if you are not interested to look at the first column value, you can set “start column group” to 2, and the first column will be removed from the visualisation.

In our report, we don’t need to use columns, but let’s add “device category” to get a more granular view. Since we didn’t import this dimension, we should import it first to our report (section 1.4)

2.6 Values

This section allows you to add metrics as values to the report. 

We have already imported the necessary metrics into the report; let’s now add a few of them into values: “Total users”, “Conversions”, “Transactions”, “Ecommerce revenue”.

Cell type allows you to change the display of the metrics in the table: bar chart, plain text or heatmap. I prefer to use “plan text”. 

2.7 Filters

Filters allow you to exclude some data from your report. We are interested to see only US desktop traffic. 

Therefore, I created two filters to show only relevant data.

Report part #3 – Report View

There are a few things left to discuss. The third part of the report is “Report View”. This window presents the final data after applying filters, segments, rows, columns, and other settings. 

3.1 Right-side menu – Plus icon

This icon allows you to create and include more reports in your exploration report.

3.2 Left-side menu – Undone, Re-do, Share

You can use the left-side menu to share a report with your peers. The share functionality allows you to share the report in read-only mode. You can also export your report in CSV, PDF and as an image.  Apart from that, you can undo or redo the latest changes you made. 

3.3 Report Navigation

When you click on the right button of your mouse, you can include or exclude selections from the report. Once you click on any of these options, GA4 creates the filter and applies it automatically.

You can see that only 375 users generated 2,083 conversions and 3 transactions. If you are interested in looking at the users’ profiles, you can select the right-mouse button and click on “View Users”. It will open the User Explorer report.  

If you want to build remarking campaigns on Google Ads, you can click on the right button of the mouse and select “create segment from selection”, after that, you can build the remarketing audience. 

However, so many conversions and so few transactions tells me that something is wrong here. After I looked at “Conversions” tab in GA4, I found that “pageviews” events were labeled as conversions. Therefore, there is no need to do that in our case. 

At the beginning of this section, our goal was to find Google CPC campaigns that acquire US desktop traffic. Below, you can see the screenshot that shows the relevant data.

GA4 Free Form limitations

As with every report in GA4 Explore, free form also has limitations. To use the report efficiently, you know them. 

• You can apply up to 4 segments. 
• You can use up to 5 dimensions in Free Form.
• You can display up to 2 dimensions as columns in Free Form report.
• Free form report can show up to 10 metrics.
• GA4 Free Form doesn’t show today’s data. 

Conclusions

GA4 Explore Free Form report allows you to conduct ad-host analyses and delve deeper into users’ behaviour. You can use many options to break down the data to the granular level you are interested in. As with every report in GA4 Explore, this report has limitations. Majority of them you can overcome using BigQuery integration.

Frequently Asked Questions