If you are familiar with Google Analytics, you have most likely heard of the introduction of Google Analytics 4 (previously known as App + Web Property), and the necessity to soon migrate your property to accommodate for the change.
Google Analytics 4 (GA4) is a new type of analytics service gradually introduced by Google since November 2019, and made the default when a new Google Analytics property is created, starting October 2020. Google Analytics 4 is built on the same platform as the App + Web Property, allowing property owners to track users across apps, software, and websites.
Based on events rather than pageviews, GA4 offers far more flexibility compared to previous versions of Google Analytics. This includes no volume limits for data collection, cross-platform user identification, advanced analysis capability (including custom funnels), and many other features which we will explore in more detail. One such feature is the turn-key ability to integrate with Google BigQuery.
Table of Contents
New Version of the Side Menu
The Google Analytics 4 has retained its side navigation bar (navbar), with few minor changes. The new side menu now has only 4 high-level menu items. They are presented as icons which expand to reveal the menu names when the user hovers over them. The four high-level menu items include:
In addition to these changes, GA4 has expandable second-level menu items that reveal 2 additional levels of menus. Besides the already familiar menu items found in the previous versions of Google Analytics, users can now discover others such as reports snapshot, engagement, monetization, retention, library, custom definitions, and debug view.
What Does Google Analytics 4 Do Better Than Universal Analytics?
Although there are many differences between Google Analytics 4 and Universal Analytics, some of the most important ones can be categorized as differences in data tracking, data collection, reporting, and the possibility to integrate Google BigQuery. We will explore each of these in more detail, and answer the question why Google Analytics 4 is better than Universal Analytics.
The big difference between GA4 and UA is the process for creating segments
The biggest and the most important change introduced in Google Analytics 4 is the data tracking model.
Previously, Universal Analytics was relying on hits to track data. A hit was described as the interaction between the user and the website in question, and was triggered by the specific behavior of a user. Universal Analytics had a rigid structure of different hit types such as pageview hit, event hit, ecommerce hit, social interactions hit, screen hit (for apps), and others.
On the other hand, Google Analytics 4 has introduced an event model, which is far more flexible, descriptive, and able to provide all sorts of data for analytical purposes. These events fall into four main categories, including:
- Automatically collected events
- Enhanced measurement events
- Recommended events
- Custom events
Let’s explore each of these event categories in more detail, and see how they enable you to track specific events on your website.
Automatically Collected Events
This category of events includes some of the most important metrics you need, which is why Google Analytics 4 collects them automatically. Users are not required to activate anything in order to start collecting data for these events.
Some of the examples of automatically collected events include:
- ad_click – triggered when a user clicks an ad
- first_visit – triggered when a user visits a website or launches an Android app for the first time
- session_start – triggered when a user engages the app or website
If you would like to explore automatically collected events even further you can visit this section of the Analytics Help page.
Enhanced Measurement Events
If the automatically collected events do not cover all of your data collecting requirements, Google Analytics 4 enables you to turn on an extra set of automatically collected events called Enhanced Measurement. This set of measurements allows property owners to track interactions users have with the content.
Some of the examples of enhanced measurement events include:
- video_start – triggered when a video starts playing
- file_download – triggered when a user clicks a link leading to a file
A full list of the enhanced measurement events and the instructions on how to turn them on can be found on the Analytics Help page, under enhanced measurement events.
Recommended events fall into the category of events which are not automatically collected by GA4. This is because these events require additional context to be meaningful.
As the name suggests, these events are recommended, however when collected on a website or mobile app, they help measure additional features and behaviors as well as generate more useful reports. Recommended events fall into several categories such as events for all properties, events for online sales, events for games, and others.
Some of the examples of recommended events include:
- spend_virtual_currency – triggered when a user spends virtual currency (coins, gems, tokens, etc.)
- generate_lead – triggered when a user submits a form or a request for information
- level_start – triggered when a user starts a new level in the game
A full list of the recommended events and the instructions on how to turn them on can be found on the Analytics Help page, recommended events.
To manage events, in the left sidebar, go to:
- Create Event
If you have exhausted all other options and need to track specific events that can not be found in the above-mentioned categories, Google Analytics 4 allows you to create your own custom events.
This advanced feature requires some programming skill, as you will need to design and write custom code to implement the custom event you want to track. It is highly recommended that you consult Google’s developer’s documentation when writing code to create custom events.
Another important change introduced by Google Analytics 4 touches on data tracking processes. Data tracking allows website/app owners to easily track and measure website’s traffic and conversion goals, which leads to smart business decisions.
With the introduction of Google Analytics 4, previously used views are now replaced with data streams. But what is the difference between views and data streams?
- With Universal Analytics, each website or app would have been an individual property. Once the data is collected at the property level, views allow website owners to see and report on the data in various ways.
- With Google Analytics 4, a Data Stream can be a website, an iOS app, or an Android app. Data is now collected at the stream level. Additionally, changes to data collection can happen within the individual stream, and property owners can add multiple data streams to a property in order to see cross-domain traffic.
For example, a single property can have multiple streams such as a website (even if this includes several domains), iOS, and Android, and data can be collected from each of them.
|Stream Name||Active Users|
At the moment Google Analytics 4 properties are limited to 50 custom dimensions and 50 custom metrics (which is a huge increase from the standard Google Analytics). Users can also have 25 registered user properties in a single GA4 property.
The best way to differentiate between Google Analytics 4 property and Universal Analytics property is to look at the Tracking ID.
GA4 properties use a Measurement ID, which starts with a capital letter G and is followed by a hyphen and 10 characters (mix between capital letters and numbers). For example:
On the other hand, Universal Analytics properties use a Tracking ID instead of a Measurement ID. The Tracking ID starts with the capital letters UA, followed by a hyphen, a 7 digit combination, another hyphen, and another number, indicating a specific property in the user’s account. For example:
In order to check your Measurement ID (in case you are using GA4), go to your Google Analytics page, press Admin » Property » Data Streams. The Measurement ID will be located in the stream details after the Stream URL and Stream Name.
Google Analytics 4 Reporting
Once Google Analytics 4 data streams are set up and working properly, users can rely on GA4 reporting capabilities to analyze the gathered data. First thing most users will do is access standard reports. These reports provide turn-key solutions for different figures and grant users an overview of the data in a more visually appealing manner than its predecessors.
Standard reports come into several sub categories including:
Although most of these are self explanatory categories, Google Analytics 4 also contains new features/reports users might want to explore.
The Engagement report is a new addition to the GA4, and has replaced the previously used bounce rate. The engagement metrics are essentially the different side of the same coin. Seemingly the complete opposite of the bounce rate, the engagement metrics serve the same purpose, to provide website users with the overview of the user’s interactions with the page. Google Analytics 4 counts the engagement metrics if a user fulfills at least one of the following:
- Actively engages with the website or an app for at least 10 seconds
- Triggers a conversion even such as newsletter subscription
- Triggers at least two screens or pageviews
Moreover, Monetization report is meant for an e-commerce business. It is a section that allows users to assess how the company is performing financially, as visualization options allow for a detailed data analysis. For instance, users can see how each individual product category is performing compared to other product categories, notice trends in the customer experience and behavior, and learn about other aspects of the online store.
The more experienced users that are not satisfied with the standard reports, can also rely on the Analysis Hub feature to monitor other aspects of the business such as:
- Funnel analysis (a detailed analysis of both open and closed funnels)
- Path analysis (allowing users to discover the most common path users take from a starting point to an ending point which property owners can freely specify)
- Exploration report (providing heat map analysis for property owners)
- Segment overlap (providing the analysis of relationship between the different segments, for example users aged 20-25 years and android users)
- User explorer report (providing analysis of data entries per individual user)
BigQuery Integration and Why It Matters
As previously mentioned, one of the key features of Google Analytics 4 is its ability to easily integrate with BigQuery.
Google BigQuery is a data warehouse, fully managed by Google. It has a capability to analyze terabytes of data in seconds and find insights in the user data using simple SQL queries. This means that users can request data analysis from their Google Analytics 4 account, without having to rely on samples that usually provide inaccurate data.
The GA4 + BigQuery integration create new opportunities for GA4 users including:
- Uploading raw event data directly into a data warehouse, running unsampled data analysis, predictive analytics, machine learning models, and other
- A new streaming export taking seconds and providing real-time reports, as opposed to the current export for Google Analytics 360 that is updated every 10-15 minutes
- A possibility to choose where to store data in order to comply with the data governance policies
The export of data also works with the dedicated BigQuery sandbox, which allows users to get started for free, and assess if the BigQuery integration is for them.
Google Analytics 4 vs Universal Analytics
Although we have already described many differences between Google Analytics 4 vs Universal Analytics, the following overview will show the key differences between them and provide users with even deeper insights as to why Google is switching to GA4.
Let’s start with data limits. Universal Analytics had a 10 million hits per property data limit, which is now completely removed, and with Google Analytics 4 you receive a free, unlimited data collection.
When it comes to sampling, Universal Analytics used sampling with over 500,000 sessions, which was problematic because it had a tendency to give a bias and inaccurate data results. On the other hand Google Analytics 4 offers Standard Reports with no sampling and up to 10 million events in advanced view.
As previously mentioned, BigQuery integration is a big change, as Google Analytics 4 can now implement a turnkey BigQuery integration, something that was only possible with Google Analytics 360 before.
Furthermore, advanced analytics UI was not available in Universal Analytics also, which is now available and easy to use in Google Analytics 4.
Finally, the only segment in which Universal analytics is temporarily better than GA4, is integration with other tools. For example, UA can integrate with Ads, Search Console, Optimize, and others, while GA4 can currently integrate only with Google Ads. However, please note that this will change quickly and surpass the capabilities of UA.
How To Set Up Google Analytics 4 for Different Platforms?
If we sparked your interest so far, and you wish to migrate your property to GA4 before Universal Analytics becomes unavailable, we’ll help you do so for some of the most popular platforms.
How To Set Up GA4 for WordPress
If you are using WordPress to manage your website, you can follow several simple steps to set up your Google Analytics 4 Account.
Step 1: Create a new account
Head over to your google analytics account or create one from scratch by pressing the “Start Measuring” button near the top of the page.
All you have to do is enter the desired account name, and click the “Next” button.
Step 2: Create a new property
Next, select a blue “Create Property” button under the “Admin” tab, and a new window will appear. Here you can add all the relevant property information needed, including property name, time zone, and currency.
Step 3: Create a data stream
The next step is to create a data stream. Since you’re setting this up for a WordPress website, click the Web button. Follow this up by filling in your website’s URL and name, then click Create stream.
Step 4: Copy the Global Site Tag
Head over to the Web Stream Details tab, and select Global Site Tag under Tagging Instruction.
Copy the entire code that appears once you open the Global Site Tag category, making sure to include every bit of the information.
If done correctly, the code you copied should look like the example provided above.
Step 5: Paste the code in your WordPress Website
Head over to your wordpress account, select appearances > Theme Editor. A submenu on the right side of the screen will appear. Select Theme Header menu option, and the header code will appear.
Paste your google analytics code in the head section, right between the last line of code, and the head closing tag (head closing tag looks like this: </head>). And you are done. Your WordPress website will now automatically track the metrics for you.
How To Set Up GA4 for Shopify
In order to set up your Google Analytics 4 for Shopify, please repeat steps 1 to 4, from the previous section (How to set up GA4 for WordPress). Once you have your code copied and ready to go, head over to your Shopify account.
Step 5: Add the code to your Shopify Page
Just like in the previous example, you have to add the code into your website’s head tag. To do so, go to the “Online Store” section, select “Themes”, and edit the theme.liquid file. Locate the head tag (<head>) and paste the code right before the head closing tag (</head>).
How To Set Up GA4 for Google Tag Manager
In order to set up your Google Analytics 4 for Google Tag Manager, please repeat steps 1 to 4, from the first section (How to set up GA4 for WordPress). Once you have your code copied, head over to your Google Tag Manager account.
Step 5: Create a New Tag
Find “Add a new tag” under the “Workspace” tab > “Tags”, or simply click the same button on the “New Tag” card in the Dashboard.
Once selected, a new window will pop up, allowing you to name your new tag, set up the tag configuration, and select the triggering events.
After naming your tag, press the pen icon in the top right corner of the Tag Configuration card, and select Google Analytics: GA4 Configuration.
Once selected, a few new options will appear. Fill in the measurement ID by copying the info from your Google Analytics account. You can leave the remaining options unchanged.
Finally, head over to the Triggering card below, press the pen icon, and choose a trigger such as All Pages shown in the example above.
Step 6: Submit the tag
Go back to your Google Tag Manager dashboard. In the top right corner you will find the “Preview” and the “Submit” buttons. Press the “Submit” button to make your new tag live on your website. If you have already pasted the code in the head section of your website, you can now freely remove it.
Can I Connect Google Search Console With GA4?
At the time of writing, integrating Google Analytics 4 with the Google Search Console is not possible. However, we would not exclude this possibility entirely, as Google will most likely modify and improve GA4 as time goes on, just like they did with Universal Analytics.
What Happens to My Historical Data in Universal Analytics?
If you are still using Universal Analytics, you are probably wondering what will happen with your historical data and the future data collection after July 1st, 2023. According to Google, UA property will no longer process new hits, which means that as of July 2nd, 2023 no new data will be collected.
Although Universal Analytics will no longer gather new data from users, you will still be able to access the historical data for your property for at least additional six months. However, after this period your data will be permanently deleted.
Google has not yet disclosed a definitive date when the Universal Analytics data will be deleted, but it is advisable to handle all your data as soon as possible.
Why Is Universal Analytics Being Deprecated?
Although Universal Analytics was a powerful tool, with numerous features added since its original launch in 2012, the way companies, brands, and users interact with each other has changed over the years.
Companies no longer rely solely on their website, but use multiple applications and platforms to implement their marketing strategies and reach their potential customers. This has created some challenges for data collection and analysis, and in order to provide a full picture of user/customer engagement, Google had to come up with another solution.
Furthermore, the path to purchase or conversion has now become multi-screen and collection of data across multiple devices is necessary. Users are becoming increasingly privacy-aware nowadays, and data modeling is sometimes needed to “fill in” for data that can no longer be collected.
Taking everything into consideration, Google decided that further improvement of Universal Analytics would not resolve these issues and that a new approach was necessary. The result was previously described Google Analytics 4, with all its built-in features.