Google Analytics 4: How to migrate from Universal Analytics & implement GA4?
Universal Analytics is a variation of Google Analytics which has established a new benchmark for the collection and organisation of user data from websites and apps. Universal Analytics was introduced in 2012, and since then it has been a go-to tool for marketers to measure and monitor the acquisition and engagement behaviour of website visitors and app users. It worked using a unique tracking code for web pages that could effectively track and evaluate user activity. Nevertheless, it had its own drawbacks and failures, and it was reported in 2022 that Google Analytics 4 would replace Universal Analytics on July 1, 2023.
Universal Analytics was designed for a generation that was fixed in the desktop web, separate sessions, and much more easily viewable cookie data. This system of measuring is rapidly becoming outdated. However, Google Analytics 4 works across channels, does not rely just on cookies and provides user-centric monitoring through an event-based data architecture.
What is Google Analytics 4?
Google Analytics 4 marks the most recent release of Google Analytics. This is a completely new era of web analytics which will enable marketers to monitor vital visitor usage statistics rather than merely measure traffic.
Google Analytics 4’s key goal is to provide more data across the customer journey’s complete lifespan. In other words, when a client is obtained, additional data is accessible, such as their degree of interaction, monetization, and retention. Despite these data points, GA4 is concerned with customer privacy and is fully compliant with the new implementations in online privacy policies. With all of these new capabilities and additions, GA4 is proving to be an innovative tool that gives unrivalled insights.
How is GA4 different from Universal Analytics?
Google Analytics 4 provides a more holistic approach, using artificial intelligence and machine learning to deliver more knowledge of consumer behaviour across various platforms and devices. However, Universal Analytics concentrated on recording single visitor engagements on a website. Let’s look at some of the significant distinctions between UA and GA4.
1. Distinct Measurement Models –
The primary distinction between UA and Google Analytics 4 is the measuring methodology that they employ.
Universal Analytics employs a session and page view-based measuring approach. A session is a collection of visitor engagements (hits) with a site that occur over a specific time period. Several page views, actions, and eCommerce purchases can occur throughout the same session.
Google Analytics 4, on the other hand, employs a measuring methodology that relies on parameters & events. The idea is that any engagement can be recorded as an event. This is why all UA hit types are converted to GA4 events. What might be perplexing is that with Universal Analytics an event has its own hit type, category, activity, and label. These classifications are not present in GA4. Each hit is an event, & events can (but are not required to) include custom parameters.
2. Website and App Data Tracking –
The ability to monitor webpage and app data within the same property is one of the most awaited Google Analytics 4 features that were not accessible in UA. GA4 uses the same measurement paradigm as Google Analytics Firebase (which is used for mobile apps), in which all interactions are recorded as events. This new uniform data format between a webpage & a mobile app implies that combining data across them will be considerably easier.
3. GA4 session calculations vs. universal analytics –
Another distinction between UA and GA4 that may be seen when comparing numbers between the two platforms is different session values.
A session in UA reflects the duration for which a customer is actively engaged in your site. On the other hand, in GA4 the ‘session start’ event produces a session ID to which every future event throughout the session is connected.
In both UA and GA4, a session stops upon 30 minutes of inactivity. However, unlike Universal Analytics, sessions in Google Analytics 4 may now continue past midnight and are not impacted by meeting new campaign settings.
4. Free BigQuery Connectivity –
BigQuery allows for the rapid querying of very large and complicated data collections. Due to sampling, creating complicated segments in GA causes a slew of issues while evaluating data. Big Query extracts data from GA and allows you to explore it without the need for sampling.
BigQuery exports are now accessible to all properties with Google Analytics 4 (for UA, this was available only for Analytics 360 properties). This means you can transmit raw events to BigQuery, which will subsequently be evaluated using SQL.
5. Google Tag Manager has become more vital than ever –
You could utilise Universal Analytics without Google Tag Manager if you were using simpler features. You could, for example, construct destination page conversions directly in UA.
It’s no longer feasible with Google Analytics 4. Because all objectives are event-based, knowing Google Tag Manager is more essential than ever. Knowing and working with GTM is also useful for complex data collection, such as developing customized events and dimensions.
Why is Google deprecating Universal Analytics?
Since its inception in 2012, UA has been Google’s premier analytics tool. Since then, UA has gained a plethora of additional features and capabilities. Meanwhile, the way companies and customers engage in the digital realm has evolved significantly, creating issues for measurement and analytics.
A. Companies frequently have more than just a website presence; they also have apps and maybe other linked platforms.
B. Purchase or conversion paths have become more multi-screen and multi-device than before.
C. Customers are increasingly concerned about their privacy than ever before, and data modelling is often required to “fill in” for information that is unable to be acquired.
To address these difficulties, Google determined that a fresh method to the Google Analytics platform was necessary, rather than continuing gradual progress in UA. As a result, GA4 is the first “all-new” Google Analytics service in a decade, and it is purpose-built to assist marketers in overcoming the complicated issues stated above.
“Universal Analytics was built for a generation of online measurement that was anchored in the desktop web, independent sessions and more easily observable data from cookies. This measurement methodology is quickly becoming obsolete.“
According to Google, the model on which Universal Analytics is based has become outmoded.
How to quickly migrate from UA to GA4?
Migration to Google Analytics n4 is not as easy as flipping a switch. There is no better opportunity than the present to begin preparing, converting, or moving any UA property you use to GA4. All conventional UA assets, as well as 360 UA, are expected to disable processing new hits on July 1, 2023. Although relocating your digital assets will take careful preparation, we will make the process a little easier for you in this section!
Step 1 – Examine your existing Google Analytics configuration:
The first thing to keep in mind on the UA to Google Analytics 4 migration is to conduct an audit in order to have a better knowledge of your current UA account. Make things simpler for yourself by just migrating what you require. If you’ve been utilizing the UA for a while, go over your customized events and make sure everything is still necessary. After auditing, export this data from your UA account.
Step 2 – Setup your GA4 account as follows:
Because views are not accessible in GA4, you need to prepare your account structure ahead of time. You should select the number of properties and streams to put up based on your business. GA4 enables you to capture website and app data together within a single property, which will involve careful preparation and an efficient approach on your part.
Step 3 – Set up a new Google Analytics 4 asset:
Integrate your current data streams by creating a new Google Analytics 4 property. We recommend utilizing Google Tag Manager to apply your GA4 tracking code—these two technologies are meant to function in harmony. Other platforms to integrate with your GA4 account are Google Ads and Google BigQuery.
Step 4 – Control your user permissions:
It is critical to determine who is authorised to access your Analytics account. You should be aware of every user’s role and the kind of permissions that should be provided to them. By setting specific user permissions from the start, you can guarantee that your project runs well.
Step 5 – Configure your Filters or Conversions:
You should make a list of your UA objectives and decide whether they should be replicated as conversions in your Google Analytics 4 asset. One of the most significant GA4 benefits is the increasing number of conversions. You may now set approximately 30 conversions for each GA4 property.
Since views are not accessible in GA4, if you have specified a number of objectives across distinct views, you need to develop a new measurement method. Also, smart objectives are lacking in GA4, although other goal types can be recreated.
Step 6 – Check to see what customized metrics & dimensions should be configured:
Whenever it concerns custom dimension migration, the concept of scope must be considered. The scope specifies which events are covered by a certain dimension.
In UA, there are four scope levels: session, user, product, and hit. Customized dimensions in GA4, on the other hand, should define either your user or your event. Remember to register any custom parameters you develop for your GA4 events as custom metrics or dimensions. You can get innovative by utilizing the event model’s full capability.
Step 7 – Prepare your team:
Inform your colleagues about the modifications in Google Analytics 4. Pay attention to your team’s reporting requirements. Try creating new Exploration & dashboards that only display the data that is relevant to them.
How to Create Custom Events For GA4 Conversions?
Another intriguing new feature of Google Analytics 4 is the possibility to create events straight from the User Interface. With GA4, you may build a custom event to track data on your website that is useful to your business but is not automatically recorded. If you don’t want to develop custom events in GA4, you may utilize Google Tag Manager instead.
Again, this feature was not available within Google Analytics before, and it’s a major step forward in customizing your parameter & event data to get it just as you want it. It is also an excellent approach to developing more targeted conversion events!
Let’s walk through the steps on how you can create such custom events and conversions in Google Analytics 4.
Step 1: Create an Event.
Go to ‘Configure’ once you’ve signed in to Google Analytics and are going through the reports. On the upper right corner, click the ‘Create Event’ button. If the property has multiple data streams, you have to pick the data source you would like to utilise. The Custom Events page will then appear, where you have to click on the “Create” button.
Step 2: Create your new event.
You must first give this new event a unique name. This should be brief and adhere to Google’s suggested naming conventions (such as sign-up, page view, and so on). Following that, you must specify the criteria that will cause your new event to occur. Then, specify the event from which you want to generate your new event.
After that, you must add an extra condition to identify this event as distinct from others. Lastly, you must select your parameter setting. If you just want to utilize the parameters that were already included in the original event, select the “Copy parameters from source event” option. You can also specify your own/extra parameters to be utilized for the new event. You can just click on the “save” button after all these steps are done.
Step 3: Run your new event through Realtime.
The final step is to ensure that the new event is triggering as expected. To do so, go to your website and browse the page where you have set up the new event. Your new event should now be firing. Just view the Realtime data in GA4 to validate that it does indeed work.
Step 4: Delegate the new event as a Conversion.
One of the most tempting aspects of the possibility of simply developing new events in GA4 is the ability to label such events as conversions. There are two approaches to this. Either wait a day for your events table to refresh with the current event name, then turn it on to indicate it as a conversion in the Events report. If you don’t want to wait, go to the “Conversions” report and make it from there. Choose “New Conversion Event” from the drop-down menu.
Then label the new conversion event just as you did when you created it. Save to create a new conversion event.
How to Create Custom Reports in Google Analytics 4?
If you want to handle your data more specifically by creating your own customized reports, you may do so on GA4. Now, let’s take a deeper look at the custom reports interface’s components. It is divided into three sections:
1. Variables: segments, dimensions, and metrics
To begin, choose the data that will be included in the report. At the top-left section of the interface, you can alter the ‘title’ of the analysis. To change the ‘date range’, select the timestamp in the upper-left corner and pick the range you require. If you wish to compare how various groups of customers or visitors behave, enter those segments in the ‘Segments’ section. To do so, select the Plus icon. Next, you may either build a custom section or choose one that has been recommended to you.
Dimensions in Google Analytics are parameters or properties of a user or event. Generally, these are properties that characterise an entity. However, metrics assist us in measuring performance.
To begin creating your report, enter the metrics or dimensions into the Variables column. You can pick the dimension/metrics by just clicking on the Plus symbol. When you’ve chosen the desired dimension/metric, click the Import option in the upper-right corner. To summarize, the Variables tab is in charge of data entry. Some segments/dimensions must fit into that column if they are to be used.
2. Tab Settings –
In this section, you may specify how the report should look.
a. To begin, you’ll find a drop-down list from which you pick “Free form.”
b. Next, you’ll discover the visualization area, where you may choose from the following options:
>> table
>> donut chart
>> line chart
>> scatterplot
>> bar chart
>> geo map
The customization choices accessible in that same column are affected by the visualization approach used.
c. Drag segments from the Variables column into the Tab Settings section to add them. Instead, you can also double-click on the Variables tab to add them automatically. If you have at least a single segment in the comparisons area, a new field, ‘Pivot’, will emerge. This field is in charge of segment positioning in the chart and has four options: First & last row and first & last column.
d. Under the Values section, drag the parameters that you wish to display as report columns. This section can contain up to ten metrics in a single report.
e. There are several types of cells to select from:
>> In each metric cell, bar charts display horizontal bar graphs depending on their values and the proportion to certain other rows within that column itself.
>> All cells are displayed in plain text, with no further aesthetic modifications.
>> Heat maps highlight cells that have greater values than other rows within the exact dimension column.
6. Filters help you swiftly limit the amount of information you’re working with. Finally, select the placeholder & choose the metrics that you want.
3. Output –
The report will display once you have configured all of the appropriate parameters in the Variables & Tab Settings columns. Each tab can employ a different analytic approach (free form, funnel investigation, and so on), so create additional tabs as required. By selecting the Triangle button next to a tab name, you may also duplicate and delete it:
Right-click a cell to reveal more options:
>> include selection
>> exclude selection
>> create segment from selection
>> view users (in User Explorer reports)
If you still want to get better clarity on how to switch to Google Analytics 4, talk to a professional and make this migration smoother for your company!