The year 2020, among other things, has brought to the world the long-awaited Google Analytics 4, which is now officially released and available worldwide. What are the key changes and how Google Analytics 4 differs from Universal Analytics? Who will benefit from the transition to the new data model and how to get started with Google Analytics? The new property type is explained by Kate Guzevataya, Head of Web Analytics at Promodo.
The new Google Analytics property was originally presented as App + Web, which presupposed combining data from web and mobile apps to ensure a more unified view of customer data. Let’s see why the new property type is so promising and what new features it brings to the users.
We’ll elaborate on each point separately.
In the standard web version of Google Analytics, everything was built around user sessions, that are an artificially brought indicator. The new Google Analytic is all built around events. This allows you to collect the same data across all devices and platforms, thus improving the reporting quality and providing you with a unified view of the user path.
Firebase Analytics is an analytics platform for accounting of mobile and web applications. Google Analytics 4 is essentially an analogue of Firebase with its interface and data accounting logic, as well as some additional functionality that Firebase may lack.
Some Machine Learning and NLP features were represented in the previous version of Google Analytics but were used very little, which is understandable as more of ML potential was to be added (and actually was included) in Google Analytics:
So, what does privacy mean in the context of Google Analytics 4:
The latest version of Universal Analytics already uses this library, but few people switched to it, as this library needs to be installed in the site code. Here at Promodo we see no need to rush with the gtag.js, as the standard Universal Analytics is installed via Google Tag Manager and doesn’t require any additional actions.
We would assume that in the nearest future Google will abandon Client ID to fully rely on internal device & browser identifiers, as well as a cross-platform identifier that is generated in CRM, i.e. User ID.
Actually, IP anonymisation was not tracked in the previous versions of Google Analytics either. The only difference is that in the new GA, there is no way to customise the analytics for tracking.
Integration with YouTube is considered the most advanced so far. Google is actively working to improve the quality of evaluations for YouTube campaigns, for example, making it possible to track view-through conversions. This will help to understand the following:
In the new version of Google Analytics, measurement of YouTube campaigns represents a more advanced system that allows to analyse statistics on YouTube within Google Analytics interface.
A deeper Google Ads integration allows creating audiences and running campaigns that attract new customers with more relevant and useful offers. And the most valuable is that the device the customers are using doesn’t matter.
Google Analytics 4 has direct free data export to Google BigQuery (a cloud-based database for storing, processing data and building various reports). Previously, the export feature was paid and provided only in GA 360, while in GA 4 it’s now free. Google BigQuery is good because it provides constant access to raw, non-aggregated data, which means you’ll be able to build various reports at any stage of project maturity.
One of the key points of the GA update is the ability to see the entire user journey that can start on the website and continue in the mobile application. To count real users (not the devices and browsers they used) who interact with your company, the new resource type uses 3 levels of identification:
User ID is the main authentication layer and one of the key figures in this update. It is the User ID that allows to combine information from devices and websites inside Google Analytics. The user ID, however, will have to be customised as it is not set up by default.
Implementing event-driven analytics means you can more accurately track the user’s journey from first touch to conversion and repeat orders. Moreover, if a user performs the same event on various devices, this data will merge into a single touchpoint. For example, if a customer adds an item to the shopping cart twice (on a smartphone and then on a laptop), the “Add to shopping cart” event will be counted once.
Previously, the results for the application and for the website were presented as separate users, which could be difficult to combine. Google Analytics 4 makes it easier and faster.
Google Analytics 4 has three key differences over the previous version:
Analytics is no longer built around sessions, but around events. Google suggests abandoning the artificially created concept of sessions. If you need session data, you can build it manually using raw data from Google BigQuery.
There are advanced data collection settings for the entire website and settings that change with each event.
GA 4 has built-in end-to-end user id reporting.
Universal Analytics contained numerous metrics, such as Page/Screen View, Events, Sessions, social, various Hit types, User ID, Client ID and the others. In the new resource type Google reduces all the metrics to the four key ones:
Google Analytics 4, in line with Firebase, provides three types of events and their parameters:
Recommended and custom events are implemented independently..
Custom Definitions are end-to-end dimensions and metrics that help you stay within Google Analytics 4 limits.
Previously, the “Add to cart” event had a separate script and an individual parameter for each value, while now they are united by a single event structure (product name, product cost, size, color, etc. – all of them are passed to parameters, as well as user properties).
In Google Analytics 4 there does not exist such concepts as category, action and event shortcut.
For existing customisations and collected data, these properties are mapped to custom event settings. You need to register the properties in GA 4 reports in order to see them. In order to see some additional properties transmitted with each event, you can select them in the interface.
Along with that, the page_view event in GA4 has preset parameters:
The page_view event is fired automatically if the “config” snippet of gtag.js is implemented.
Sessions are present in Google Analytics 4 reports, but the way they are counted differs from the one of Universal Analytics:
Currently, session duration in GA 4 can’t be configured.
In order to include custom dimensions and metrics in Google Analytics 4 reports, the latter must be transferred to a new resource type according to the rules of Google. In Google Analytics 4, there are analogues for hit-level and user-level parameters, but no equivalents exist for session-level parameters. Although, you can define them at the hit level.
To use custom product-level definitions, you must add them separately. This feature is still in development, and there are no eCommerce reports that would contain custom product-level definitions, thus it’s not yet clear how this will work.
Whereas previously in Google Analytics there were 4 levels of indicators focused on hits, users, sessions and products, now their equivalents are events and event parameters.
In Google Analytics 4 there appears a new feature called “User Properties”. These are definitions that correspond to a specific audience/user. For example, gender, city, new or returning customer etc.
Properties that concern specific users are applicable to their behaviour. Based on User Properties, audiences for personalising ads are formed.
Let’s see how the Traffic Sources report looks like in Google Analytics 4:
The “Events” report is visually represented in a different way:
Scatter chart shows which event is most popular when added to the cart (no such visualisations were available in the previous version)
In Google Analytics 4, there is no longer the “My Reports” menu. Instead, a promising “Analysis” appears, with its two tabs: “Analysis Center” and “Template Gallery”. In addition, the report types have been replaced by “Methods”.
If you have a set of events using which you can form a funnel, you can do this manually.
Note: first you need to set up the correct tracking, and only then generate reports, as shown in the pictures.
In the same report, you can create segments for any step in the funnel.
Another difference between Google Analytics and the previous version is that you no longer need to create goals manually, you just need to use the slider for the event that is being tracked to become a conversion.
In Google Analytics 4, you can add a new segment from the funnel steps.
To do this, select “Build an audience” and create the necessary condition (or do not change anything).
It’s worth to start implementing Google Analytics 4 right now provided:
Our opinion: the new resource type is definitely worth implementing for everyone. Moreover, the sooner you switch to GA 4, the faster you will begin to collect historical data, which means there will be more information that can be used for making decisions. Plus, the faster you get value from ML insights. New analytics will not interfere with the old one, as long as it can be used separately. But the fact that it will develop rapidly and eventually everyone will switch to it (as it was once with Universal Analytics) is a fact. One of the difficulties is that the data structure and logic of their collection are significantly different for GA 4 and Universal Analytics. Therefore, it will be rather problematic to combine the data of the two resource types.
You may face some problems implementing Google Analytics 4 in case:
And more cases to show that Google Analytics 4 is not a fit for you (at least yet):
Since we recommend using Universal Analytics in parallel with Google Analytics 4, we will explain how to switch to the new analytics without abandoning the old one.
The main update of the whole Google Analytics concept: in GA 4 everything is built around events, parameters of events and users, and not around sessions, as it was before.
The key feature of the App + Web functionality is cross-platform analytics between the website and the applications.
To configure a new GA4 resource, you can use the previously configured GA via gtag.js or GTM.
When setting up GA 4, a new WP resource is automatically created. And this is the moment that launches data collection. It’s impossible to migrate data from old WPs.
Google does not urge you to abandon the old Google Analytics and switch to the new one. They (and we at Promodo) recommend launching the new Google Analytics 4 in parallel and start collecting data into it. The source of historical data is still the standard GA.
There are flaws in the new GA 4. Moreover, not all features are available to users yet – the developers are gradually rolling these out.
There is no way to import costs from non-Google sources into Google Analytics 4 yet.
Data upload from GA 4 to Google Big Query can be configured for free. The export scheme is the same as in Firebase.
You can start customising GA 4 assets and collecting data. The earlier you set it up, the more historical data you will be able to collect.
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