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Decoding Universal Analytics vs. Google Analytics 4

Not sure what you should be tracking in Google Analytics 4 (GA4)? With Universal Analytics (UA) being sunset in 2023, it’s critical that digital marketers learn the differences between GA4 vs. Universal Analytics. 

Oct 28, 2022

8 m read

Universal Analytics turned 10 in October 2022. And while many web analysts cut their teeth on the platform, Google has decided it’s time to move on to what they believe is a better way to collect and analyze web data. While it launched in 2020, Google Analytics didn’t draw a large crowd, with only about 25% of users opting for the newer platform. Until Google announced UA was going away, that is. Now, if you want to access free web analytics from Google, you’ll need to make the switch to GA4 before they deprecate UA on July 1, 2023. (In fact, if you haven’t already installed GA4 on your site, I recommend you do so right now. Have questions? Check out this post.)

How To Get Ahead With GA4

Set up the latest Google Analytics and unlock its potential with this free guide.

There are plenty of differences between the two platforms, and I won’t cover them all here. Instead, I’ll touch upon the differences that will impact marketers the most. 

Let’s start at the beginning: How Google Analytics gathers data.

How Data Collection Differs in Universal Analytics & Google Analytics 4

Universal Analytics, also known as GA3, relies primarily on first-party cookies to learn more about who is visiting your website, how they got there, and what they do when they land there. 

Cookies, though, have become persona-non-grata as consumers (and governments) have grown more privacy-focused. Most web browsers have phased out third-party cookies, and Google plans to do so in 2024. Apple iOS 14 introduced App Tracking Transparency (ATT), which lets users opt-out of tracking. This led to 60% of iPhone and iPad users saying “no, thanks” to having their activity monitored. Therefore, while GA4 still uses a first-party cookie to collect web data, it also applies machine learning to help fill in the gaps and provide more robust data collection and modeling.

To track app data, GA4 uses an app-instance identifier.

Measurement Models in UA vs. GA4

Google created Universal Analytics to track only website data. However, the digital landscape has changed. Marketers, web admins, and digital teams need insight into their omnichannel presence. With GA4, these stakeholders can now see how both apps and websites are faring in one property. By combining data for the two in their interface, Google Analytics 4 allows for a more in-depth analysis of digital properties that wasn’t possible on the website-only UA.

To capture this data, GA4 relies on data streams that are then combined into a property. It’s recommended that you only have three data streams per property: one data stream for a website, one for an android app, and one for an iphone app. If you have multiple brands, it’s a good idea to create a property for each of them.

Universal Analytics Session-Based Data Model

Universal Analytics relies on a sessions-based model that requires GA to add a cookie to a user’s browser. In a sessions-based model, user actions are grouped together. A session may include a pageview, a particular goal, or a purchase, all of which are considered ‘hits.’ The session is ended after 30 minutes of inactivity.

Google Analytics 4 Events-Based Data Model & AI

GA4 uses an events-based model that still uses cookies but also integrates user-IDs, Google signals, and/or device IDs to allow for cross-device and cross-platform tracking. With event-based tracking, each action is tracked on its own. 

Event-based modeling allows you to gather more in-depth information about how users interact with your site. However, you can still view session data. GA4 also includes AI modeling to help fill in the gaps that cookies can’t fill. This is increasingly important as more users opt out of tracking and become more privacy focused.

Google believes the events-based model will allow users to customize and capture more of the data they need to measure the effectiveness of their websites and apps.

UA vs. GA4: Identity Spaces

Identity spaces is the name Google uses for the identifiers it tracks: user-ID, Google signals, device ID, and modeling.

UA primarily uses device IDs to track users, though it can also use Google signals from individuals signed into their Google accounts. While UA allows sites to track their own user IDs, the data isn’t integrated and must be viewed and analyzed separately. This separation of data also severely limits cross-device tracking.

GA4, on the other hand, integrates the data it collects from your user IDs, Google signals, and device IDs to paint a clearer picture of what’s happening on your website and apps. Integration of the identity spaces means GA4 users can more easily de-duplicate their data and gain better insights into the customer journey across their Google Analytics property. 

When switching from UA to GA4, it may seem like you have fewer users. However, further research may show that GA4’s cross-device tracking is just presenting more accurate data thanks to its integrated tracking.

UA vs. GA4: Metrics

Google Analytics 4 is its own beast, but seeing how it relates to UA can provide context for understanding the different metrics so you can more easily integrate it into your workflows. Here are the important metrics in GA4 and how they relate to those used in UA.

User Metrics in Google Analytics

User metrics in universal analytics vs GA4

While UA featured total users and new users, GA4 tracks total users, new users, and active users.

In UA, new users are defined as users who have not previously interacted with your website. In GA4, new users are active users that haven’t had a previous interaction with your website.

Active users are those who have triggered the first_visit event or engagement_time_msec parameter or who have an engaged session.

The primary user metric in UA is total users, while active users is the primary user metric in GA4. That means when you look at a report in GA4, ‘Users’ refers to active users, not total users.

If you see an arrow next to ‘Users’ in a GA4 report, you can click it to toggle between user metrics.

Pageviews vs. Views

pageviews in GA4

UA has two pageview metrics: Pageview and unique pageview, while GA4 focuses only on pageview

A pageview is what it sounds like. When a site visitor views one of your pages, Google Analytics counts it as a distinct pageview. The pageview metric (shown as ‘Views’) is similar in both platforms. However, if you include an app in your GA4 property, it will also include screen views

The unique pageview metric, which does not count repeated viewings of the same page, is not available in GA4. 

Bounce Rate – Session – Engaged Session

engagement in GA4 vs Universal Analytics

In UA, the bounce rate is the percentage of sessions where a visitor lands on a page and then leaves without taking further action. They may stay on the page for a while before navigating away from your page, but their inaction means Universal Analytics counts them as a bounce. 

In GA4, bounce rate is the percentage of sessions that aren’t engaged sessions. This metric isn’t reported, but you can ascertain the percentage by subtracting your engaged session percentage from 100.

An engaged session is one where a site visitor stays on a page for more than ten seconds and triggers at least one conversion event or two or more page view events. Any session that doesn’t meet these requirements will be calculated in the bounce rate metric.

Your bounce rate in Universal Analytics will likely not be equivalent to your bounce rate in Google Analytics 4. Because scroll is measured as an engagement event, a user reading and scrolling through an entire blog post before clicking away, for example, will be counted as an engaged session. In Universal Analytics, this same event would be counted as a bounce.

This update to the bounce rate metric will help users better understand how site visitors are interacting with pages. It also illustrates that a page view without a click still provides value. In fact, rather than focusing on bounce rate, which isn’t clearly laid out in GA4, switch your gaze to engage users and make sure your content is capturing1your visitors’ attention.

Sessions in UA vs. GA4

I’ve already mentioned engaged sessions above, but I wanted to touch on them a bit further since it’s such a pivotal part of Universal Analytics.

UA is a sessions-based model. All of its data is reported as sessions and many people have used sessions as a measure of website traffic. On this platform, a session is a group of actions (hits) a user takes on your website within a particular time frame. 

Google Analytics 4 views sessions a bit differently and does not display them as prominently as UA does. In GA4, a session is a group of events recorded for the same user.

I know these definitions sound extremely similar. However, since events in GA4 are not equivalent to hits in UA, these two metrics will differ between platforms. Rather than trying to find how they relate to each other, it’s best to start conceptualizing how GA4 presents events and create new benchmarks for your analytics.

Event Count – Conversions – Goals

conversions in GA4

One of the biggest differences in the new Google Analytics is the move to an events-based model. This is most apparent when looking at events and conversions.

Universal Analytics users will be familiar with GA Goals. Once set up, these goals allow users to track conversions and particular user actions like form fills, downloads, and purchases. 

In GA4, events are the bedrock of the platform. User interactions are measured as events, and there are no Google Analytics goals. Instead, users will need to set up conversion events with Google Tag Manager or a Google tag to track the events that matter most to their businesses.

UA also uses events, however, UA events have a Category, Action, and Label in addition to a hit type. For example, a pageview is a hit type. With GA4, all of those hit types are just events. 

Automatic Event Collection

When GA4 is installed, it automatically collects events. If your desired events aren’t on this list of automatically created events, you can create them by following these steps.

These events will not have revenue associated with them and will not be considered conversions. To start tracking conversion and ecommerce transactions, mark specific events as conversions events.

You can also turn on enhanced measurement to start tracking different engagement metrics on your site, like video engagement and file downloads.

Setting up your events and conversion events properly is critical for accurate tracking. Discuss your needs with your data analytics team to establish a list of necessary events and conversions. Then, compare your list against Google’s list of automatically generated events. 

If you believe you need to add events, create a naming convention that’s distinct from Google’s naming convention to avoid confusion. Pinpoint the parameters that matter most to you and verify that the event will measure precisely what you want it to.

Because conversions will only be counted once you turn an event into a conversion event, you will not have conversion data after implementing GA4. Set up your conversions as soon as possible to start collecting this data for historical analysis.

TIP: To protect your data, consider experimenting in a sandbox environment first before rolling out changes to your GA4.

Event Parameters in GA4

An event parameter is metadata you can ask Google to collect. 

Each event already collects certain parameters, but you can edit those events by adding or modifying up to 25 parameters.

In this way, event parameters allow you to customize the data that is collected for a particular event. For example, you can have Google collect author data for the page-scroll event to determine whether posts by particular authors have more engagement.

Google offers three ways to add event parameters. To make sure that adding parameters doesn’t impact data collection, I recommend making a copy of the event you want to modify or sending a custom event to capture just the additional information you want. That way, the original event will continue to collect data as intended and you reduce the chance of errors. 

Custom Dimensions

If you modify events, you’ll need to create custom dimensions and possibly custom metrics, as well. 

There are two types of custom dimensions:

  1. Event-scoped — these track information about particular events.
  2. User-scoped — these track information about users.

You can learn how to create custom dimensions and metrics here.

Need Help Making the Switch? 

Configuring and navigating a new analytics platform can be confusing. At Victorious, we know that being able to measure the effects of your SEO strategy is crucial for success. If you need help implementing a strategy and measuring your SEO performance, schedule a free SEO consultation.

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