Google Analytics Definitions: GA4 Defined in 2023
There is a lot going on with Google Analytics. This is even more true with GA4 which introduces some new terms. So let’s jump in to this list of Google Analytics definitions and get rolling!
An audience is a distinct group of visitors on a website (or app). It could be an audience of visitors who have been to the site before. It could be an audience of people who live in a certain country. Or it could be an audience of people who have completed a key goal (a “conversion”) on the website.
There are multiple ways to create audiences in GA4. They can be used for reporting and analysis or for remarketing in Google Ads (or both). Here’s a video explainer of GA4 audiences if you want more.
Google Analytics can fire an event every time someone new satisfies your audience conditions and enters your audience? It’s true! This is called an “Audience trigger event” and it can be very helpful for audience management, conversion tracking, and more.
This video is all about audience triggers and shows how to create an audience trigger event.
Attribution refers to how “credit” is assigned to traffic sources for various conversion actions. For example, let’s say you have a B2B company and the primary goal of your website is to generate leads through a contact form. Let’s see this situation takes place:
A visitor first comes to your website through Google organic search. They leave before converting. Then, they come back to your site a second time through a Facebook advertisement. They leave before converting. They come back again to your site a third time through Google organic search (again) and more research. But they leave once again before converting. Finally, they come back to your site a fourth time through a Google search ad. On this fourth visit, they fill out your contact form. They have converted! But how do you assign the “credit” (aka, the attribution) for that conversion?
How much goes to Google organic search? How much goes to Facebook Ads? How much goes to Google Ads? The answer will depend based on what specific “attribution model” you are using in your analytics set up. We’ll touch on Attribution and GA4 Advertising reports in greater detail in Module 3.
One of the benefits of GA4 is supposedly the free integration with Google BigQuery. In the days of Universal Analytics, this was only available with paid GA 360 accounts.
Using the BigQuery integration requires creating a Google Cloud account (that’s free) and a project for BigQuery (also free). Here’s how to set up the GA4 and BigQuery integration if you want to follow along in your own GA4 account.
A bounce is a visit to your website where your visitor likely didn’t find what they were looking for and left the site prior to converting. The bounce “rate” is the percentage of such visits that take place on your site relative to your overall visits. A low bounce rate can be representative of a site that offers a helpful user experience, while a higher bounce rate can be indicative of potential user experience issues.
Google Analytics 4 calculates bounce rate differently than in UA. We will cover this in greater detail in Module 2.
A key action that you track directly related to how your website makes your business money or otherwise supports a key organizational goal. In Google Analytics 4 we can create conversions by marking certain events to be counted as conversions. This makes sense for the most important events that we track.
Conversion Counting Method
In Google Analytics 4 conversions can be counted in two different ways. They can either be counted “once per event” or “once per session” as you can see below.
Once per session is the way that conversions were counted in Universal Analytics. This method may be most helpful for situations where a meaningful conversion action really only takes place once in a single session. For example, a file download conversion might make sense to count only once per session (since it doesn’t matter much whether your visitor downloads the same file twice or once).
Once per event may be more helpful for conversions like purchases where you truly want to track a conversion every time the event occurs, even if it occurs more than once in a session.
We need the GA4 configuration tag when setting up GA4 on a website for the first time. This is the tracking code that has the unique “Measurement ID” that maps back your specific data stream.
A “dimension” is an attribute of your data in Google Analytics. These dimensions can sometimes help to provide additional context to events. A “custom dimension” is one such attribute that Google Analytics 4 does not track on its own. Instead, we need to be able to do some additional work to be able to see this data. Custom dimensions are especially important in the context of “events” and “event parameters.”
This guide explains how to use custom dimensions.
Certain reports in GA4 will only track a limited amount of data. The advanced reporting feature called “Explorations” (see below) will only record 2 months worth of data by default. You can change this to 14 months in the admin settings using the Data Retention settings.
If you haven’t already done so, this 10 step implementation guide to GA4 could be worth a read.
Data streams are new in GA4 compared to UA. It refers to a flow of data from your website or app to GA4. Data streams can be 1 of 3 types: Web (websites), Android (Android apps), or iOS (iOS apps).
The GA4 tracking code (the “configuration tag”) is found within the Data Stream.
Dimensions and Metrics
Your Google Analytics 4 data is presented in terms of dimensions and metrics.
A dimension is an attribute of your data. A metric is the quantifiable part of your data. For example, you might be looking at the total number of Sessions (visits) broken down by Country. In this situation the dimension would be Country and the Metric would be count of Sessions.
Explorations are an advanced reporting feature that is available in GA4.
It is a new term compared to Universal Analytics. Explorations can be used from pre-existing templates or they can be created completely from scratch by selecting your own dimensions, metrics, and segments.
Here’s an example of how to use GA4 Explorations.
A specific web interaction is tracked as an “event” in GA4.
There are four different types of events in GA4. You can read about them below. Although for practical purposes we can consider them in two categories: events that GA4 tracks by default and events that we need to configure ourselves for tracking.
Automatically Collected Events
Automatically collected events are collected automatically by GA4. How’s that for profound? The first_visit, session_start, and user_engagement events are the most important automatically collected events to know. Unlike enhanced measurement events (below), you can’t disable automatically collected events.
Here’s what Google says in their support article about these events.
Enhanced Measurement Events
Enhanced measurement events are an area of real strength for GA4 relative to UA. Most of these events were things that could not be tracked in UA without custom work requiring the help of Google Tag Manager. In GA4, however, these events are collected by default. Unlike automatically collected events, you can decide to toggle some or all of these events “off” if you want to.
Some examples of enhanced measurements are the ‘scroll’ event (fires at 90% scroll depth), the click event (fires on outbound link clicks), and the file_download event (fires when an embedded file is downloaded). Here’s the full list of enhanced measurement events and event names from Google.
One important thing to note: there are limitations to some enhanced measurement events. For example, on this website we’ve turned off the ‘scroll’ enhanced measurement event and replaced it with a custom scroll tracking event that will record data at multiple depths instead of just 90%.
Unlike automatically collected events and enhanced measurement events, these events will not be tracked by Google Analytics by default. We’ll need to do the work ourselves to track them.
Google gives us a little bit of help for Recommended events by providing a recommended event name to use. Google will also recommend names of event parameters for us to use with those events. But all of the setup work to create the event falls fully on the analyst.
Here is Google’s documentation on Recommended events and parameters.
Custom events are differentiated from Recommended events by the fact that Google doesn’t provide a recommended event name or recommended event parameters for the event.
Custom events are similar to Recommended events in that Google Analytics won’t collect them automatically for us. There are two primary ways to create custom events. You can create some custom events through the GA4 interface. Other custom events need to created with the help of Google Tag Manager.
If you already know all about Tag Manager, there are a number of custom event tutorials on the Root and Branch YouTube channel. Here’s how to set up a custom event for button click tracking and here’s how to install GTM in 4 minutes. If you’re not yet comfortable with GTM, this guide to understanding tags and triggers may be worth a read.
Parameters provide additional context to events. For example, you might track the number of internal link clicks with an event named internal_link_click. Do you want to see the destination URLs of the links that were clicked? Do you want to see the text of the links that were clicked? This additional context would be provided by event parameters. Compared to UA, event parameters play an even more prominent role in GA4.
Google Signals is a Google product that can be associated with GA4. Signals are additional data that comes from users who are signed in and have consented to Ads Personalization. This additional data can be used for cross device remarketing and tracking.
Here’s what Google says in this support article:
Google signals are session data from sites and apps that Google associates with users who have signed in to their Google accounts, and who have turned on Ads Personalization. This association of data with these signed-in users is used to enable cross-device reporting, cross-device remarketing, and cross-device conversion export to Google Ads.Google Analytics Help
There are some potential downsides that you should research before you make a decision to activate signals. One of them is thresholding (see more in the thresholding entry below).You can turn Google Signals on or off in your Data Settings.
Google Tag Manager
Just like in Universal Analytics, GA4 functions best when used in conjunction with Google Tag Manager. Tag Manager can quickly install the GA4 configuration tag. Tag Manager can also create custom GA4 event tags for things like button click tracking and custom scroll depth tracking.
GA4 has multiple places for reporting functions. Earlier in this list of key definitions we covered Explorations, the advanced reporting features. There are also “Standard reports.” Standard reports live within the “Reports” section of the GA4 interface. You can see that below. For a full review, this guide to standard reports has the details.
Does your GA4 property seem to be missing data? If so, thresholding may be the culprit. Google Analytics applies thresholds when it believes the identity of individual users may be at stake. This primarily relates to Google Signals, Demographic information, and Search query information. Here is what Google says in their support article:
Data thresholds are applied to prevent anyone viewing a report or exploration from inferring the identity of individual users based on demographics, interests, or other signals present in the data.Google Analytics Support
In Universal Analytics many of us were familiar with the account structure of Account -> Property -> View. In GA4, there are no more Views. There is instead the “Data Stream” in the GA4 account hierarchy, although this doesn’t perform the same function as a View in UA.
It is possible, however, to use report filters to replicate some of the same View functionality in GA4.
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