Google Analytics 4 (GA4) vs Universal Analytics – What is the difference?

Last Updated: May 20, 2022

Google Universal Analytics (GA3) will be discontinued from 1st July 2023.

On this date, standard Universal Analytics (GA3) will stop processing the new hits, and only GA4 will be available.

This is the best time for you to start migrating all of your GA3 trackings to GA4.

Why should you compare GA3 and GA4 data?

You probably know that both GA3 and GA4 use different data models.

GA3 data model is based on sessions and pageviews. In contrast, the GA4 data model is based on events and parameters. Thus both GA3 and GA4 can collect, process, and report the same data differently.

However, that should not stop you from comparing GA3 and GA4 data.

It is a good practice to do such comparisons.

Following are the main benefits of comparing GA3 and GA4 data:

  1. You can quickly detect anomalies in data collection.
  2. You learn a lot about how GA4 works.
  3. You can explain data discrepancies between GA3 and GA4 to your client/boss.

#1 You can quickly detect anomalies in data collection

For example, if GA3 reports 100 newsletter sign-ups, but GA4 reports only ten sign-ups during the same period, one of the GA versions is not collecting data correctly. Without such a comparison, you may never know whether your GA4 property is set up correctly.

#2 You learn a lot about how GA4 works

By comparing GA3 and GA4 data, you learn how GA4 works. This would help you in data interpretation and reporting.

#3 You can explain data discrepancies between GA3 and GA4 to your client/boss

You don’t look like a fool in front of your client/boss when they ask you why the reports and metrics are not matching.

Even if you choose not to compare GA3 and GA4 data, the decision-makers will likely do such a comparison and ask you questions about data discrepancies.

And they are likely to ask such questions for as long as GA3 exists.

So it is in your best interest to do such a comparison and improve your understanding of GA4.

Following are the key differences between Google Analytics 4 (GA4) and Universal Analytics (GA3).

#1 Reporting interface

ga3 reporting interface
ga4 reporting interface

At first glance, the GA4 reporting view may look intimidating as many of the reports and metrics you are familiar with are not there. They have either been removed or replaced.

Businesses should not expect to see the same reports that were available in GA3 since GA4 is based on a different measurement model.

You will see different sets of reports in your GA4 view, and you will not see many reports.

This is because many reports are only generated when you start tracking events.

The reporting interface of the GA4 view looks similar to that of Google Analytics for Firebase (because GA4 is built on Firebase analytics). But it is quite different from any GA3 reporting view.

#2 Measurement model

GA3 (aka Universal Analytics) uses the measurement model, which is based on sessions and pageviews.

GA4 uses the measurement model, which is based on events and parameters.

In GA4 even a ‘pageview’ is considered an event.

Every tracked activity taken by a user in GA4 is considered an event, and these events can provide much more detailed information.

Let’s say we are tracking ‘pageview’ as an event in GA4. This GA4 event would also have additional information attached to it, like the title of the page, user location, etc.

#3 Tracking IDs

To set up any type of tracking in GA4 via GTM, we use the measurement ID.

ga4 measurement id

Whereas we use the tracking ID to set up tracking in GA3 via GTM.

tracking id

If you have set up a GA4 property with a web data stream, then your measurement ID begins with the characters ‘G-’.

For example G-TXKT959827

If you have set up a GA3 property then it uses the tracking ID (and not measurement ID) and this tracking ID begins with characters ‘UA-‘.

For example UA-1509844-8

#4 View and Data Streams Setup

Historically, as Google Analytics best practice, it was always advised to have a minimum of three different views in a Google Analytics property.

One would be the ‘unfiltered view’, which would contain all the raw and unfiltered data, another would be a ‘test view’, which would contain filter, goals and other configuration changes that you would like to test, and the other a ‘master view’ which will have goals, filters and the other configuration that you tested in test view.

In GA3, you have an option to create additional views. You can create a view for your app and web tracking separately.

In GA4 standard, you do not have the option to create views. However, you do have an option to create data streams for your web and apps.

#5 Event tracking setup

The events are tracked differently in GA4 than in GA3.

When you are using GA3, all the tracked events must follow the category-action-label-value schema:

category action label value schema

This is not the case with GA4, which provides a more flexible event tracking setup.

In the case of GA4, additional information is supplied to an event via parameters:

ga4 parameters

In GA4, you do not have an event category, action, and label, but it captures the four categories of events, which are:

Out of the above four event categories, automatically collected and enhancement measurement events do not require code changes on the page or app.

These events are automatically captured if the web page has gtag.js implemented directly on the page or via Google Tag Manager.

You can send up to 25 custom parameters per event, and each value can be 100 characters long.

There is a limit of 500 unique event names per GA4 property.

However, if you need to create new events after reaching your quota, you can archive the ones that are not in use.

#6 Event tracking automation

A GA4 property has got the enhanced measurementfeature built-in which allows automatic tracking for certain types of events without any additional coding/tagging:

enhanced measurement ga4

You can automate the following types of events in GA4: 

  1. Scroll tracking
  2. Outbound clicks (aka exit tracking)
  3. Site Search tracking
  4. Video engagement (aka video tracking)
  5. Tracking file downloads.

This is something that is not possible with GA3.

Both automatically collected events and enhancement measurement events do not require any code changes.

Such events will be automatically captured if the page you are looking to track has gtag.js implemented.

However, the following two GA4 event categories require code changes to the app or web.

  • Recommended events
  • Custom events

Recommended events have predefined names and parameters and are used for specific business verticals like retail and ecommerce, travel, games, jobs, and real estate.

Custom events are implemented by people like you and me.

#7 User and event data retention

Through the ‘User and event data retention’ feature, you can set the amount of time for which Google Analytics retains user-specific data for an inactive website user before automatically deleting it.

The user-specific data is the data that is associated with cookies, user identifiers, or advertising identifiers.

In the case of GA3, you can set the amount of time to one of the following: 

  1. 14 months
  2. 26 months
  3. 38 months
  4. 50 months or 
  5. Do not automatically expire
User and event data retention 1

In the case of GA4, you can set the amount of time to either two months or 14 months

There are no other options available:

User and event data retention ga4

#8 Ecommerce tracking

ecommerce reports in ga3 vs ga4

The ecommerce tracking capabilities provided by GA4 are still in their infancy. They are nowhere as powerful as the ecommerce tracking capabilities provided by GA3.

Also,

GA4 does not provide enhanced e-commerce tracking.

#9 Cross-device and cross-platform tracking

In the case of GA4, both the web and app data use the same schema. Whereas in the case of GA3, this is not the case.

Because of this reason, GA4 provides much more robust and reliable cross-device and cross-platform tracking than GA3.

#10 Attribution modelling

attribution reports

GA3 provides powerful attribution modelling capabilities via multi-channel funnels and attribution reports.

Such attribution modelling capabilities barely exist in GA4.

#11 Custom dimensions

In GA4, custom dimensions are created differently than in GA3.

ga4 custom dimensions

If you are using GA3, you can set/change the scope of your custom dimension to ‘Hit’, ‘Session’, ‘User’ or ‘Product’

scope of custom dimensions google analytics

There are no ‘Hit’ and ‘Session’ scopes in the case of GA4. It has been replaced by the ‘event’ scope.

For now, you can not create a custom dimension with the ‘product’ scope in GA4. You would need to use e-commerce parameters.

You can create a custom dimension in GA4 with either the ‘event’ scope or ‘user’ scope:

custom dimension in GA4

In GA4, the value of custom dimensions and custom metrics are supplied by logged event parameters and user properties.

This is not the case with GA3.

#12 Custom metrics

In GA4, custom metrics are created differently than in GA3.

ga4 custom metrics

If you are using GA3, then you can set/change the scope of your custom metric to ‘Hit’ or ‘Product’:

custom metric scope

In the case of GA4, it is not possible to set/change the scope of your custom metric. A GA4 custom metric has only one scope and that is ‘event’ scope.

custom metric scope ga4

#13 Debugging

The GA4 reporting view provides the DebugView report through which you can validate your analytics configuration from within the reporting interface:

DebugView report ga4

This is impossible with a GA3 reporting view as there is no DebugView report available.

#14 Engagement metrics

GA4 reporting view provides a new set of engagement metrics that can track users’ engagement with your website/app much more accurately than the pageviews and bounce rate metrics used by GA3.

Engagement metrics ga4

Following are examples of GA4 engagement metrics:

  1. Engaged Sessions
  2. Engagement Rate
  3. Engaged Sessions per User
  4. Average Engagement Time

Note: There is no concept of bounce rate in GA4.

#15 IP anonymization

Under GDPR, an IP address is considered personal data.

Google Analytics tracks and stores the IP addresses of your website users to report on geolocation data. However, GA does not report on IP addresses in its reports.

If your privacy policy or local privacy laws prevent the storage of full IP addresses, then you can use the IP anonymization feature to anonymize/mask website visitors’ IPs.

When you anonymize visitor IP, the last three digits from your website visitor’s IP address are automatically dropped/deleted.

In other words, the IP anonymization feature sets the last octet of IPv4 user IP addresses and the last 80 bits of IPv6 addresses to zeros.

For example,

If a website visitor has a public IP of 12.214.31.144, then as soon as the Analytics Collection Network receives the IP data, Google will anonymize/mask the IP to 12.214.31.0

If you are using the GA3 property, you can enable or disable IP anonymization.

IP Anonymization

The IP anonymization is disabled by default in GA3.

However,

If you are using a GA4 property then the IP anonymization feature is built-in, is enabled by default and you can not disable it.

#16 Reporting views

Using GA3, you can create up to 25 reporting views per property. But in the case of GA4, you can use only one reporting view.

Currently, there is no option to create additional views in the standard GA4 property.

However,

If you are using GA4 360, you can create replicate some of the functionality of a reporting view by creating a new sub-property.

subproperty ga4

There are workarounds available for creating additional views in GA4 standard. 

You can create new ‘Audiences’ or ‘Data Streams’ and use them in place of filtered views.

#17 BigQuery

GA4 comes with a free connection to BigQuery. So you can access the raw GA4 data and run SQL queries on it.

This helps in more precise and multilevel data analysis of your users so that it is easy to understand the user activities on the website.

bigquery links ga4

 GA3 does not come with a free connection to BigQuery (unless you are using GA 360). 

#18 GA3 hits vs GA4 events

A GA3 property captures users’ interactions with your website in the form of hits.

A hit is a user’s interaction with your website that sends data to the Google Analytics server.

A hit can be a pageview, event, social interaction, ecommerce, screenview etc.

A GA4 property captures all users’ interactions with your website only in the form of events.

As such:

  1. pageview hit is captured as an event in a GA4 property.
  2. An event hit is captured as an event in a GA4 property.
  3. Social interaction hit is captured as an event in a GA4 property.
  4. An ecommerce hit is captured as an event in a GA4 property.
  5. user timing hit is captured as an event in a GA4 property.
  6. An exception hit is captured as an event in a GA4 property.
  7. Screenview hit is captured as an event in a GA4 property.

A GA3 property will process the hits as long as they arrive within 4 hours of the preceding day’s close. Such hits are called ‘late hits’ as they are not sent immediately.

Whereas in GA4, events are processed even if they arrive up to 72 hours late. Such events are called ‘late events’ as they are not sent immediately.

#19 GA3 vs GA4 events

A GA3 event hit follows the category-action-label-value schema and is its own hit type:

category action label value schema

GA3 reports display event hit data in the form of category-action-label-value:

GA3 reports display event hit data in the form of category action label value

A GA4 event is a hit of any type.

For example, 

A GA4 event can be pageview, event, social interaction, ecommerce, screenview etc.

As such, the event count between GA3 and GA4 is unlikely ever to match.

A GA4 event does not follow the category-action-label-value schema.

Also, GA4 reports do not display event hit data in the form of category-action-label-value.

Unlike in GA3, in GA4, you can send one or more parameters with each event. 

Through parameters, you can provide additional information about an event like where, why and how the event was logged.

Unlike in GA3, in GA4, event names do not need to be unique and are differentiated by the parameter values collected.

In fact, 

In GA4 reusing the same event name as many times as possible is considered as best practice.

#20 GA3 vs GA4 pageviews

In GA3, the pageviews metric represents the number of views of a web page or set of web pages:

ga3 pageviews

Repeated views of the same page are counted in the ‘Pageviews’ metric of GA3.

Note: The ‘pageviews’ metric in GA3 does not report on screenviews. The screenviews are reported in a separate mobile-specific GA3 property.

GA4 reports ‘pageviews’ via the ‘views’ metric

views metric ga4

The ‘views’ metric in GA4 is the combination of pageviews and screenviews as GA4 combines both app and web data in the same property.

The repeated views of a single screen or page are counted in the ‘views’ metric of GA4.

Pageviews are calculated differently between GA3 and GA4.

So you should not compare them. They are unlikely to match.

Unlike in GA3, the GA4 property does not have the ‘unique pageviews’ metric.

#21 GA3 vs GA4 Sessions

The GA3 sessions count is unlikely to match the GA4 sessions count. This is because both GA3 and GA4 sessions are calculated and adjusted differently.

A GA3 session is a group of hits recorded for a user in a given time period. In contrast, a GA4 session is a group of events recorded for a user in a given time period.

To learn more about the differences between GA3 and GA4 sessions, check out this article: Understanding Google Analytics 4 Sessions

#22 Session counting method

In Universal Analytics, a session is basically a combination of pageviews, events, ecommerce transactions, and social interactions and would end in 30 minutes in the case of inactivity.

In contrast to this, a Google Analytics 4 session is derived from the session_start event, and there is no limit to how long the session would last.

For an app session, it would begin to end when the app is moved to the background.

However, you can extend the session by logging the extend_session parameter (with a value of 1) on events logged while the app is in the background.

Additionally, you have an option to override the default 30 minutes session timeout for an app by using the setSessionTimeoutDuration method.

You would also see lower session counts in Google Analytics 4 since it does not create a new session when the campaign source changes mid-session, like in Universal Analytics.

In GA4, we have three types of sessions-based metrics:

  1. Sessions: The number of sessions that began on your site based on the session_start event on the app or web.
  2. Engaged sessions: The number of sessions that have lasted for 10 seconds or longer.
  3. Engaged sessions per user: The number of engaged sessions per user.

#23 Difference in user counts

Google Analytics 4 uses the User ID method and considers active users on the site, who are currently engaging, to calculate user count.

Universal Analytics uses the Client ID method and focuses on total users on the site to calculate user counts.

#24 Spam data prevention

A common problem in Universal Analytics has been spam referrals, and it was possible for anyone to send the spam hits to a Google Analytics property using measurement protocol.

This issue of spam hits has been addressed in Google Analytics 4 by forcing the measurement protocol hits to include the secret key.

This key is available only to the users who have access to analytics property and is not available publicly. Only hits with a valid key will be able to send data to a Google Analytics 4 property.

#25 Explorations Reports

The reporting view of a GA4 property comes with a new set of report templates called ‘Explorations’ through which you can do advanced data analysis:

explorations report ga4

Following are the various GA4 Exploration report templates:

  1. Blank report
  2. Free form report
  3. Funnel exploration report
  4. Path exploration report
  5. Segment overlap report
  6. User explorer report
  7. Cohort exploration report
  8. User lifetime report

You can see the full list of the GA4 exploration report templates by clicking on the ‘Template Gallery‘ link:

template gallery link
template gallery ga4

In the case of GA3, only GA 360 customers can use this feature.

analytics 360 explorations reports

#26 Ability to create conversions that satisfy multiple conditions

GA3 allows you to create conversions based on:

  1. Pageviews
  2. Events
  3. Duration
  4. Pageviews/screens per session
ga3 conversions

But GA3 does not allow you to create conversions that satisfy multiple conditions.

For example, you can not define the following user activity as a conversion in GA3:

A user who visited your website via your newsletter and then watched a five minutes long video before making a purchase above $100.

However,

GA4 let you create conversions that are based on multiple conditions.

You can create such type of complex conversions in GA4 by carrying out the following three tasks:

#1 Create a new audience in GA4 with one or more conditions (like visiting your website via newsletter, watching a video for at least 5 minutes etc.).

#2 Create an audience trigger that logs an event when a user becomes a member of this audience.

#3 Mark the event as conversion.

audiences ga4
create a custom audience ga4
add one or more conditions 1
create an audience trigger ga4
mark as conversion ga4

#27 GA3 vs GA4 Content Grouping

Content grouping is a rule-based grouping of related content groups. It is made up of one or more content groups.

A content group is a set of web pages that should be based on the same/similar theme.

So in the case of a blog, a content group can be a set of web pages based on the same/similar topic (like ‘Attribution Modelling’).

In the case of an ecommerce website, a content group can be a set of web pages that sell similar products (like ‘shirts’).

Since ‘content grouping’ is made up of one or more ‘content groups’, ‘Men’ content grouping can consist of the following content groups:

  1. Men shirts
  2. Men trousers
  3. Men sportswear

Similarly,

 ‘Women’ content grouping can consist of the following content groups:

  1. Women shirts
  2. Women trousers
  3. Women sportswear

As a rule of thumb use content/product categories for ‘content grouping’ and content/product sub-categories for ‘content groups’

Content grouping is used to quickly check the performance of a content group or compare the performance of different content groups with each other.

Content grouping is especially useful if you have a big website with hundreds or thousands of pages; you can realistically measure the content performance only at the group level and not at the individual page level.

In GA3, you can create a new content grouping by clicking on the ‘+NEW CONTENT GROUPING’ button:

new content grouping button

In GA4, we create content grouping using a predefined event parameter called “content_group“:

content group

The “content_group” event parameter populates data into the “Content Group” dimension (found under Reports > Engagement > Pages and Screens):

content group dimension ga4

Note: Unlike in GA3, you can create only one content grouping in GA4.

#28 GA3 vs GA4 Users

Both GA3 and GA4 report on the total number of users via the ‘users’ metric:

users metric ga3
users metric ga4

The total number of users reported by either GA3 or GA4 is not equal to the sum of ‘New Users’ and ‘Returning Users’.

Google Analytics 4 (GA4) and Universal Analytics

This is because Google Analytics also counts new users as returning users if they return within the selected time period.

Thus there is an overlap between new and returning users.

A new user can also be labelled as a returning user both by GA3 and GA4.

GA3 does not have the ‘Returning Users’ metric. It is missing for no apparent reason. 

Whereas GA4 has the Returning Users’ metric:

ga4 returning users metric

By default, GA3 could not measure user engagement on a page, if a user does not navigate to another page.

As a result, the time spent on the page is reported zero.

GA4 on the other hand could measure user engagement on a page even if a user does not navigate to another page.

It can do that via enhanced measurement events, which allow automatic tracking for certain types of events (scroll, click, site search, time elapsed etc.) without any additional coding/tagging.

#29 GA3 vs GA4 User ID

Both GA3 and GA4 can use the following identifiers to identify a user:

  1. Google Signals – identify Google account users who have enabled ads personalisation. 
  2. Client ID – identify users by their device and browser. 
  3. User ID – identify users via the user IDs assigned to them.

Google Analytics (whether GA3 or GA4) defines user ID as a unique set of characters (like 455688863) assigned to a user so that they can be identified across devices and/or web browsers and throughout multiple sessions.

The usage of the user ID feature helps in improving the cross-device measurement and in fixing cross-device attribution issues both in GA3 and GA4.

Since each user ID is interpreted as a separate user, without the user ID implementation, the same user can be counted multiple times both by GA3 and GA4.

This could inflate your user count in GA3/GA4.

Thus, implementing the user ID feature provides you with a more accurate user count whether you are using GA3 or GA4.

From a data collection standpoint, no specific changes are necessary to map user IDs in a GA3 property to a GA4 property.

However,

Unlike the GA3 property, you don’t need a separate user ID view in a GA4 property as the user ID feature is built-in in a GA4 reporting view.

Google recommends that you keep the following factors in mind while implementing the user ID feature in a GA4 property so that the implementation of user ID on your website is consistent with the implementation of user ID on your mobile app:

  1. You use the same user ID to track a user across your mobile app and website.
  2. The values passed for user ID are of the same data type across your mobile app and website.

Google Analytics (whether GA3 or GA4) cannot automatically generate user IDs for you. You also can not use Client IDs as User IDs.

To implement the User-ID feature, you would need to generate your own unique IDs and assign those IDs to new and returning users through your user authentication system.

You would need the help of a web developer here as the implementation is quite technical.

This user authentication system is usually your website login, the system through which users can log in and log out.

The unique ID that you use to identify a logged-in user (also known as login ID) on your website can be sent as a User ID to your GA4 property.

Note: The user ID should not be used to send personally identifiable information (PII) like name, email address, etc., to a GA4 property. However, you can still use PII data internally to identify users.

Once you have set up the user ID feature in GA4, you can do the following tasks:

  1. Compare the behaviour of logged-in users with not-logged users.
  2. Create remarketing audiences based on user IDs

#30 GA3 vs GA4 Client ID

For both GA3 and GA4, a website user is technically a client ID. However, for a mobile app, GA4 uses the ‘App Instance ID’ instead of the client ID.

Whenever a user visits your website for the first time, a client ID is assigned to him. 

When the same user later returns to your website, Google Analytics (whether GA3 or GA4) checks for his client ID.

If the client ID is present, Google Analytics labels the user as a returning user and starts a new session.

If the Client ID is not present, Google Analytics labels the user as a new user and generates a new client ID.

That’s how with the help of client IDs, Google Analytics can detect new and returning users.

The client ID in both GA3 and GA4 is an identifier that is used to anonymously identify a unique website user.

This identifier is a combination of a unique random number and the first timestamp (i.e. the time of the first visit). 

Following is an example of a client ID:

5987532.16456790952

A Client ID represents a unique browser instance and is stored in browser cookies.

The client ID can exist only on the device/browser on which it has been set up. Because of this attribute, a Client ID cannot be used to measure across devices.

Since the client ID exists only on the device/browser on which it has been set up, whenever a user switches devices/browsers to visit your website, he can be labelled as a new user by Google Analytics.

As a result, client IDs cannot be used to identify the number of unique website users accurately. 

#31 GA3 vs GA4 Funnels

The funnel creation and analysis capabilities have greatly improved in GA4.

For example, you can not create funnels on the fly in GA3, but you can in GA4.

Similarly, you could not apply advanced segments to a funnel in GA3, but you can in GA4.

The GA4 funnel exploration report provides a visualization called ‘trended funnel’ through which you can determine how the funnel is performing over time:

funnel exploration ga4
trended funnels ga4

Neither GA3 nor GA3 360 provided the ability to create trended funnels.

By default, the funnels that you create in GA4 are closed. What that means, if a user does not enter the funnel via the first step, he/she will not be counted in the funnel.

When you make a GA4 funnel open, a user can enter the funnel via any step and would still be counted in the funnel.

In GA4, you can make a funnel open or close on the fly by using a toggle button:

make open funnel ga4

#32 GA3 vs GA4 Conversion count

In GA3, a conversion is counted only once per user session. Whereas in GA4, a conversion can be counted multiple times per user session.

So if you have defined ‘file download’ as a conversion, then GA3 will count only one file download as a conversion in a given session no matter how many times a user downloads the file in the same session.

Whereas in GA4, if a user downloaded a file twice in the same session, two conversions will be counted.

While you can duplicate most GA3 goals using GA4 conversion events, two GA3 goal types cannot be duplicated. These goals are ‘smart’ goals and ‘duration’ goals.

duration smart goal universal analytics

#33 GA3 vs GA4 Web purchase count

As long as you are collecting a unique transaction_id value in both GA3 and GA4, the web purchase counts should match closely between GA3 and GA4.

#34 GA3 vs GA4 Segments

In GA3, you can create only the session, and user scoped advanced segments:

universal analytics segments

However, in GA4, you can create not only session and user scoped segments but also event scoped segments:

funnel exploration ga4 1
create segment ga4
event segment ga4

#35 Bounce rate vs Engagement Rate

GA3 uses ‘bounce rate’ as one of the metrics to measure site engagement.

Bounce rate is the percentage of single page sessions in which there was no user interaction with the page. 

Since bounce rate does not have a time threshold associated with it, a bounced session has a duration of 0 seconds.

GA4 uses the ‘engagement rate’ metric instead of ‘bounce rate’.

The ‘engagement rate’ metric is defined as the percentage of engaged sessions.

By default, an ‘Engaged Session’ is defined as the session that lasted longer than 10 seconds, had a conversion event, or had at least two pageviews or screenviews.

Unlike the bounce rate metric, the ‘Engagement Rate’ metric has a time threshold associated with it.

Because of this attribute, the ‘Engagement Rate’ metric is more useful than the ‘bounce rate’ metric in measuring user engagement, especially on a single page app/web.

#1 Google Analytics 4 Intro

  1. What is GA4 (Google Analytics 4) – The Apps + Web Property?
  2. Key Benefits of Using Google Analytics 4 (GA4)
  3. How to upgrade to GA4 (Google Analytics 4)
  4. Google Analytics 4 (GA4) vs Universal Analytics – What is the difference?
  5. Google Signals GA4 – See demographics (gender, age) in Google Analytics 4
  6. Understanding Google Analytics Measurement ID (GA4)
  7. Google Analytics 4 training & tutorial with FREE GA4 ebook
  8. Using the GA4 (Google Analytics 4) Test Property

#2 Google Analytics 4 Integrations

  1. How to connect GA4 (Google Analytics 4) with Google Data Studio
  2. How to link GA4 (Google Analytics 4) with Google Ads
  3. How to link Google Search Console to Google Analytics 4 (GA4)
  4. How to Install Google Analytics 4 on Shopify

#3 Google Analytics 4 Events

  1. GA4 (Google Analytics 4) Event Tracking Setup Tutorial
  2. Understanding Event Parameters in Google Analytics 4 (GA4)
  3. Recommended events in Google Analytics 4 (GA4)
  4. Enhanced measurement events in Google Analytics 4 (GA4)
  5. Automatically collected events in Google Analytics 4 (GA4)
  6. How to set up GA4 Custom Events via Google Tag Manager
  7. Events Report in Google Analytics 4 (GA4)
  8. How to rename events in Google Analytics 4 (GA4)
  9. How to use Google Analytics 4 Event Builder

#4 Google Analytics 4 Conversions

  1. Google Analytics 4 Conversion Tracking Guide – GA4 Goals
  2. How to import conversions from GA4 property to your Google Ads account

#5 Google Analytics 4 Dimensions

  1. GA4 (Google Analytics 4) Dimensions Tutorial
  2. GA4 (Google Analytics 4) Custom Dimensions Tutorial
  3. GA4 User Properties (User Scoped Custom Dimensions) – Tutorial
  4. Event Scoped Custom Dimensions in GA4 – Tutorial

#6 Google Analytics 4 Metrics

  1. GA4 (Google Analytics 4) Metrics Tutorial with Free Google Analytics 4 Ebook
  2. GA4 (Google Analytics 4) Custom Metrics Tutorial
  3. What are predictive metrics in Google Analytics 4 (GA4)

#7 Google Analytics 4 Ecommerce

  1. GA4 (Google Analytics 4) Ecommerce Tracking via GTM – Tutorial

#8 Google Analytics 4 Specialized Tracking

  1. GA4 (Google Analytics 4) Enhanced Measurement Tracking Tutorial
  2. Cross Domain Tracking in GA4 (Google Analytics 4) Setup Guide
  3. GA4 Site Search – Tracking Site Search in Google Analytics 4
  4. GA4 (Google Analytics 4) Scroll Tracking Tutorial
  5. Self-referral Google Analytics 4 – Referral exclusion GA4
  6. GA4 (Google Analytics 4) Data Import Tutorial
  7. Google Analytics 4 Content Grouping – Create Content Groups in GA4
  8. How to track single page apps in Google Analytics 4 (GA4)

#9 Google Analytics 4 filters

  1. GA4 filters – Understanding data filters in Google Analytics 4
  2. How to create and test filters in Google Analytics 4 (GA4)?
  3. Exclude internal traffic in GA4 (Google Analytics 4) via IP filter

#10 Google Analytics 4 Explorations

  1. Free Form Report in GA4 (Google Analytics 4) – Exploration Report
  2. How to use the user lifetime report in Google Analytics 4 (GA4)
  3. How to use Path exploration report in GA4 (Google Analytics 4) – Path analysis
  4. How to use Segment Overlap Report in Google Analytics 4 (GA4)
  5. How to use the Funnel Exploration Report in GA4 (Google Analytics 4) – Funnel Analysis
  6. Cohort Exploration Report in Google Analytics 4 (GA4)
  7. How to Create Landing Pages Report in Google Analytics 4 (GA4)

#11 Google Analytics 4 Advanced

  1. Understanding Google Analytics 4 Sessions
  2. GA4 (Google Analytics 4) Measurement Protocol Tutorial
  3. How to build comparisons (advanced segments) in Google Analytics 4 (GA4)
  4. Understanding Automated Insights in Google Analytics 4 (GA4)
  5. Understanding Channel Groupings in Google Analytics 4 (GA4)
  6. Understanding Data Sampling in Google Analytics 4 (GA4)

#12 Google Analytics 4 Reporting

  1. How to create custom insights in Google Analytics 4 (GA4)
  2. How to use Debug View report in Google Analytics 4 (GA4)

#13 Google Analytics 4 Attribution

  1. Guide to Attribution Models in GA4 (Google Analytics 4)
  2. How to Change Attribution Models in GA4 (Google Analytics 4)?
  3. GA4 (Google Analytics 4) Conversion Paths Report in Attribution
  4. GA4 (Google Analytics 4) Model comparison report in Attribution
  5. Advertising Snapshot in GA4 (Google Analytics 4) Attribution

#14 Google Analytics 4 Audiences

  1. GA4 Audiences – Creating custom audience in Google Analytics 4
  2. How to create a remarketing audience in Google Analytics 4 (GA4)
  3. Understanding Audience Triggers in Google Analytics 4 (GA4)
  4. Google Analytics 4 (GA4) Predictive Audiences – Tutorial

#15 Google Analytics 4 BigQuery

  1. GA4 BigQuery – Connect Google Analytics 4 with BigQuery
  2. How to connect and export data from GA4 to BigQuery
  3. events_ & events_intraday_ tables in BigQuery for GA4 (Google Analytics 4)

Frequently asked questions about Google Analytics 4 (GA4) vs Universal Analytics

Do I need to have an app to set up GA4 Property?

No. It’s not mandatory to have an app to create GA4 property. If you only have a website that needs to be tracked, you can select the web as the data stream.

Do we still have an option to create universal analytics property?

Yes. You still have an option to create universal analytics property, or you can also create both universal analytics and Google Analytics 4 property. 

Can I just use traditional GA on the web and use GA4 to track my mobile app?

Yes. You can use universal analytics to track your web activity and use GA4 to track your app measurement. However, the users are counted twice with this setup, once on the web and once in the app.
Google advises that you still use GA4 even for websites, as it has advanced capabilities.

How do I enable Google Analytics 4?

If you have a Google Analytics account (if you don’t have one, create one). Login to your GA Admin section and click on ‘create property’; you will see that you have GA4 will be your default option. It is recommended that you copy the code and add it to your website; however, you can use Google Tag Manager to implement it as a best practice.

Do we have an option to revert to a Google Analytics GA3 property after using GA4?

No. You do not have an option to switch back to a GA3 property since GA3 and GA4 are separate properties. 

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"How to use Digital Analytics to generate floods of new Sales and Customers without spending years figuring everything out on your own."



Here’s what we’re going to cover in this training…

#1 Why digital analytics is the key to online business success.

​#2 The number 1 reason why most marketers are not able to scale their advertising and maximize sales.

#3 Why Google and Facebook ads don’t work for most businesses & how to make them work.

#4 ​Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.

#5 The number 1 reason why conversion optimization is not working for your business.

#6 How to advertise on any marketing platform for FREE with an unlimited budget.

​#7 How to learn and master digital analytics and conversion optimization in record time.



   

My best selling books on Digital Analytics and Conversion Optimization

Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.

Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.

Attribution Modelling in Google Analytics and BeyondSECOND EDITION OUT NOW!
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.

Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.

About the Author

Himanshu Sharma

  • Founder, OptimizeSmart.com
  • Over 15 years of experience in digital analytics and marketing
  • Author of four best-selling books on digital analytics and conversion optimization
  • Nominated for Digital Analytics Association Awards for Excellence
  • Runs one of the most popular blogs in the world on digital analytics
  • Consultant to countless small and big businesses over the decade
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