Google Analytics 4 (GA4) is a new analytics platform designed to enhance user tracking across web and mobile platforms, focusing on a more user-centric, event-based system. It introduces features like engagement metrics, improved tracking capabilities, and an organized interface but requires a learning curve for users familiar with Universal Analytics. Recommendations include running both GA4 and Universal Analytics simultaneously to ease the transition, while utilizing Google Tag Manager for flexible implementations.

1. G o o g l e A n a l y t i c s 4

2. C O N T E N T S
1 Introduction
2
3
4
System
Differences & Implications
Implementation
5 Recommendation

3. Introduction

4. W h a t i s G A 4 ?
Google Analytics 4 (GA4) is a re-envisioned Web + Mobile Property.
It is clearly built to deal primarily with Mobile App issues.
It’s Primary Purpose is to correct the inadequacies in tracking the relationship between
Web + Mobile Apps
It’s also supposed to be Google’s answer to a more cross-channel environment, and
preparing for a more cookie-less future.

5. W h a t i s G A 4 ?
1. GA4 is more much user-centric and has a better understanding of user behaviour
which can results in a more accurate number of users and sessions
2. It is offering features that were once only available until now in 360, like probability
metrics and more custom analytical tools
3. It has a more organised and cleaner look to it
4. It has a revamped engagement measurement system (engaged sessions) that makes
it a lot easier to understand engagement instead of just session duration and bounce
rate
5. Much more flexible and agile system
6. Has built in tracking for engagement systems that were once add-ons like scrolls,
time on site, etc.
7. Unified display of all data
Main Benefits

6. System

7. S y s t e m O V E R V I E W
1. GA4 is a completely event-based system instead of a
session-based system
2. GA4 centres around the “Stream” which is like a
mini-property with its own settings and tracking
system
3. It is also much more of a user-based system that
relies upon device id, signals and user ids to connect
sessions
4. It is still reliant upon the company or app to provide
a user id and to find a way to send that even when a
user isn’t signed in

8. e v e n t s O V E R V I E W
1. Automatically Collected Events
2. Enhanced Measurements Events – These
needed to be opted in but no further setting
required
3. Recommended Events – Require configuration
but aren’t considered custom
4. Custom Events – Require configuration both
within GA4 and on the website

9. Differences & Implications

10. U A V s G A 4 I n t e r f a c e
U n i v e r s a l A n a l y t i c s G o o g l e A n a l y t i c s 4

11. N e w D I M E N S I O N S / M E T R I C S
Dimension/Metric Definition
Engaged Sessions
Number of sessions that lasted longer than 10 seconds or had a conversion event, or
had 2 or more screen or page views
Engagement Rate The Percentage of engaged sessions (engaged sessions/sessions)
Events Per Session Events Per Sessions
Event Counts A count of all triggered Events (has a table for specific events)
Conversions Number of times triggered a conversion event (has a dropdown for different events)
User Source/Medium etc This is now based on a user level rather than sessions level
Average Engagement Time
Average length of time that the app was in the foreground or the website had focus in
the browser
Views Per User Instead of page views per users
Views Number of app screens or web pages users saw. Repeated views are counted
Unique User Scrolls
The number of unique users who scrolled down at least 90% of the page. Tracked as
part of enhanced
Total Revenue Total revenue from purchases, subscriptions and advertising
Ecommerce revenue Purchase events including tax and shipping
Total Ad Revenue
Item category Was product category and is now multi-level
Churn probability The probability that users won’t be active in the next 7 days
Purchase probability The probability that users will make at least one purchase in the next 7 days
First date visit The date the user’s first visit occurred
Last purchase date The last date the user made a purchase
Last platform The last platform that the user was seen on

12. M i s s i n g D I M E N S I O N S / M E T R I C S
Dimension/Metric Change Note
Channel Groups
It doesn’t look like you can configure the channel groups
and must rely on default channel group
Bounce Rate Replaced for engagement rate
Cart-purchase rate Doesn’t Look Like it Has Been Replaced
Conversion rate Might be a calculated field or a manual calculation
Ecom conversion rate Same as CVR or just on monetisation
Exit rate

13. M i s s i n g R e p o r t s
Report Is It Replicated Elsewhere?
Affinity/In-Market Report This is the full Interests Report
Frequency & Recency
New Vs Returning In analysis hub
Date time Can do day but not hour
Search Console missing
Campaign Report
Can create in analysis but complicated as event campaign or user
campaign
Social Report Could probably configure in analysis with difficulty
Speed Report Not at this time
Exit Pages Has exit has a metric but not rate
Landing Pages Using first_seen metric in analysis, probably
Funnel Visualisation Yes in analysis
Site Search
I think it would need to be sent as an event and then analysed using the
specific event
Source Drilldown
This is the report that allows you to drill down more on default category to
see what’s nested within. This might be able to be done in analysis
Shopping Behaviour
Yes in analysis using funnel. But can’t have all widgets in it. Each is its
own report
Checkout Behaviour Yes in analysis using funnel but the build out is separate on each
Sales Report Yes using events
MCF assisted conversion
Top Conversion Paths
Time Lag
Path Length
Model Comparison Tool

14. O t h e r N o t a b l e D i f f e r e n c e s
1. Time Series Graphs in each section are fix in terms
of date distribution and the metric they are
comparing over team
2. It is also much more reliant on accurate
source/medium and campaign tracking for campaign
tracking and defaults to source/medium instead of
default channel category
3. It has also split source/medium into user and
session
4. Data layer for ecommerce is very different to
Universal Analytics
5. Audiences are much more integrated into the GA4
and you can easily create audiences within the
analysis tool. It is also much more integrated with
Google Ads, allowing for users from different
streams to impact audiences

15. I m p l i c a t i o n s
1. Instead of a session lasting 30 minutes, it can now last 72
hours after the last event was triggered, resulting in less
sessions, but more accurate accounting of cross-browser,
cross-channel
2. The automatic events and enhanced measurements add
tracking to the page that would require further set up. This
means that Google has added more layers of additional
tracking throughout the experience and not just on the
pageview load
3. Engagement rate and engaged session is a relatively much
better metric than bounce rate. It needs to be able to track
active browser tab in order to be helpful
4. Page titles are more critical in path or flow analysis as the
analysis tool only shows page titles and not paths
5. The analysis tools is powerful but will be a learning curve
especially it’s designed to be very configurable

16. Implementation

17. I m p l e m e n t a t i o n
1. Simple Click and Upgrade or Add
New Property and it defaults to GA4
2. Has Installation Guide
3. Can pull data from UA tracking script
if it is not implemented through a
CMS app, GTM or full script
implementation
Google Analytics Interface

18. S h o p i f y I m p l e m e n t a t i o n
1. Shopify is working on supporting
GA4, but as of now, they are not
2. The tag can be implemented directly
by changing the theme liquid
3. Development will need to go to
recreate the datalayer or send data
to GA4
4. Or can use Google Tag Manager +
Elevar app ($50/month) which
creates the datalayer (they even
have the commerce GTM tags as a
free download)

19. Recomendation

20. R e c o m m e n d a t i o n
Google Analytics 4 is going to be the norm as Google Analytics
will eventually retire Universal Analytics
It will be a learning curve and it doesn’t have everything that
we look at.
Since UA and GA4 can be run at the same time, we should run
both and get used to GA4 but not completely rely upon it
Since GA4 is an event-based system, Google Tag Manager
seems like a better and more flexible implementation apparatus
rather than hardcoding every single event.