In e-commerce companies, businesses heavily depend on tools such as Google Analytics to understand user behaviour. This tool enables marketing teams to monitor activities on their websites, offering valuable insights into customer interactions and behaviours, thereby improving their understanding of how users engage with their e-commerce platforms. These insights play an important role in defining effective online strategies and improving overall user experience.

However, with the introduction of GA4, there is a noticeable gap compared to its predecessor UA (or GA3) in terms of interpreting metrics. In this article, we will explain some disparities between GA4 and UA. But first let’s recall what UA and GA4 are.

UA (Universal Analytics)

Universal Analytics is a web analytics service launched in 2012 by Google. Some of us also call it GA3. This tool allows website owners to track visitor interactions with their websites. It provides insights into user behaviour, helping businesses understand their audience better.

GA4 (Google Analytics 4)

Google Analytics 4, commonly referred to as GA4, is the latest version of Google Analytics. It was officially introduced in October 2020. GA4 represents a significant shift from Universal Analytics, focusing on a more user-centric and event-driven approach to analytics. Unlike Universal Analytics, which primarily relies on pageviews, GA4 emphasises event tracking. One of the key reasons for creating GA4 was to adapt to the evolving digital landscape, including the rise of mobile apps and the increasing importance of cross-platform and cross-device tracking.

GA4 vs UA metrics

Many of us may be curious about the implementation of GA4. GA4 represents a new tracking approach; as mentioned earlier, it relies on event-based data rather than session-based data. However, it introduces additional features such as the collection of website and app data to provide a comprehensive understanding of the customer journey. It includes privacy controls such as cookieless measurement, and behavioural and conversion modelling.

Standard Universal Analytics will stop collecting data in July 2023, and the 360 version is set to stop in July 2024. Many of you have started migrating from UA to GA4 (or have finished the migration). During this transition, discrepancies in data may have pop-up. It’s essential to recognize that comparing metrics from UA to GA4 isn’t a straightforward apples-to-apples comparison. Consequently, we need to understand these disparities and provide explanations. This article aims to outline some key metrics and clarify the primary reasons behind these gaps.


A session refers to a period during which a user actively engages with your website or app. This timeframe is defined by specific parameters that dictate when a session begins and ends.

GA4 defines sessions differently, often resulting in a variance in session counts when compared to UA due to factors such as geography, UTM usage, filters, and estimation methods. UA has specific criteria to end a session: when there’s a 30-minute lapse of inactivity, if the clock strikes midnight (based on the viewing time zone), or if new campaign parameters are introduced. This means if a user returns after 30 minutes of inactivity or if they’re on the website when a new day begins, UA initiates a fresh session. Similarly, encountering new campaign parameters prompts the start of a new session in UA.

Unlike UA, GA4 does not restart sessions at midnight or with new campaign parameters. Moreover, GA4 uses a statistical estimate of the number of sessions, but UA does not. And finally, GA4 combines both web and app data.

One last thing is about “Consent Mode”. In practice, when Consent Mode is activated and the users did not give their consent for collecting the data, Google Analytics generates a random fake GA client identifier. This identifier is refreshed every time the page is loaded. This means every page view will be attributed to a new session. So if you have Consent mode activated in GA4 and not in UA, this can be also a reason for a higher number of sessions in GA4.


In Google Analytics, a “User” refers to a unique visitor who interacts with your website or app within a specific timeframe. It is a metric that quantifies the number of individual users who have accessed your site or app.

Google Analytics uses various technologies, including cookies, to identify and differentiate users. In UA, you have Total Users (everyone) and New Users (first-time visitors). GA4 expands this by introducing Active Users, those engaged in meaningful interactions. Moreover, GA4 broadens this scope by seamlessly integrating app data, providing a more holistic view of user behaviour, like we previously explained for sessions.

A screenshot of a user analytics dashboard displaying a table with columns for Audience, Users, New Users, Sessions, and Views per Session. 'All Users' is highlighted as the audience segment, showing a total of 286 users, 259 new users, 488 sessions, and an average of 1.54 views per session. A tooltip indicating 'The total number of active users' is visible over the table


In Google Analytics, a “Pageview” is a metric that counts the total number of pages viewed by visitors on your website or app. It measures the number of times a specific page on your site has been loaded or reloaded in a user’s browser.

Pageviews should be similar between UA and GA4, but variances might occur based on filters and additional tracking elements. GA4 combines both web and app data, unlike UA, which might separate mobile-specific properties. Consider a scenario where a user visits an e-commerce website on their desktop using a web browser and later switches to the mobile app to make a purchase. In Universal Analytics, the web and app data might be tracked separately, leading to potential underreporting of pageviews if not properly configured. On the other hand, GA4 seamlessly integrates web and app data, providing a more comprehensive view of user interactions across platforms. This integration can result in higher pageview counts in GA4 compared to UA, highlighting the importance of understanding these differences when interpreting analytics data.

Bounce Rate

The bounce rate indicates the proportion of visitors who exit a webpage without engaging in any activity, such as clicking a link, submitting a form, or completing a purchase.

Bounce rate is a critical metric indicating user engagement, and is also affected by the transition to GA4. In UA, a bounce occurs when a session consists of only one pageview without any interaction, but next interactions prevent it from being a bounce. Engaged Sessions in GA4 are defined by having multiple views/pageviews, a conversion event, or lasting more than 10 seconds, GA4’s Bounce Rate is calculated by subtracting the Engagement Rate from 100, thereby reducing bounce rates as compared to UA.

Analytics dashboard snapshot showing user engagement metrics with a line graph tracking changes over time. Metrics include 'Average engagement time' at 1 minute and 37 seconds, 'Engaged sessions per user' at 0.95, and 'Average engagement time per session' at 57 seconds. The graph displays a time span from September 17 to October 8 with fluctuations in engagement time.


A conversion occurs when a website visitor completes a desired action, such as making a purchase, signing up for a newsletter, filling out a form, or any other goal that the website owner wants to achieve.

Conversions are crucial metrics for businesses as they indicate the effectiveness of their website or app in fulfilling specific objectives. Comparing conversions can be intricate due to differences in how UA and GA4 handle conversion events. GA4 counts every instance, while UA counts one per session.


As you may already be aware, UA (Universal Analytics) and GA4 (Google Analytics 4) are two distinct tools with different structures, metric calculation methods, and user interfaces. One of the primary disparities between these tools is the shift from session-based data collection in UA to event-based data collection in GA4. There are other distinctions not covered in this article, but focusing on the fundamental differences discussed here is advisable if you wish to comprehend the main gaps.

Businesses should allocate time to educate their teams about GA4’s metrics to ensure that analysts can effectively leverage its capabilities. Additionally, it’s essential to revisit the definitions of metrics like sessions and bounce rates in the context of GA4, enabling businesses to align their key performance indicators with this new analytics framework.

In subsequent articles, we will deep dive into the sink of GA4 data into BigQuery and how to efficiently transform this raw data into curated datamarts.

If you enjoyed reading this article, stay tuned as we regularly publish articles on Google Analytics and how to get the most value of this data. Follow Astrafy on LinkedIn to be notified for the next article ;).

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