Universal Analytics vs GA4 – What’s the Difference

Dec 30, 2022 | Analytics, Digital Marketing |

Google recently announced that the days of Universal Analytics (UA) are numbered, and we have no choice but to move to Google Analytics 4 (GA4). Many marketers who’ve been using UA for years seem pretty shocked and upset.

After all, old habits die hard, and it can take time to get used to new ones.


    OCT 2020 – Google releases Google Analytics 4, under the acronym GA4

    JUL 1, 2023 – Standard Universal Analytics properties will stop processing new hits. Users will need to upgrade to GA4 by this date.

      There are also a lot of people who’re excited about the new version of Google, and you’ll see why in a few moments. Let’s remember that any of us who work with UA will probably continue to use GA4. So there’s no point in debating whether it’s good or bad. It’s just happening; we must adjust and make the best of it.

      To get an overall impression of Google Analytics 4, we can say that it’s not easy to start using it right away, but there are a lot of new features and customisations that you’ll love. Of course, there are also some missing features, but Google has promised that many current issues with the new platform will be solved in a few months.

      Let’s first take a quick look at the GA4 platform and then discuss how it differs from Universal Analytics. Then, we’ll give you some pro tips for analysing data in GA4  that will help build your analytics skills.

      Universal Analytics vs GA4

      Universal Analytics vs GA4: Brief Overview

      Google Analytics 4 (GA4) is officially Google’s recommended analytics tool. It was initially called App+Web Property because GA4 can track app and web visits in a single Google Analytics property. According to Google, the new platform:

      • Collects website & app analytics and maps the customer journey more accurately
      • Uses events instead of session-based data
      • Improves privacy control through cookieless measurement and behavioural and conversion modelling
      • Provides predictive capabilities without requiring complex models
      • Offers direct integrations to media platforms

      A Google Analytics property is where the magic happens, where your online business data gets processed by Google Analytics. Before Google Analytics 4, you had to use two different properties if you had an app and a website. However, with GA4, you can use a single property, data filtering, and configurations to organise and optimise analytics on both platforms.

      Google Analytics 4 allows “businesses to measure across platforms and devices using multiple forms of identity,” including first-party data and Google Signals from viewers who have opted into ads personalization. GA4 will still use available cookies for tracking, but the event-based data model will replace the traditional models of tracking sessions.

      Universal Analytics vs GA4: What Are The Main Differences

      When you visit GA4, you first notice that it looks very different. If you see that all the reports you used have disappeared, don’t panic! This is GA4’s way of telling you that it’s super customisable, and you can choose what to display on the main dashboard. But aside from the look, there are other significant differences between the two platforms, including:

      Universal Analytics vs GA4

      Session-Based vs. Event-Based Data Models

      The difference between UA and GA4 is mainly the conversion of sessions to events. These terms can be a bit confusing. So let’s get them straight.

      All your analytics data was categorised into sessions in the Universal Analytics properties, and all reports were based on those sessions. A session is a group of user interactions with your website within a specific time frame. Analytics collects and organises user interactions such as page views, events, and eCommerce transactions as hits.

      In GA4, user interactions with your website or app are still collected and stored as events. This gives you a new real-time perspective into what’s happening in your website or app by analysing data such as page views, button clicks, user actions, or system events.

      Events-based modelling has several advantages. For example, it specifies user actions such as purchase value, the title of the page a user visited, or their geographic location. This information can add context to the event, allowing you to focus on potential weaknesses and strengths along the customer journey. Distinguishing between user and session acquisition also helps identify the channels with the highest conversion rates.

      When you compare UA and GA4, you see that events-based modelling puts GA4 miles ahead, offering an immensely flexible setup for marketers by integrating web and app data into one analytics tool. Session data isn’t entirely kicked out of GA4, but it’s no longer the primary tracking source.



      Marketers with UA experience confirm that custom reports are not used that much. Because they were not easy to use, you had to spend a lot of time figuring out what was what. If you compare the operating technology of Universal Analytics with GA4, the difference is clear as day. UA’s tech foundation was outdated, and you could barely create event funnels or even collect more event data.

      With Universal Analytics, there were only three parameters to send with each event: category, label, and action. GA4 has expanded its reach with 25 parameters and is now a serious contender for other analytics tools. Now you are well equipped to monitor and analyse various events in the funnel. The type of table report you can create with GA4 is almost unlimited.

      You can also create your own custom events to track particular actions on your website. For instance, if you are trying out a new content strategy or ad combination and want to know how visitors are responding to that blog or ad, you can track their behaviour by changing the current events or setting up a new event.


      Public concern about digital privacy is growing daily, and for a good reason. We should be able to protect our own personal information and that of our clients and customers. And indeed, the privacy protocols in Universal Analytics vs GA4 have changed dramatically.

      For starters, GA4 no longer collects and stores IP addresses. That was not the case with Universal Analytics unless you physically anonymised them. To protect users’ data, Google implemented a privacy mode in GA4 that only uses cookies for specific purposes when users agree to share their info.

      The associated Google tags adjust their behaviour when consent for ad or analytics storage is denied. Privacy issues related to Google’s new conversion modelling have led to notable attempts to mitigate security breaches and improve privacy, including data retention and deletion requests, ad personalization, regional settings, and location-specific data.

      Conversion Modelling

      Google has been talking about a revolution in conversion modelling since August 2020 and why “it will be crucial in a world without cookies.” For those unfamiliar with the term: Conversion modelling essentially uses machine learning to quantify the impact of marketing efforts by analysing the subset of your users who generated high-quality conversion data.

      Conversion modelling identifies correlations and trends between key data points and then uses the behaviour of that subset to fill data gaps in the larger population. But again, there are privacy concerns. Google announced that it does not use individual user data in its modelling. Instead, it relies on aggregated data such as historical conversion rates, device type, browser, location, etc.

      Data & Reports

      Comparing UA and GA4 does throw up stark differences. On logging into your GA account, you’ll find a “Reports” tab on the left that includes reports you’ve viewed recently or frequently, as well as Google Insights. So far, it’s pretty much the same as UA, but GA4 reports have two subcategories: the “Reports” and “Explore” segments.

      In the “Reports” segment, you’ll find predefined reports divided into “Life cycle” and “User Group.” You’re probably familiar with both if you’ve tried UA. “Life cycle” includes acquisition, monetization (formerly conversion), and engagement (the same as behaviour in UA).

      As for the information available, UA and GA4 provide pretty much the same data. In addition to the new names, there’s also a new section called “Retention”. 

      “Engagement” has pretty much the same function as “Behaviour” and additionally includes reports on conversions (formerly known as “Goals”). 

      Monetization, on the other hand, is a new shining star in the constellation of GA4.

      In the U.S., monetization was almost exclusively limited to e-commerce. In GA4, however, advertising revenue and in-app sales can be integrated so that all the income you earn from the items, ads, and subscriptions on your website or app are accounted for.

      The downside? Fewer predefined reports in GA4’s folders than in UA. For example, your Behaviour reports consist of 22 predefined reports in UA, while GA4 has only 4 reports in the Engagement folder. Also, you can create need-specific and person-specific folders in GA4’s library.

      Universal Analytics vs GA4


      One of the most common problems with most analytic tools is that it’s difficult for business owners to find relevant metrics to measure their overall performance. However, Google Analytics 4 uses event-based data and picks a select combination of metrics that matter to your business. If you’re new to analytics tools, you can start with simple metrics and track more complicated ones over time.

      For developers, the opposite is true: you want increasingly detailed resources. You can also use GA4 to collect data from Internet-connected devices like POS or a kiosk. You can then export data to BigQuery, combine it with other data, use SQL queries and get actionable insights for your business analytics.

      Universal Analytics started to showcase a few glimpses of machine learning in 2018. But in the last few years, the trend of integrating machine learning into online analytics has been rapid. Machine learning combines artificial intelligence and computer science, and now Google has integrated it into GA4.

      For example, anomaly detection is an AI-powered method to identify anomalies in time series data for a given metric. If you’ve collected enough historical data to build predictive models, this can be a beneficial tool for detecting statistical differences in your data sets.

      Universal Analytics vs GA4: Who Is the Winner?

      Google Analytics has always been a reliable web analytics tool, and in fact, there are two major camps of critics and supporters. Most content creators, marketers and strategists have used it at least once in their lives, but its proponents agree on one thing: It can’t be the be-all and end-all of day-to-day reporting and analytics solutions.

      GA4 has brought many new features and changes compared to UA, but it still has a long way to go. GA4 has many bugs, and it seems that Google is now doing its best to keep the lights on. It’s best to use Google Analytics 4 to collect data and send it to their BI tools. Using a combination of the best services and solutions is a fail-proof growth strategy.

      If you’re not sure which analytics solutions and services work best for your business, check out our website and contact us today!

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