Migration to GA4:
What to Expect If You Haven’t Made the Switch Yet

Google Analytics 4 (GA4) is the latest version of Google Analytics. It is designed to help businesses and website owners gain a deeper understanding of their target audience — for example, by tracking user behavior and measuring the effectiveness of marketing campaigns.


GA4 introduces a range of new features and improvements compared to the previous version, Universal Analytics (UA). The main difference lies in its event-based model, rather than relying on interactions (hits) as before.


For a long time, analytics focused primarily on measuring website performance on desktop and laptop devices, while mobile data remained secondary. Google Analytics 4 changes this approach by combining different types of resources into a single, unified user journey.

With Google Analytics 4, you can track performance not only on your websites but also across web and mobile applications. You’ll also gain insights into machine learning algorithms and learn how to apply their results to solve various project-related tasks.


Another important point is that Google Analytics 4 does not rely solely on cookies. Instead, it places stronger emphasis on user privacy.


Most leading analysts agree that migrating from UA to GA4 should be initiated as soon as possible. First, it simplifies working with analytics tools. Second, it strengthens a company’s competitiveness. We’ll cover this in more detail in the next section.

GA4 represents the next stage in measurement standards. It allows users to analyze audience behavior across iOS and Android apps as well as the web.


Companies can now automatically identify user journeys on their websites and leverage machine learning technologies to improve marketing efficiency and increase return on ad spend (ROAS).


We recommend migrating to GA4 as soon as possible to collect the maximum amount of audience and campaign data before the transition window fully closes.

Migrating from Universal Analytics to GA4 may feel inconvenient for those accustomed to the old interface. However, Google is working to unify and streamline its platforms.


To better illustrate why GA4 is the only way forward, here are at least four compelling reasons to make the switch.

You should migrate as quickly as possible to build up sufficient data in the new system. While Google announced that UA would stop processing data in August 2023, in reality most tracking stopped only by October.

But that is far from the only reason. There are at least four more compelling arguments for making the switch now:

The main goal of migrating to GA4 is to save time — the most valuable resource in business. But time is far from the only reason. GA4 offers a range of powerful advantages that significantly improve marketers’ efficiency. We’ll take a closer look at the most important ones below.

Many of the new features in GA4 are so appealing that you’ll want to start using them right away:

Still, the drawbacks are far fewer than the advantages:

Of course, as always, despite the significant improvements, GA4 is still not a perfect product. Take a look at the list of drawbacks in the next section.

Unfortunately, the unpleasant surprises don’t end there. When implementing Google Analytics 4, there is a chance you may encounter additional challenges. The good news is that, so far, only three such cases are known.

Here are the main situations that may cause difficulties:

• If you haven’t developed a clear data collection framework, you risk running out of storage space too quickly.

• If you lack a unified system of metrics — meaning events and their parameters are not standardized — it will be impossible to run end-to-end analytics across your website and apps.

• You will need to reconfigure all conversions and user audiences, since the migration tool from UA has never worked properly.

To better understand the advantages and drawbacks of the new analytics system, let’s take a closer look at the key differences between UA and GA4.

In Universal Analytics, interactions were tracked through different types of hits: social interactions, transactions, pageviews, and others. In Google Analytics 4, every interaction is treated as an event.


Universal Analytics also supported events, categorized by label, action, or category. However, GA4 does not follow this classification. Instead, the new system works with event parameters, which provide additional details about user actions.


Some parameters are recorded automatically, while others can be added manually. In total, up to 25 parameters can be assigned to each event.


Because of the fundamental difference in data models, Google recommends not copying the logic of the old system into GA4, but instead designing new tracking frameworks that better match current needs.

When comparing data across the two systems, you may notice differences in how sessions are measured. In UA, a session is defined as the period during which a user actively engages with a website. A session in UA ends when:

• the user is inactive for more than 30 minutes;

• the clock passes midnight and a new day begins;

• new campaign parameters are detected, for example UTM tags on internal links (which actually contradicts Google’s own recommendations).

In GA4, the event session_start creates a session ID and links all subsequent events to it. Here, a session also ends after 30 minutes of inactivity. However, unlike UA, a session in GA4 can continue past midnight, and new campaign parameters do not trigger a new session. For websites with a global audience, this difference may result in discrepancies between session metrics in UA and GA4.

Instead of focusing on bounce rate, Google has introduced a more positive metric in GA4 — the engagement rate. In simple terms, it’s the percentage of engaged sessions out of all sessions. An engaged session is defined as one lasting longer than 10 seconds, having at least 2 page or screen views, or including a conversion event.


GA4 still provides a bounce rate metric, but it represents the percentage of sessions with no interactions. In other words, the number of bounced sessions is inversely proportional to the number of engaged sessions. In UA, by contrast, bounce rate simply meant the percentage of users who viewed no more than one page on the site.

In GA4, this option is available for all properties, while in UA it was limited to Analytics 360. Events can be sent to BigQuery in raw form and then queried using SQL. The feature has no additional requirements as long as it is used within the BigQuery sandbox, which also supports data streaming.

In the old system, basic Universal Analytics functions could be used without Google Tag Manager. For example, you could set up conversions for a landing page directly. In GA4, this is no longer possible, as all goals are event-based. That means it’s much harder to work without Tag Manager, and it’s worth getting familiar with how to use it — especially for e-commerce and digital marketing projects.

A good understanding of GTM makes it easier to set up advanced data collection and create custom measurements and events for users.

One of the most anticipated features in the new analytics system is the ability to track both website and app data within a single property. All interactions are recorded as events, making it much easier to unify data across platforms.

In the old version, the structure consisted of three parts: account, property, and view. In GA4, only account and property remain. This means GA4 properties no longer use views. Instead, the system is built around data streams, which send information from apps and websites into Analytics.

UA collected data at the property level using a tracking ID. GA4 collects data at the stream level, using a stream ID. Each GA4 property can include up to 50 data streams in total, with up to 30 app data streams.

Google Analytics 4 may not be the right fit for you if:

• You need to export conversions, since integration with search campaign management tools and creative platforms is still limited.

• You rely on data import, as GA4 currently does not allow analyzing costs from non-Google campaigns or calculating ROAS.

• You require collaboration across multiple teams, as GA4 has no views and access management is not yet fully implemented.

Of course, without these features you won’t be able to use the system to its full potential, but we still recommend setting up GA4 — at least to begin collecting and storing data. Sooner or later, these functions will be implemented.


The old version will eventually stop working, and data cannot be transferred from it. Missing the opportunity to collect valuable information over a specific (and often lengthy) period would be a serious setback.


If, after reading this section, you are convinced that GA4 is right for your company, let’s move on to the correct migration process.

If you’ve decided to move forward with the migration, we recommend following these steps:

After that, you can focus on more advanced tasks — for example, exploring the AI-powered features in the new analytics system. We cover them in detail in the next section.

Machine learning is transforming the way data is analyzed — and, as a result, how strategic decisions are made. That’s why it’s important to understand at least the core AI-driven features that distinguish GA4 from UA and help marketers gain a competitive edge.

Artificial intelligence helps detect unusual patterns and analyze them. These could be isolated incidents or emerging widespread issues that require closer attention.


With this capability, businesses can quickly adjust marketing campaigns and strategies, ensuring more efficient use of resources while keeping performance consistently high.

This refers to predictive metrics that are valuable to marketers in terms of user behavior — for example, customer churn and potential conversion rates.


With this information, it becomes easier to target audiences that are most likely to respond positively to your marketing campaigns. This increases the chances of improving both engagement and conversion rates. In addition, AI-powered predictive analytics enables marketers to design more accurate and effective strategies overall.

Artificial intelligence makes it possible to segment target audiences with maximum relevance and accuracy. This ensures that potential customers receive only the information they need — and at the right time. Adding personalized recommendations further enhances the user experience. As a result, customer loyalty grows, and conversions increase across key areas.


To make the most of machine learning, it’s important to understand the main types of events in Google Analytics 4.

Artificial intelligence goes beyond standard reports, allowing you to build custom analytics in GA4 tailored to the goals and needs of your business.


These insights help identify new growth opportunities and key trends that can be used to refine marketing campaigns. With advanced analytics in GA4, businesses can spot market shifts earlier than competitors and gain a strategic advantage.

In the new analytics system, all events are grouped into four categories:

Unlike UA, where setting up events required working with the global tag <gtag.js> or Tag Manager, GA4 automatically records many events by default.

At the same time, GA4 takes privacy to an entirely new level with the introduction of Consent Mode. We’ll cover how this feature works in the next section.

Consent Mode in GA4 operates on several levels of data granularity — from fully anonymous to fully identifiable — depending entirely on the level of consent provided by the user.

• The owner can see which content was interacted with — this applies to all users, even those who did not accept analytics cookies.

• The owner can view reports on all content interactions, broken down by each visit — this applies to all users who accepted analytics cookies.

• The owner can see the content a user interacted with during a visit and also identify who the person is — this applies to users who both accepted analytics cookies and registered in the system.

Consent Mode is a new GA4 feature that addresses the challenge of reporting on user interactions when people refuse the use of cookies or the processing of personal data. It does not rely on user identifiers and instead collects data anonymously.


This way, a website owner still receives the essential information about how visitors interact with the site while respecting user privacy.


Here’s how it works. If a user visits a site for the first time and declines the use of analytics cookies, the site owner can still see how the visitor interacted with the content — but no personal data is collected, unless the user gives explicit additional consent.


For simplicity, think of it like a local grocery store. The shop owner or cashier can see that a customer comes in, notices which products they look at, and knows what they buy. But the owner does not learn the customer’s personal details unless the person voluntarily agrees — for example, by filling out a form to receive a loyalty card.

When users disable analytics cookies, Consent Mode can still provide site owners with information such as the number of visits to a specific web page or the number of downloads of a particular document. However, user-level details are lost. For example, it is no longer possible to distinguish between a new visitor and a returning one based on a document download.


Privacy will continue to play a critical role as the digital environment evolves. This means that website owners will need tools that both ensure compliance with regulations and still provide the insights necessary to run their business effectively.

Consent Mode is a compromise: users do not disclose their personal data, while website owners still receive at least the minimum information needed for analytics. When this mode is enabled, personal data online becomes blurred in the same way that faces or license plates are blurred on Google Maps.


With Consent Mode, you may not know your customer’s phone number, home address, or car plate — but you will still be able to analyze how they interact with your content. These insights can then be used to improve marketing campaigns and refine your strategy.

Want to worry less about the challenges of switching to GA4? Start the process as early as possible. This is nothing like cramming the night before an exam — GA4 is a new and complex product that requires careful, detailed study.


The more time you give yourself to get familiar with the tool, the more precisely you’ll be able to tailor it to your business needs. The timing may feel inconvenient, but trust us — the results will be well worth the effort.

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