Google Analytics 4 is a powerful marketing tool providing vital information for better marketing decisions.
It represents a new generation of web analysis that has allowed marketers to effectively analyze important metrics about how customers interact with websites, not just track traffic. It was a big change from Universal Analytics to GA4, at the time many doubts were raised, but today I think everyone agrees that it was for the better, and an inevitable reality.
Here's what you need to know about GA4.
Google Analytics 4 tracks the entire customer journey across multiple platforms and takes advantage of AI and machine learning to provide more detailed information on how users interact with your website and/or application.
Google Analytics 4 (GA4) was developed with customer privacy in mind, so it includes privacy controls, cookie-free measurement, and behavioral and conversion modeling. This is in response to some of the latest privacy laws, such as the GDPR (General Data Protection Regulation) and the CCPA (California Consumer Privacy Act). With a tracking approach that prioritizes privacy, data measurement across different channels, and predictive analysis driven by artificial intelligence, GA4 is an advanced tool that offers unparalleled insights.
For GA4, all measurements are events. Instead of seeing generalized data, you can now gain a more complete understanding of how users interact with your app and website.
Originally, GA assumed that page views were the most important metric - but when the majority of traffic happens on mobile and apps take on a decisive importance, this is no longer true. The new parameters may have forced a learning curve, a small trade-off when you can access more and better data.
What does this mean for you? You can still view reports at session level, but the ability to break them down by interaction means more detailed reports and insights.
But how does Google Analytics 4 work?
In simple terms, Google Analytics 4 is a free tracking tool offered by Google that shows you how visitors use your site.
For example, imagine you own an e-commerce shop and you want to know how many users visit your site. With the help of Google Analytics, you can see the number of visitors to your shop, where they come from, what device they are using and much more.
To measure a web page, you first need to create a Google Analytics 4 account. Then you need to add a small piece of JavaScript measurement code to your site. This can be done in several ways, but most of today's websites make it easy to integrate with GA4 from scratch in just a few steps. From then on, whenever a user visits a web page, the tracking code will collect pseudonymized information about how that user interacted with the page.
Google Analytics 4 provides information about user behavior that can be crucial for your business. There are several reasons why you should use GA4.
Here are some of its benefits:
Evaluate your site's performance.
Verify the effectiveness of your marketing efforts.
Get ideas for what kind of content to create or what products to offer on your site.
Segment users into different groups (such as age, gender, country, device, behavior, etc.) to identify which ones are most active.
Determinar quais as páginas do site a otimizar para aumentar as conversões.
Artificial Intelligence
Google Analytics 4 integrates machine learning and AI. In this way, it can provide you with detailed information about user behaviour.
Interestingly, Google Analytics 4 manages to work even without always using cookies. Instead, it uses machine learning to fill in the data gaps (left by users who opt out of cookies) and provide you with reliable information about user history - without the need for cookies.
Through the power of AI, GA4 uses your past data, analyses it and makes useful predictions about future user behaviour. Analysing how users have interacted with your site in the past gives you a degree of insight into how they might interact in the future.
GA4 displays its predictions through its AI metrics, which are as follows:
Churn probability - The chances that a user who has been active in the last 7 days will not be active again in the next 7 days..
Likelihood of purchase - The chances of a user active in the last 28 days becoming a conversion in the next 7 days.
Revenue forecast - How much revenue can you expect to make in the next 28 days from a user who has been active in the last 28 days.
With this collected data, you can create complex target audiences for future campaigns on social media and Google Ads.
These AI metrics can, for example, help you create an audience made up of website visitors who are likely to return to buy from your e-commerce shop. Or, users who are likely to buy a product in the next 7 days.
Determining the likelihood of such events manually would be almost impossible - which is why including Machine Learning in GA4 is so useful.
How and where can I access the information provided by Google Analytics?
The Google Analytics platform is all about an interface that allows you to access the data you collect from your website, application, etc. It does this through a set of reports, standard and customized, with real-time or historical data and even predictive data with access to artificial intelligence, which presents you with information reliably and consistently. Let's explore some of these reports now.
Standard reports in GA4
Os relatórios padrão do GA4 englobam o " Resumo dos relatórios", uma visão rápida do desempenho, o relatório "Em tempo real", assim como os relatórios de "Ciclo de vida" etc. A maior parte dos relatórios encontra-se na área "Ciclo de vida", onde estão os relatórios do funil de vendas, Aquisição, Envolvimento, Monetização e retenção.
The Reports Snapshot
This report offers extremely useful information on how your marketing investments are performing:
It provides quick access in the initial "dashboard" or control panel to metrics such as the number of users and specifically new users, allowing you to understand the effectiveness of your marketing investments and how many new users are finding your site, in that same control panel you can also see the average engagement time and total revenue.
In the cards below you can easily access various important metrics such as the location of your visitors, the ranking of channels from which sessions originate, the most viewed pages, the most triggered events, etc.
The Real-Time Report
The real-time report is interesting for getting a quick overview of what's happening on your site and can help diagnose what might be causing significant traffic spikes. It reports on all users in the last 30 minutes and provides a snapshot of activity.
You can easily see the total number of simultaneous users, as well as an interesting map showing where the activity is taking place and where in the world your visitors are coming from.
It has several very interesting metrics such as users by source, users by audience, the breakdown by device category, which pages are particularly popular at the moment, and which events are taking place.
Life Cycle Reports
A good part of the value of GA4's standard reports lies in the Lifecycle reports. In particular, the Acquisition, Engagement and Monetisation reports contain detailed reports that can provide useful insights for the business.
Acquisition Reports
The Acquisition reporting area focuses on how your visitors get to your site. How are they "acquired"? This includes Acquisition Overview, User Acquisition and Traffic Acquisition, as you can see in the red box below.
The overview:
The overview provides a snapshot of users and sessions and also integrates data from Google Ads and Google Search, if you have configured these integrations for your GA4 property.
The User Acquisition report:
The User Acquisition report includes details on traffic sources based on user activity.
The Traffic Acquisition report:
The Traffic Acquisition report is similar, but focuses on Sessions instead of Users.
Engagement Reports
While Acquisition reports focus on how visitors get to your site, Engagement reports focus on what they do after they arrive.
The standard Engagement reports include an Engagement Overview, Events Report, Conversions Report and Pages and Screens.
Events Report
The Events Report lists all the events that occurred on the site during the period you are analyzing.
Conversions Report
Conversions focus only on the specific events that you have marked to be recorded as conversions.
Pages and Screens Report
It includes information on how visitors interact with the most popular pages on your site.
Monetisation reports
Monetization reports are only relevant to companies that have monetized their website or application. These reports provide valuable information on the performance of monetization strategies, allowing companies to better understand revenue sources, user behavior in relation to paid products or services, and the effectiveness of different monetization approaches. They are essential for adjusting strategies and maximizing the financial return of the site or application.
Retention report
This area allows you to analyse how effectively you retain customers. The idea here is to understand whether or not users who come to the site return, and for how long.
User retention by cohort is probably the most valuable graph in the Retention section, as it allows you to analyse how many of your users return to the site the day after they are acquired (1 day), in the following 7 days (7 days) or in the following 30 days (30 days). This graph allows you to understand whether you are managing to retain the interest of your users or not but, of course, it is very much influenced by the type of business.
There is also a graph with the Life Time Value of users, and it's important to point out that in Analytics the LTV refers to all users, not just customers, so the figure is much lower than the LTV of your customers, the traditional one. There's also another important difference: in your customers' LTV you take into account the average customer retention time, in Analytics this metric has to do with the period of analysis defined.
There are other reports that we will cover in a different blog post specially dedicated to reporting in GA4.
Event-Based Data Model
The new event-based data model allows you to track every action users take on your domain. This helps you understand how your customers move through the sales funnel.
Google Analytics 4 classifies all actions on the page as "events". These include clicks, downloads, video plays, submissions, among others.
These "events" are used as the central unit for measuring user engagement, as they suggest that an action has been completed on your site.
For example, if you wanted to measure how many people subscribed to your mailing list, you could assign this action as an "event". You could name the event something like "mailing_list_subscription". Every time these actions are carried out on your site, an "event" is recorded.
Once the data has been collated, you can review how many times this particular event has been triggered.
Multi-Platform Analysis
If you have a website as well as an app, you can use GA4 for multi-platform analysis. The tool combines data from your app and website, allowing you to track the user journey on both platforms. (This is different from UA, which only allowed you to track web-based data.)
Once you connect your iOS or Android app to Google Analytics 4, unique user IDs are used to track your customers. Data will be collected from each session initiated and sent directly to Google Analytics.
The data collected from apps is very similar to the data collected from your website - "events" such as video views and clicks, as well as conversion tracking, screen views and more.
This information can help you better understand how users interact with the functionalities of your site and application simultaneously.
A single source of data (from a website or application) is referred to as a "data flow" in GA4. This "flow" is the flow of data from a user and a specific platform to their GA4 account.
How GA4 calculates Sessions
With Google Analytics 4, each user is assigned a session ID that remains valid for as long as they are on the site.
This is a significant improvement on Universal Analytics, which used to record new sessions every time a user's time zone crossed midnight. This means that if a user was on your site between 23:59 and 00:01, Universal Analytics would count that 2-minute visit as two separate sessions.
Although this may seem minor, if it occurred regularly enough, it would make your session count massively unreliable. With GA4, if it's past midnight and a user is still on your website, only one session is counted.
Google's 30-minute rule still applies. Google has defined that after 30 minutes of inactivity, the session is officially recorded as closed. This rule is followed by both UA and GA4.
Engagement rate
GA4 introduced a new metric, the "engagement rate". While UA used to record bounce rate, GA4 has opted for the much more positive metric of engagement rate, which reflects how many of your site visits are user-involved.
This metric is calculated by adding up the number of user sessions that lasted more than 10 seconds and featured either a conversion event or at least two page views. These sessions are aptly named "engaged sessions".
Attribution Model
The attribution model is the process by which Google Analytics assigns credit to different touchpoints in the sales paths. These "touchpoints" are the steps a user takes before reaching a conversion and can be anything involved in the sales funnel, such as a click on a link in an email advert, or when a user clicks through to your site after an organic search.
Google Analytics 4 has three different attribution models to choose from:
Data-driven Attribution:
Data-based attribution distributes credit for conversion based on the data from each conversion event. It differs from other models because it uses your account data to calculate the actual contribution of each click interaction.
Each data-driven model is specific to each advertiser and each conversion event.
How data-driven attribution works
A atribuição utiliza algoritmos de aprendizado de máquina para avaliar tanto caminhos de conversão quanto de não conversão. O modelo baseado em dados resultante aprende como diferentes pontos de contato impactam os resultados de conversão. O modelo incorpora fatores como tempo até a conversão, tipo de dispositivo, número de interações com anúncios, a ordem de exposição aos anúncios e o tipo de ativos criativos. Usando uma abordagem contrafactual, o modelo contrasta o que aconteceu com o que poderia ter ocorrido para determinar quais pontos de contato têm maior probabilidade de impulsionar conversões. O modelo atribui crédito de conversão a esses pontos de contato com base nessa probabilidade. Preferência por Anúncios — Como o nome indica, este modelo dá crédito total ao último anúncio do Google com o qual o utilizador interagiu. Se não houver anúncios do Google no funil de vendas, este modelo muda para o último clique cross-channel.
Last Paid and Organic Click
Last Click Paid and Organic: Ignores direct traffic and attributes 100% of the conversion value to the last channel the customer passed through (or view with engagement, in the case of YouTube) before converting.
Note: The first click, linear, time decay and position-based attribution models are no longer available as of November 2023.
Last Click on Google Paid Channels
Last Click on Google Paid Channels attributes 100% of the conversion value to the last Google Ads channel the customer passed through before converting. If there is no Google Ads click along the way, the attribution model uses Last Click Paid and Organic.
Google Analytics 4 is a powerful analysis tool that offers invaluable insights into your audience, where they come from, how they got to you and how they are interacting with your site. There are numerous benefits to GA4, including cross-platform tracking, more control over data and AI-driven insights, over the next few weeks we'll be sharing more insights on analytics with you as we think it's a very important tool in digital marketing.
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