Google Analytics 4 (GA4) reporting uses a new event-based data model that is more flexible and adaptable to the changing needs of businesses. The latest data model uses events and dimensions, allowing you to measure and analyse user interaction on your website or app.
GA4’s new reporting capabilities include:
Predictive insights: machine learning to predict future outcomes, such as customer churn and revenue
Cohorts reports: analyse groups of users with shared characteristics, such as new users or paying customers
Pathing reports: understand users’ paths through your website or app
Funnel reports: track how users move through your conversion funnel
We’ll dive into these capabilities and GA4’s latest reporting features later in the article.
Session-based tracking is the traditional approach to tracking user interactions on websites and apps. It groups individual user interactions into sessions defined by a period of inactivity. Session-based tracking is good for understanding how users move through a website or app during a single visit. However, it has limitations for reporting and analysis, such as:
It doesn’t track user interactions across multiple sessions.
It doesn’t track user interactions outside of a session, such as when a user clicks on an email link to your website.
Tracking complex user journeys involving multiple pages or screens is difficult.
Event-based tracking is a more modern approach to tracking user interactions. It tracks each individual user interaction as an event. This event allows you to track user interactions across multiple sessions and outside of sessions. It also makes it easier to track complex user journeys.
Benefits of event-based tracking for reporting and analysis:
Event-based tracking provides more granular data about user interactions than session-based tracking, allowing you to analyse user behaviour in more detail.
Event-based tracking provides more accurate insights into user behaviour by tracking all user interactions, regardless of whether they happen within a session.
Event-based tracking offers more flexibility than session-based tracking, allowing you to track any user interaction, regardless of complexity.
Here are several reasons why GA4’s event-based tracking is superior for reporting over its session-based predecessor:
Holistic User Insights: It’s about the journey, not just the visit. GA4 provides an understanding of every interaction and touchpoint.
Adaptability: As user behaviour evolves, event-based tracking evolves with it. GA4 lets you tailor tracking criteria without overhauling the system.
Cross-Platform Clarity: GA4’s event-based model seamlessly integrates user actions across devices, giving a unified view.
Proactive Engagement: With granular data, you can strategise in real time and predict actions or trends rather than reacting to them.
Let’s explore a couple more key differences between GA4 and UA and how they impact reporting.
One of the biggest differences between GA4 reporting and Universal Analytics reporting is how the platform collects and processes data.
Universal Analytics collected and processed data in separate streams like web, app, and eCommerce. Conversely, GA4 uses a single stream, giving you a more complete and comprehensive view of users and interactions across many touchpoints.
Another key difference is how GA4 organises reports. Universal Analytics categorises reports into Audience, Acquisition, Behavior, and Conversions. GA4, on the other hand, organises reports in two primary categories:
Lifecycle: reports that track the user journey, from acquisition to conversion to retention
Predictive Insights: reports that use machine learning to predict future outcomes
Let’s dive deeper into these GA4 reporting methods and how to use them for your business.
You can find all these reports in GA4 by navigating to Reports in the left sidebar. Google separates these by Life cycle and User, and there are several categories and subcategories.
Acquisition reports show how users find and interact with your website or app. These reports include information about traffic sources, referral paths, and user behaviour on your landing pages.
Types of Acquisition reports available:
User acquisition: how users find your website or digital product
Traffic acquisition: where new and returning visitors come from
How to use Acquisition reports:
Identify your most effective traffic sources.
Optimise your landing pages to convert more visitors into users.
Understand how users find and interact with your website or app through different channels.
Engagement reports show how users interact with your website or app content. These reports include information about pageviews, event completions, and session duration.
Types of Engagement reports available:
Events: shows how often an event is triggered and how many users trigger each event.
Pages and screens: shows data about the pages users visited on your website and the screens users opened on your mobile app.
Landing page: shows the first page a visitor lands on when visiting your website and how many visitors land on each page.
How to use Engagement reports:
Identify your most popular content.
Understand how users are interacting with your content.
Find areas where you can improve the user experience.
Track your marketing objectives and progress.
Identify your most effective conversion paths.
Find areas where you can improve your conversion rates.
Monetisation reports show how much revenue your website or app generates. These reports include information about eCommerce transactions, in-app purchases, and advertising revenue.
Types of Monetisation reports:
E-commerce purchases: information about the products or services you sell on your eCommerce store.
Purchase journey: shows how many and where users drop off in your purchase funnel.
In-app purchases: the purchases made through your app.
Publisher ads: shows the engagement and revenue associated with each advertisement in your app or website.
Promotions: shows the impact of promotions on purchases and revenue.
In late 2023, Google released the Checkout Journey Report. The Checkout Journey Report is a funnel visualisation tool showing customers’ steps during checkout. This report helps you identify where potential customers drop off during the checkout process and pinpoint areas for improvement.
How to use Monetisation reports:
Track your revenue over specific dates or timelines.
Identify your most profitable products, services, and channels.
Find areas where you can improve your sales funnels and monetisation strategy.
The Retention overview report shows how well your website or app retains users. It includes information about the percentage of users who return each day in their first 42 days.
The Retention report is a simple dashboard that includes data for:
Engagement by cohort
User retention over 42 days
How to use Retention reports:
Track user retention rate over time.
Identify which marketing campaigns and product development initiatives are driving retention.
Find areas where you can improve the user experience to increase retention.
GA4’s Analytics Intelligence uses advanced modelling to help you better understand data and take appropriate actions. Features include a search function for quick answers, automated insights on data changes, custom insights through user-defined rules, and predictive capabilities via machine learning models.
You can use Analytics Intelligence to ask questions using natural language, receive automatic insights, create rules for custom insights with notifications and predict potential user actions.
Analytics Insights lets you dive deeper into data with machine learning. There are two types of insights available:
Automated Insights: These alert you about unexpected data shifts or emerging trends.
Custom Insights: Here, you set the rules. Track particular data changes and create up to 50 custom insights for every property.
You can view, manage, and create new insights on the Insights dashboard. GA4 stores insights for a year and ranks them based on user interaction, helping the system learn over time. You can also manage notifications for custom insights and share these across your team.
You can utilise Anomaly Detection to identify unusual data patterns by applying a Bayesian state-space time series model to your historical data, predicting current metric values. If a data point falls outside the expected range, GA4 flags it as an anomaly. This system works on different timelines, with specified training periods for hourly, daily, or weekly anomalies.
You can identify anomalies within segments at a specific time for a more granular analysis. This method employs Principal Component Analysis (PCA) and cross-validation across multiple metrics and dimension values, flagging any segment showing anomalous behaviour and comprising at least 0.05% of the users on that property as an anomaly.
Contribution Analysis helps you pinpoint user segments tied to anomalies in your data. It first generates user segments, calculates anomalous metric values, and then surfaces these segments based on their contribution to the anomaly and the metric’s relative change over time.
To utilise this feature, ensure that Analytics Intelligence scans your data for anomalies. Once GA4 detects anomalies, you can create audiences from the identified user segments, which are helpful for root cause analysis or leveraging them for ad campaigns.
GA4 offers personalised recommendations to enhance your data utility and acquaint you with new, relevant features. These suggestions are based on your property’s history, settings, and overarching trends in Google Analytics, appearing in the designated section on the Home page and contextually across the platform.
Depending on your website, app, or data, GA4 will show you one or more of the following recommendations:
Create Predictive Audiences: Create audiences based on likely user behaviours for remarketing or Google Ads campaigns.
Google Ads Credit: New Google Ads users may receive a one-time credit to expand customer reach using GA data.
Import Conversions to Google Ads: Facilitate bid optimisation by importing web/app conversions from GA4 into Google Ads.
Link Google Ads Account: Enhance Google Ads remarketing by linking your Google Ads account to GA.
Link Search Console Account: Linking enables access to new dimensions and reports, aiding search queries and traffic data analysis.
Reconfigure Consent Mode: Address cookieless pings blocking to utilise behavioural modelling in GA4 reporting.
Sign Up for a Merchant Center Account: Display your online store products across various Google services.
So far, we’ve talked about GA4’s out-of-the-box reporting features. But this reporting only scratches the surface of the platform’s capabilities. Let’s take a look at how to go deeper with Explorations.
Explorations in GA4 introduce a fresh approach to data reporting, allowing you to craft custom data visualisations that might not be readily available in standard reports. Get a comprehensive understanding of your data and quickly discover custom insights.
There are three sections to an Exploration:
Canvas: A large display area showcasing data, with the capability to use multiple tabs for various techniques.
Variables: A left-side panel offering access to dimensions, metrics, and segments, with an option to adjust the exploration time frame.
Tab Settings: A panel to customise the active tab, select techniques, and adjust technique-specific settings from the Variables panel.
Explorations offers several visualisation techniques for the canvas:
Free-form exploration: Crosstab layout with multiple visualisation styles like bar, pie, line charts, etc.
Cohort exploration: Analyse user behaviour and performance based on shared attributes.
Funnel exploration: Visualise user steps on your site/app to optimise experiences and pinpoint audience performance.
Segment overlap: Understand how user segments interrelate and discover new complex user segments.
User exploration: Deep dive into segment users and individual user activities.
Path exploration: Map out user interaction paths on your website/app.
User lifetime: Analyse a user’s behaviour and value across their customer journey.
While GA4 is a powerful tool with excellent reporting capabilities, the platform has limitations. If you want to analyse data from multiple sources, you’ll need to export using the BigQuery Export integration.
BigQuery is a cloud data warehouse that enables you to store, query, and analyse large datasets. You can combine GA4 data with other sources, such as CRMs, advertising platforms, etc., giving you a holistic view of your customers and their interactions with your business.
Here are some of the reporting capabilities that BigQuery offers:
Advanced data modelling: BigQuery allows you to create your own data models, which can be more complex and nuanced than the data models available in GA4, giving you more data analysis flexibility.
Customisable querying: BigQuery allows you to write custom SQL queries to analyse your data. This customisation offers more control over the data you see and its presentation.
Integration with other tools: BigQuery integrates with various platforms, such as data visualisation tools and machine learning tools, allowing you to analyse your data in new and innovative ways.
GA4’s event-based model and reporting capabilities offer a dynamic, holistic understanding of user journeys. But, as the digital realm grows in complexity, businesses might find GA4’s offerings may not support their unique needs and goals. BigQuery is an excellent tool for analysing complex datasets from multiple sources, but it requires sophisticated digital analytics and data visualisation expertise.
Our Metric Labs data experts can design a bespoke data strategy, streamline GA4 reporting, and harness data analytics technologies to provide actionable insights to grow your business.
Ready to unlock the full potential of your data? Contact Metric Labs to discuss your unique data needs.
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Reminder: Google UA Historical Data to be Deleted in July 2024