As Google deprecates Universal Analytics in favor of Google Analytics 4 (GA4) there are several changes on the horizon that website owners need to be aware of. Google Analytics 4 is poised to provide granular data about website traffic keeping the privacy-centric future of the internet in mind. Let’s look at some of the key updates that make GA4 the future of analytics.
Unlike Universal Analytics which measures entire sessions, GA4 allows you to “measure distinct user interactions” within your page using events. There are 4 broad categories of events that GA4 uses:
Automatically Collected Events are active once you set up the Google tag or the Tag Manager snippet on your website or the Google Analytics for Firebase SDK in your app. These are the basic interactions that take place on a page and no additional code is required.
Enabling Enhanced Measurement Events allows you to collect data for interactions on the website or app without changing any code. It is important to understand what enhanced data will be collected from your website, so be sure to carefully understand each option.
Recommended Events require additional context to be effective and are not set automatically. By adding these events to your web data stream, you can generate detailed data about your website traffic.
GA4 allows you to create Custom Events for events that might be unique to your website or not found in the existing event types. You can define the name and parameters of such events for segregating data for specific events on a page.
Unlike its predecessor Universal Analytics, GA4 allows users to monitor event data for both web and app to create a detailed cross-platform customer journey that allows for a deeper understanding of customer interactions. This will provide a complete view of the customer journey and help in engaging with customers across all touchpoints
As the internet moves into a cookie-less future, data privacy takes center stage. By including options for cookie-less measurement and behavioral models, GA4 is designed to comply with the data privacy norms of the future while delivering an in-depth analysis of website traffic.
At its core GA4 is designed with privacy in mind, for businesses to meet the evolving needs of consumers around data collection and usage. GA4 is built for the future, to operate without cookies and applies machine learning to fill the data gaps. This will ensure marketers can rely on Google Analytics for measurement in a cookie-less world.
By collecting and creating structured event data with the help of Machine Learning (ML) models, GA4 uses three predictive metrics to determine a future purchase decision.
| Metric | Definition |
|---|---|
| Purchase Probability | The probability that a user who was active in the last 28 days will log a specific conversion event within the next 7 days. |
| Churn Probability | The probability that a user who was active on your app or site within the last 7 days will not be active within the next 7 days. |
| Predicted Revenue | The revenue expected from all purchase conversions within the next 28 days from a user who was active in the last 28 days. |
Using its structured event data models GA4 can predict events with considerable accuracy. These models allow marketers to create predictive audiences that fulfill at least one of the predictive metrics, allowing for more effective targeting and retargeting of customers.
Universal Analytics depended can on the last-click attribution model that assigned the total credit of a purchase to the last click the customer made before making a purchase decision, this could be an ad, search engine result, social media post, etc. GA4’s enhanced attribution model monitors the customer journey and attributes credit to the various touchpoints within the customer journey. There are three types of attribution models used in GA4:
The data-driven attribution model uses advanced machine learning to understand how each touch point within a customer’s journey contributed to a purchase decision. Data-driven models use a counterfactual approach by looking at the customer journey and contrasting ‘what happened with what could have happened,’ and which touchpoints were best to drive interaction.
These data-driven attribution models provide a more complete view of the customer journey and the importance of each customer touchpoint to marketers, allowing them to create more efficient and effective customer journeys while respecting user privacy.
The cross-channel rule-based models use rules on the cross-channel interaction of visitors with your website or app. Four cross-channel rules can be used:
A. Cross-channel first click
This model attributes 100% of the conversion to the first click the customer made on the journey to a successful conversion.
B. Cross-channel linear
This model attributes credit for the conversion equally across the touchpoints within the customer journey.
C. Cross-channel position-based
This model attributes 40% of the credit to the first and last clicks in the customer journey, respectively, and the remaining 20% is distributed across all the other touchpoints in the middle.
D. Cross-channel time decay
This model assigns greater attribution to touchpoints that occurred closer to the time of conversion in a customer journey. Credit for the conversion is distributed using a 7-day half-life.
100% of the credit is attributed to any Google Ads that the customer clicked on. If the customer did not use a Google Ad as a touchpoint in their journey the model reverts to a cross-channel last-clicked model.ii
With its advanced AI and ML models to help marketers in a privacy-centric future, GA4 is set to become the standard for all website and app traffic analysis. It’s time to make the move from Universal Analytics to GA4 and stay ahead of the curve.
With over 150 successful migrations completed, we are here to help your business be prepared for the cookie-less future. To know more about how Milestone can assist with your GA4 migration, contact us at sales@milestoneinternet.com or call us at 408-200-2211.
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