H
ave you figured out Google Analytics 4 (GA4) yet, or are you among the (likely large) crowd of analysts who are still pounding the keyboard trying to decipher all the changes from Universal Analytics (UA)? When Google stopped data collection for UA starting in July of 2023, its replacement – created to satisfy regulatory demands and address privacy concerns – stepped in with a completely new way to process information.
Here at Hawthorn Creative, we had a lot of questions: How do I compare my new GA4 data to UA? How do I know the comparison is correct? Where can I find the tool that I loved on UA inside the GA4 dashboard? What the heck are all these new reports? Then, we realized that many of our clients were asking the same questions, so we put together some of the main points you need to know about GA4, including its new features and functions, data-collection methods, and newfound advantages for your business insights.
GA4’s New Reports, Functions, and Key Features Explained
If you’ve spent any quality time with GA4, you’ve likely noticed several new reports and functions – some of which are redefining how businesses analyze data. Tools like enhanced event tracking, machine learning-based predictive metrics, and deeper audience segmentation offer a wealth of opportunities for businesses seeking deeper insights into user behavior and trend forecasting.
But without education on how to turn those data points into insights, it’s all just a bunch of numbers. To kick-start your learning process, here’s a look at the key reports and functions, as well as what they do:
- Event-Driven Tracking: Data in UA was captured by way of “hits,” which included a number of interactions, like page views, social interactions, or transactions. GA4 names every interaction an event, no matter how it was triggered (a page view is an event, and so is a transaction). This shift allows businesses to get a more comprehensive view of the customer journey and their behaviors.
- Enhanced Machine Learning: The AI-driven insights you’ll find in GA4 help predict trends, segment audiences more effectively, and optimize marketing strategies in the ever-evolving luxury market. Machine learning can track interactions on multiple devices at the same time, follow precise customer journeys, figure out why users opt out and, over time as it learns, predict metrics like when a shopper is likely to log back in or make another purchase.
- Cross-Platform Tracking: Improved capabilities to track user behavior across various platforms and device IDs, so that one person remains one person whether they’re on a laptop or their phone. Getting a more robust picture of how users interact can help create seamless, personalized experiences across all touchpoints.
How Do I Make Sure I’m Comparing Apples to Apples?
One of the most common concerns we’ve heard from our clients is that a new data-collection method means they won’t be able to correctly compare this new data to years and months past. GA4’s approach is focused on a user-centric model with event-driven tracking, and that’s no small alteration from the way businesses were used to interpreting and using analytics.
So, how do you get an apples-to-apples comparison of GA4 data versus UA?
The bad news is there isn’t a direct way to compare the two sets of data. The good news is, there are third-party programs that can provide a workaround, such as Analytics Canvas, or various data-blending methods using programs like Google’s Looker Studio. For strictly GA4-collected data, the first step to gleaning meaningful insights is to establish relevant benchmarks moving forward. Then, study how the metrics have shifted and dig into the nuances between the two. Here’s how we recommend that you get started:
- Establish clear baselines: Set benchmarks for comparison purposes, but keep in mind that the way the data is represented might vary between UA and GA4. Google reports a sometimes large discrepancy between the two data sets, but explains here why it’s not a cause for concern.
- Embrace cohort exploration: According to Google, a cohort is a group of users who share a common characteristic that is identified in this report by analytics dimension – for example, all users with the same acquisition date. Thanks to GA4, you can track those user groups over time to analyze behavior changes and, if necessary, adjust your touch points.
- Consider data granularity: Granular data gets down to specifics, collecting attributes like city, browser preference, device brand and model, operating system, screen resolution, and more. That’s an opportunity to create some seriously personalized messaging.
- Patterns in the news: Keep an eye on the latest insights and trends being shared by other businesses that are making the transition to GA4. You might stumble upon an answer you’ve been searching for, or a hack that brings everything into focus.
Making the Switch (Without Losing Your Head)
We know this all sounds overwhelming, so we’ll give you the same pep talk we gave ourselves – You figured out UA, so you can figure out GA4, too. Start with a shift in perspective and level of comfort with user-centric analysis, and then take the time to learn how you can best take advantage of machine learning and cross-platform tracking. (Spoiler alert: They’re game-changers, in a great way!)
Also, don’t forget that this is a chance to get ahead of the curve – and the competition. And who doesn’t want a competitive edge?
If you’d like to sit with a professional analyst to unpack the full capabilities of GA4 for your organizations, Hawthorn Creative’s expert analytics team is happy to help.