Feature
The Gist
- Metrics evolution. GA4 presents more sophisticated user metrics for robust reporting.
- Filter adjustment. Ensure accurate data representation by diagnosing and optimizing filter settings.
- Regulatory compliance. With GA4, keep your data consent management aligned with the latest privacy regulations.
Migrating from Google's Universal Analytics (UA) to GA4 has been a top priority for digital marketers and analysts. But with the deadline to adopt GA4 now past, marketers may be left with a collective shrug of what to do next.
The simple answer is to look at how your analytics settings are holding up. When you buy a new car, you often fiddle with features while you take it for a spin. Taking GA4 for a spin is certainly called for.
Adam Ribaudo covers some aspects of the change in his recent CMSWire column. Here are a few more ideas to check out while your GA4 is “on the road” to keep your analysis moving forward.
Evaluate How Metrics in UA Operate in GA4
Marketers should be using the change as a welcome opportunity to rethink metrics. Much of the comparison between UA and GA4 center on how some metrics are measured. The rush to adjust their analytics accounts diverts focus from opportunities to optimize how metrics are being reported.
The good news is that you have historical data available for comparison, allowing you to explore gaps in your key performance indicator (KPI) reports based on the changes.
For example, GA4 adds a third user metric called active users. It identifies users with engaged sessions or when certain events are triggered. This is a more nuanced identity compared to total users and new users. In fact, GA4 emphasizes Active Users in its reports.
If I were examining my analytics ecosystem, I would consider how to link active user metrics to the reports that my stakeholders need. This could include the story behind the data or the KPIs related to app and website usage. Doing so opens up ideas for dashboard updates in an organized fashion.
Related Article: GA4 Brings Back Familiar Friend: Landing Page Report Now Available for Analytics Practitioners
Check Your GA4 Filters for More Accurate Metrics
Google noted in its comparison of UA and GA4 that the UA filter may exclude some data. A poorly set filter, be it by a bad application of regular expressions or a poor order of page settings, can skew metrics.
The old advice about having a clean, unfiltered data stream is useful in this transition to GA4. You need an unfiltered data stream to accurately diagnose filter settings and determine the appropriate ones.
When it comes to events, GA4 to UA is like Threads to Twitter — it’s more streamlined and has significant differences in operation, even if the concept of events is the same. An event is a hit — an activity on a page or app. In UA hits are considered one of three types — Category, Action or Label. GA4 eliminated the categories, treating every "hit" as an event and allowing users to add types through other menus and programming.
Focusing on events and how they are set in GA4 can help organize stakeholders on what conversions are needed from websites and apps, what events should appear in reporting and how the events should be measured.
Related Article: How to Create Outstanding Real-Time Reporting in Your Dashboards
Consider a Longer Data Retention in GA4
A good idea to consider is to change the data retention setting of your GA4 property from two months to 14 months. Doing so allows you to retain user-specific data for inactive website users in GA4 longer.
Maintaining data on standby proves valuable for analyzing campaigns aimed at reengaging long-term customers who have paused app usage or haven't interacted with new website features. A longer retention period enables a deeper dive into recurring patterns. Moreover, it offers extensive time series data, bolstering advanced forecasting capabilities.
Related Article: It's a New Era of Google Analytics Reporting. Are You Ready?
Know Your Exposure Risk to Data Privacy Regulation
Marketers should also take the moment to check how consent is being managed overall. Mismanaging consent can become an irritation to visitors. Customers expect brands to uphold their privacy commitments, yet increasing state legislation seems to contradict this. Ensure your consent banner displays the correct opt-in options and assess whether the choice activity is compliant with the privacy laws of the territories your website and apps serve. If your site reaches regions where General Data Protection Regulation (GDPR)/ePrivacy Directive (ePD) laws are applicable, the process should default to a setting that allows users an informed choice to opt-in.
This examination is a good reason to explore the geographic reports in GA4. Determine which territories account for the majority of visits over a consistent timeframe. Analyze the visits within various periods — a month, 90 days, and a year prior to your current analysis date, if possible. Then identify which of those territories are dealing with data privacy issues.
Keep in mind there are other sources of data privacy risk. Privacy legislation is focused on data access and permission, so there can be risks outside of website or app activity. But identifying site and/or app activity volume by location can reveal a snapshot of the most immediate and clear privacy risk, using those with the largest amount of user activity or site traffic as a proxy.
Review Your Pixel Data for Social Media Campaigns
While this suggestion is less related to Google Analytics, it presents a good opportunity to assess if other tools, such as social media pixel data, remain viable in your measurement plan. Many website platforms harbor data for dozens of pixels, which work in conjunction with analytics solutions to provide a clear picture of campaigns. Pixels excel in remarketing, but their deployment can sometimes result in campaign ads being shown too frequently for customers' liking. Increasingly, customers are expressing concerns about being tracked via pixels before giving their consent.
Use the time to audit tools and identify any tool changes that impact your measurement plans or workflow.
Explore Opportunities for Advanced Analytics
As Adam Ribaudo mentioned in his post, a wide variety of choices are available for exporting your Google Analytics. Exporting data from GA4 into R or Python allows you to develop statistical forecasts based on the data. Immediate trends can be identified within Google Analytics, while Looker provides some additional reporting and visualization options between dimensions and metrics.
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Creating forecasts in R and Python introduces some data science concepts — exploratory data analysis and statistical measures. These are useful when you want to examine a correlation between trends or conduct a forecast analysis on time series data. The overall result is determined if app or site activity identified in GA4 are sustainable and worth further investment.
All in all, there are a lot of features to interact with an analytics solution, whether it is Google Analytics 4 or any other system. The best step to take is to start with one of the aforementioned tasks and get comfortable taking the analytics for a spin. With patience and perseverance, you will make any analytics verification feel like a true joyride.
