Looking ahead to the new Google Analytics: first steps

By now you’ve probably heard about a new version of Google Analytics, called GA4. It has been more than seven years since Google introduced its last platform overhaul with Universal Analytics. The new GA4 transforms how we look at analytics by marrying user data from mobile apps and traditional desktop websites. Here are some of the advancements we’re most excited about at Empirical Path and advice for enabling them.

You should expect new features and more useful insights with varying degrees of implementation complexity. To get ready, Empirical Path is testing key features of GA4 before introducing them to our clients. We recommend that our clients begin planning around these change requirements in 2021. Even if you take “baby steps” toward GA4 at first, having that conversation early will help Empirical Path create a proper migration roadmap to meet your needs.

So what’s new? First, Google Analytics is building on the App + Web property that has been in beta since last year. The new Analytics uses machine learning to automatically produce helpful insights into your customers and their behaviors. GA4 by design will help you learn what your customers are doing on your properties regardless of platform, be that a mobile app or via a browser. (If you’re already using App + Web this change may not be such a leap.) 

Secondly, the industry writ large is bracing for increased regulation around privacy, so identifiers such as cookies will be increasingly less reliable as users opt out. To prepare for this reality, Analytics will focus less on the platform and more on each customer through user IDs and signals from opt-in advertising. The goal is to follow your customer from acquisition (via an ad, an app download, or perhaps a referral) to conversion and retention. This new way of looking at the customer journey will be reflected in GA4 reports.

Rather than emphasize tracking pageviews and sessions, GA4 provides reports on events and users regardless of the platform on which they interact with your brand. It will be easier to follow user funnels in terms of navigation steps from beginning to end and thus better understand how and why a conversion happened. The goal is to narrow down which channels on which platforms, app or web, are turning leads into customers, and to maximize each.

Google promises that its machine learning models will alert you to trends in your data automatically, helping forecast demand and even predict what customers might do next. For instance, predictive metrics can highlight the potential revenue of specific types of customers and increase engagement with them, improving their experience and making more sales.

Some additional benefits of GA4 include:

  • Simplified reporting interface (less overwhelming but perhaps harder to recreate current standard reports)
  • Many typical user actions will be tracked automatically, so less-complex instances are easier to set up
  • A more insightful and flexible conversion funnel and also content pathing (user journey) reports
  • Export to BigQuery of raw event data with streaming data export and regional data storage options, previously only available to Analytics 360 customers
  • Better and more automated remarketing audience building and publishing (but just for Google Ads for now)

Timeline

The challenge for many GA users will be making the shift to event-driven reporting, which Empirical Path partners like Mixpanel and Amplitude have long done. Seeing the customer as a series of decisions rather than disconnected actions is the key, but that means many traditional reports and interfaces analysts rely upon today may not cleanly translate into the new Analytics.

It seems clear that Google will not end support for its existing Analytics system. But it’s equally clear that Google wants to incentivize adoption of the new GA4 by providing compelling reasons to switch, such as machine learning for predictive analytics and estimating opted-out users. The good news is that the free version of GA4 currently includes all of these innovative features, including BigQuery export.

The way forward Empirical Path recommends is for clients to set up “dual tracking” by running Universal Analytics and GA4 at the same time for a while. Importantly, the ultimate move to GA4 will be a clean break from the previous way of reporting. Google thus advises that clients start early with GA4 in order to build historical data. 

Empirical Path is broadly advising our clients to migrate to GA4 in stages. The first stage is basic creation steps, such as importing current Google Analytics property settings, if tagged with the gtag.js global site tag. If tagged with Google Tag Manager, you will need to create new GA4 tags within GTM. If tagged with analytics.js you will need to migrate to the global site tag or, preferably, GTM. The good news: There are a lot of custom events such as document downloads and scroll tracking that can now be turned on without additional tracking effort. 

Every organization should consider advice in order to maximize the power of the new GA4 for its specific needs. For some clients, the path could be deliberate and take longer. For some app-driven businesses, there may be incentives to move faster to take advantage of new tools.

Empirical Path is prepared to fully brief you on what steps are important to take sooner than later and to help your analytics team prepare for a better, more useful Google Analytics. To get started, or if you would like to keep up-to-date on GA4 and receive timely advice on migration, please let us know by filling out our contact form. We look forward to hearing from you.

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