So, Universal Analytics is sunsetting in July 2023, and you’re not totally sold on Google Analytics 4.
You’re not alone.
There’s nothing wrong with weighing your options now, because you’re going to have to redo your implementation anyway. It’s a great time to decide what analytics implementation makes the most sense for your business—for now and over the long-term.
So, what’s the big deal about this change?
GA4 is taking a very flexible approach to analytics, and it’s working hard to be future-proof. But there’s still a lot of work to be done before GA4 reaches complete feature parity with its predecessor. For instance, custom calculations do not yet exist. Traffic filtering options are almost non-existent. Product and session-scoped dimensions aren’t yet there, among other features. Still, Google is racing to get these features out by the end of the year—and, for the purposes of this article, let’s assume they’re in place.
Even so, the move from UA to GA4 represents a new paradigm. New how? Google adapted the event-driven data model for GA4. This model has been popular for mobile application tracking for the past decade, but it’s new to most marketers.
The intent of this article isn’t to talk you out of migrating to GA4, but instead emphasize that we’re at an inflection point where it makes sense to ensure your analytics tool fits into how your organization operates.
What does it mean to fit a tool into how my organization operates?
At Search Discovery, we’ve conducted countless vendor audits, so we can answer, with confidence, that the best fit tool rarely boils down to core tool functionality. You can pretty much make any analytics tool work for your business. However, the GA4 paradigm is something new. With GA4, the way we operate must change. Why?
- The tagging architecture is completely different.
- Default reports have been trimmed or eliminated.
These two points mean you have to reimplement, retrain, and reports must be created manually. If these operational differences seem like too big a lift for your team, it’s probably a good time to shop around. Let’s talk about Adobe Analytics—a lot has probably changed since you last saw it.
What type of organization might contemplate the UA to Adobe Analytics migration scenario?
When you have heavy usage outside of your analytics team
Google Analytics was always exceptional at enabling users to “swim” through the data by way of their default reports. Without the default reports, those days are gone. Instead, getting data you’re looking for is done via the GA Exploration tool. This tool is akin to Adobe’s Analysis Workspace, but a much steeper learning curve.
Analysis Workspace was brilliantly designed with an intuitive drag-and-drop interface. GA’s Explorations just take longer to produce and customize. That’s partially because you have to manually import every metric and dimension you want to use in an exploration. I found that the slower pace of “swimming” through the data impacts how I test hypotheses.
When you want deep variable customization
Remember having to duplicate props and eVars with every server call? Remember setting up time-parting variables? Yeah, that’s not a thing anymore.
Maybe the beauty of that just resonates with industry vets because so much functionality is now baked into Adobe Analytics by default. To the uninitiated, let’s just focus on how you can customize variables in Adobe Analytics. You can fine-tune variables to persist at any scope. Want to set up a variable that expires after a purchase? You can do that with Adobe Analytics. That level of customization is not doable in GA.
I’m not suggesting that EVERYONE needs that level of customization, but companies that really get into the nuts and bolts will find Adobe Analytics’ level of flexibility refreshing.
When you have a lot of unique data points
Google’s new architecture reacts uniquely when it reaches high cardinality. It buckets data into this “(other)” line item. Basically, if you reach a certain level of unique values in any report, it will dump data into this bucket, so you aren’t actually seeing a real view of your data.
That includes data from high-traffic dimensions. For example, I could pull a report on Page URLs and see 50,000 pageview events for the homepage. Because there are over N unique page URLs, we reached our cardinality limit. If I refresh the page, I might see 30,000 pageview events for the homepage!
No, Adobe isn’t immune to throwing traffic into “Low Traffic” buckets, but you are still able to pull the raw data—and it won’t drop a random sample from ALL of your data into that bucket, just the long-tail.
When you worry that there be other disruptive transitions
While I don’t think this is likely, many are concerned that UA is being deprecated with a one-year notice. With Adobe, 15-year-old code will run, and you’ll collect data. That’s not likely to change.
But please don’t use 15-year-old code.
GA4 isn’t for everyone. Adobe Analytics isn’t for everyone. If you’re nervous about making the switch, do some diligence and research other tools. Analytics tools try incredibly hard to reach some level of data capture parity, and the biggest differentiator is how they fit into your business processes.
GA4 will make you change how you think and operate. For some, that will be a good business decision. For others, it’ll be a heavier-than-expected lift that makes it worth taking the time to explore all of your options.
At Search Discovery, we’d love to help guide you down the path of long-term analytics sustainability. There’s a lot of nuance to each tool that we couldn’t fit into this article. Did you know that you can use your GA/GTM data layer in Adobe Launch?