Now that Google Analytics (GA4) has officially replaced Universal Analytics, many mission-driven organizations are not loving the new normal. From a steep learning curve to having to interpret new metrics, the frustration is real. Let’s address the key issues of concern and find that silver lining in order to move towards impact.
The planned phaseout of Google Analytics was a shock when it was announced. As a free, relatively easy tool, it was used almost universally by nonprofits and all the organizations with whom we work. As of July, it is officially gone, replaced by GA4.
Here at Forum One, we have been busy helping organizations prepare for GA4, and even though our partners have now had time to test it out, GA4 still poses a steep learning curve, and frankly, prompts a lot of complaints.
Key issues of concern (i.e., frustration)
We’ll get to the tool’s silver linings, but so you know you’re not alone in your frustration, here are a few of the key issues.
1. The data isn’t apples-to-apples
We knew this going in, but organizations are still having to adjust to learning and setting up new metrics, while data like unique pageviews and bounce rate are gone. This can make it difficult to compare current traffic to past performance.
2. There’s very little “out-of-the-box”
Universal Analytics was designed to be useful immediately, providing over 30 pre-made reports. While some of us exported our data from UA, those pre-made reports served the data needs of most people well. GA4 is built with a different approach. Rather than a collection of pre-made reports, Google includes a few reports out-of-the-box, but accessing much of the information available in Universal Analytics requires you to utilize their new Explorations tool, which Google says is “a collection of advanced techniques that go beyond standard reports to help you uncover deeper insights about your customers’ behavior.”
3. The gap between free and paid versions is too wide
While GA4 still offers a free version, and free is the limit for most small organizations, we know larger organizations with sophisticated digital operations who would be interested in investing to improve their analytics and reporting capacity. But the $50k starting price for 360 is a shock after years of receiving the tool for free.
4. Transparency is lacking
GA4 relies on modeling in some cases, meaning in some cases they’re looking at similar behavior among users with shared characteristics, and making an estimate that if one user took an action, a similar user did too. There’s nothing wrong with this kind of modeling, but the extent of its use is unclear, and the lack of clarity makes some users question the data they’re seeing.
Commiserating on the downsides can be helpful—ultimately addressing these challenges together will help the entire sector—but let’s also spend some time highlighting what’s good and promising about GA4.
On the plus side: GA4 makes analytics more intentional
While the ubiquitous ease of the old Google Analytics made it a snap to use, many organizations had a set-it-and-forget-it-approach. It was often clear that they might run reports regularly, but weren’t really applying lessons or acting strategically on the data or reports they were seeing.
The learning curve of GA4 means that to use it at all, organizations really do need to be more intentional about their goals, strategies, and tactics. This is a good thing; setting real KPIs backed by user data and analyzing what works and doesn’t is key to effective digital strategy.
For example, we’ve seen our client at the Smithsonian’s National Museum of African American History and Culture uncover visitor behavior in GA4 that they couldn’t see before. By tracking events with GA4 in their Freedmen’s Bureau Search Portal, which allows users to research previously-unavailable data sets dating back to the Civil War, they can see when there are repeat or common searches that aren’t returning results—presumably frustrating users. This knowledge can help them learn what visitors are actually looking for, what they value, and the museum can respond accordingly, elevating certain content or developing new content. Previously, they might just know that visitors spent a certain amount of time on a page before leaving. With the investment of time and intentional setup in GA4, they can reveal much more actionable information.
Adaptive, machine learning and predictive analytics hold promise
Google’s overall focus on machine learning holds promise for future benefits, when fully integrated in GA4. The interface already benefits from intuitive phrasing: presenting questions like “Where did my visitors come from?” GA4 helps users get quick access to a useful report. Making that interface more dynamic, responsive to any prompt, using chat GPT-like functions is something we can envision.
Predictive analytics are also currently available in a limited scope, but it’s easy to imagine this area being further developed. GA4 could increasingly use machine learning to predict behavior and help orgs adapt. For example, using data to predict “the number and amount of donations an organization should expect to receive in the remainder of the month” or “how many visitors a museum should expect on a specific day,” can quickly enable organizations to make decisions informed by predictive data.
What other challenges or opportunities are you experiencing with GA4? We’d love to hear them. In the meantime, we’ll continue to share lessons learned and new benefits, tricks, and tactics in GA4 as they develop.