My 3 Favourite Reports in Google Analytics 4 (GA4)

edit: just 2 months later, Google has officially christened this new platform as Google Analytics 4. It’s not the most exciting of names but at least it doesn’t give the impression that one must own both a website and an app. Read more about the official launch here, and watch the quick walkthrough here.

It’s been just over a year since Google Analytics first launched App+Web (now known as Google Analytics 4 or GA4), a reexamination of the way we analyse cross-platform behaviour and piece together nuanced consumer journeys. While App+Web was still in beta, many updates along the way have proven to be handy tools in my analyst toolbox.

I’ve put together a list of my 3 favourite reports, in hopes of convincing you to set up GA4 if you haven’t already done so. There’s also a ton of helpful resources out there (read: novellas) written by experienced individuals in the community, so I’ll drop a couple of those links down below for your further reading.

Enough y(app)ing, (web)’s get on with it! I’ll show myself out…

1. Behaviour reports

Events form the cornerstone of GA4, and Behaviour reports are where you can dig deeper for behavioural insights. I typically dive right in when doing exploratory analysis, to get a quick sense of frequently occurring events and/or high value events.

Upon landing on this report, I start by toggling between views, event counts and engaged sessions, to see if I can spot any patterns or anomalies sticking out.

Fig 1. A slice of the Behaviour overview dashboard in Google Analytics 4 (GA4)

Aside from “page_view”, I see that “user_engagement” is a highly occurring event. My next steps would then be to delve into the “Event count by Event name” report. Here you can sort events in a similar fashion to standard Google Analytics, based on metrics such as event count per user and total revenue.

Fig 2. The Events breakdown report, accessible through the Behaviour overview dashboard

The rabbit hole doesn’t end there; more data awaits as you click into your event of choice and browse event reports by country and gender. These “Behaviour > Event” drilldown reports are also where I utilise comparison segments again, perhaps this time looking into device platforms or custom dimensions e.g. customer account type.

Aside from an exploratory glance, another use case would be to zoom in on high value events, like transactions or monthly payments. Armed with insight around Who, When, Where and How Much, you could more comfortably make business decisions around, say, reinforcing your live chat team on weekday afternoons to seal the deal with big spenders looking for a quick, expedited purchase.

2. Pathing reports

Path analysis is one of the 5 options available in the Analysis Hub section. As Krista Seiden rightfully swoons in her Aug’19 article, pathing reports are truly a godsend and highly desired upgrade from Behaviour Flow reports in standard Google Analytics. When you open one from the sidebar, here’s what you might see:

Fig 3. The clean slate of a Path Analysis report, created using the Analysis Hub

I know, for standard GA users accustomed to creating Custom Reports or navigating Behaviour Reports, this feels like ~a whole new world~. To break it down:

• Main report (right panel). Where the magic happens. A default report will contain 3 steps automatically generated for you; however I would recommend clicking on “Start Over” at the top right and starting afresh with the blank canvas above. Aside from relieving your eyes from sensory overload, you have the option of working backwards from an Ending Point as well.
• Variables (far left panel). Start here by choosing the dimensions and metrics you want to consider. Click the “+” icons to open a checklist which you can tick and/or deselect your options. You can also choose/create the segments you wish to explore.
• Tab Settings (left panel). You will probably use this a bit later. Suffice to say that this is where you can do the more detailed functions like adding segments and breakdowns (a feature not available in Behaviour Flow reports).

To give you an example, I’ll be using the Ending Point of Sparkline’s Digital Analytics Immersive page. I’m being old school here by using page titles for nodes, but feel free to try events out. In fact, why not both? Mix and match the nodes you want to examine along your path, by taking your pick from the drop down list under each Step.

Fig 4. A simple Sankey diagram illustrating the most popular paths leading up to an Ending Point

In the example above, I examined the most popular path users take to reach our lovely course page. Armed with these insights, I can now work with the web dev and content team to ensure links along popular pathways have clear CTAs and are appealing to users interested in our education programme.

Sankey diagrams can also be difficult to read, so another feature tweak I’m enjoying is being able to expand AND minimize paths as you wish by clicking on the blue bars. With more mature sites and apps, you will see endless permutations… Instead of spending your Friday night trying to untangle this complex web (pun not intended), you could just skim the fat and focus on the ones with the most traffic and/or impact.

3. Cross-platform report

You can find this last report under the Technology section. While there isn’t as much detail as the other two (yet), what I like is the nifty pie chart that quickly lays out the platform usage and overlaps for your users. This is what marketers are looking for: a clear understanding of how users are interacting with the different touchpoints of the brand.

Fig 5. The cross-platform Venn diagram as seen in Technology reports with both App and Web data streams

After examining the pie chart and experimenting with segments, you can then take a quick look in the “New Users by Platform” report. By expanding the report, you will see a mix of charts and tables similar to the “Event count by event name” report discussed earlier on. Take time to explore secondary dimensions here by clicking on the “+” icon in the table, just beside the “Platform” column header.

Hopefully we will see more functionalities baked into this report as GA4 develops. As of now, you will either have to make do with either the categories shown (Web, iOS and Android), or write custom code in BigQuery to include other platforms and devices that might be more relevant to your target audience.

Closing thoughts

I hope that gives you a good glimpse of what you can find and use within GA4. As alluded to, you can expect much more to come soon. In the meantime, I would recommend you to set it up in tandem with your current App and Web properties, just so you can get your hands dirty and have a good grasp of “the future of Google Analytics”.

To set your GA4 property up, you can look at guides from Krista and Simo, the former being more up to date whereas the latter containing more snippets of information. Bounteous has a comprehensive piece that breaks down the reports in more detail; LovesData’s video walkthroughs are also recommended for visual learners.

Never stop exploring and see you in our next article!

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