Any report you want to view, you’ll have to create it yourself. You’ll leave the Google Analytics dimensions and metrics system, and you’ll have to do everything with SQL (SELECTs, Subselects, Withs, and Group Bys). It’s not that complex once you understand it, and there are some AIs capable of extracting almost any data in a short amount of time, but everything will become more artisanal and slower when you work in this system.
And finally, BigQuery is a paid service. You pay to store the data and for each query you run there. On a site with moderate traffic, the cost is very low and won’t reach €100 per month, no matter how advanced your analytics are. But on medium-sized and large sites, with significant traffic and campaigns, it’s not uncommon to spend over €500 per month on BigQuery.
An infographic to summarize them all
A while back at IKAUE, we created this short infographic summarizing all the aspects we discussed (and even a few more). We hope it serves as a reference to help you remember all the details of the different GA4 reporting systems and, ultimately, that it helps you better understand what you do and can do in GA4.
Download it and use it as a cheat sheet to further familiarize yourself with the different GA4 reporting systems.
Download the infographic on GA4 reporting systems
Conclusion
Understanding how GA4’s three reporting systems work is crucial to getting the most out of this tool.
In reality, the first two systems are comparable and complementary. BigQuery, on the other hand, is a more tailored solution geared toward working in data environments that are rarely easy to integrate with the other two systems:
Officially, you either work with GA4 reports or you work in BigQuery. The data doesn’t match between the two systems (due to the aforementioned limitations), so reporting in both at the same time can be both confusing and complex.
In short, the aggregated system is ideal for quick and efficient queries, while the granular system offers more detail when you need it. BigQuery, on the other hand, gives you full access to raw data, without limitations, but requires more effort to create reports. Choose the right system based on your needs and optimize your analysis to gain more precise insights.Do you want to be more productive when preparing reports? In today’s article, we’ll share a series of tips that have helped our analytics team become more productive and produce reports faster, without losing the level of customization we offer our clients.
CONTENTS
The reality of our consultants’ day-to-day work (both Digital Analytics and SEO) is that they have limited time to complete reports. Their main focus is on presenting the information that will truly interest our clients based on the analysis they have conducted, thus empowering them to make data-driven decisions.
In addition to not being an easy task, what makes it even more complex is the level of customization we offer in each report. Therefore, it was necessary to establish guidelines and learn some tricks that would allow you to be more efficient and agile when creating reports.
Most of the hacks we’ll share will be fairly generic, so even if you don’t use Looker Studio as a data visualization tool, we recommend you still try them out. I hope you get some ideas for your projects.
