Forewarned is forearmed when it comes to transitioning to Google Analytics 4. The more I research, explore and experiment with the platform, the more hurdles and nuances appear that I was not prepared for and more often than not have frustrated me.
Marketing folk, to avoid you going through the same unpleasurable experiences, I aim to use my journey with GA4 to give you a head start, and a heads up on what to expect so that it’s far less painful for you (and perhaps encourages you to explore alternatives to GA4 at the same time).
This article brings to light the myriad of additional analytics tools that you might (will) need to adopt in order to make sense of and visualise the website performance data you’re collecting. This may surprise many of you if you have solely logged into Google Analytics in the past to retrieve the metrics that matter to you.
First and foremost you will need a Google Analytics 4 property. You may already have a Google Analytics account, but the GA4 reporting suite is housed within a GA property.
If you’re new to Google Analytics entirely, then you’ll need to create an account first.
In the past (GA Universal Analytics), properties were identified by their UA IDs, and often businesses may have created them for every website domain they owned and operated. Similarly, they would be separate properties for apps and websites.
Sometimes you may have had multiple properties for the same website, but that’s not recommended (so let’s ignore that one for now).
With GA4, it is recommended to have one GA4 property, but within that property, you can now create data streams. Data streams should be created for each domain, iOS and Android app that you own and operate for the same business. In GA4 world, you’ll be able to combine the stats across all three which may be handy for cross-platform analysis.
Whilst you’ll be able to retrieve lots of juicy stats from within the GA4 property, you’re going to need to add the following additional platforms to analyse above and beyond short timeframes (e.g. more than 14 months)…
BigQuery is a serverless, multi-cloud data warehouse if you know what that means. If you want to analyse your data sets beyond a 14-month timeframe, you will need to send it to BigQuery, and then run some SQL queries to pull together a bunch of data from which you’ll need to visualise elsewhere (there cometh my next tool in the toolbox).
Hopefully, I’ve not lost you in that sentence, but it’s the sort of thing worth being forewarned about. GA4 was certainly built more attune to how developers work than marketers because it seems Google wanted to offer greater flexibility with data sets but forgot about who uses the platform the most!
BigQuery requires a Google Cloud account (so make sure you have one of these) within which you might need to attach your billing details. If you’re using Google Maps for example on your website, you may already have one of these accounts.
BigQuery access used to be free only to GA360 users, but due to the way GA4 has been built and the necessity to use BigQuery, Google has created a free-to-use sandbox for many of the day-to-day, low-usage queries.
This is still an area I’m getting to grips with, but from what I understand, it will only process data daily (rather than stream) and has by default, for free, 10 GB of active storage and 1 TB of processed query data each month.
GA4 projects appear within their sandbox, and whilst you’re only using the sandbox, you do not need to create a billing account, nor do you need to attach a billing account to the project. But I’m not yet sure how sufficient working in the sandbox will be for our normal use purposes. So be prepared to start paying for some analytics features.
I mentioned it briefly earlier, but in order to visualise data from BigQuery, you’re also going to have to add data visualisation software to your toolbox. Google Data Studio is a free tool to create and share dashboards and reports. If you have a Google account already, logging into datastudio.google.com will be relatively straightforward and looks a little bit like Google Drive.
Obviously, Google will make it ‘easy’ to tie in Google Data Studio with BigQuery and GA4, rather than 3rd party platforms like Tableau, Microsoft Power BI and Zoho Analytics, but you should check out whether other software solutions are better for your needs. The answer isn’t always Google!
You may also need Google Data Studio to recreate some of the reporting views and filters that you have become accustomed to in Universal Analytics. So don’t dismiss if any notion of using BigQuery puts you off, you might still need Google Data Studio anyway for simple analytics visualisation.
Possibly something you’re already using with Universal Analytics, but for those that aren’t, life will be a whole lot easier if you are working with Google Tag Manager to implement your analytics tags, and also to handle some of your cookie consent conditions.
Within Google Tag Manager there is the ability to use Consent Mode, which can help your business control analytics tag fires according to user consent preferences.
Google Tag Manager, does as the name suggests, it’s a tag management system. Created to give marketers more autonomy to implement tags and configure tracking on websites with less need to involve web developers. If you’re not using it, definitely check it out.
All of these Google products should work from a single sign-on with a Google account. Within them all, you should have the ability to add users to the accounts so that you can collaborate with colleagues and partners. Just make sure any which require administrative access, especially billing details, is set up from within an account assigned to an authoritative figure (or group email) for continuity of access.
I recently discovered a YouTube video from a helpful analytics guy (Loves Data) sharing the how-to for adding annotations to GA4 properties. If you didn’t know already, at the moment (August 2022), the ability to add annotations in your GA4 account is not without workarounds. There is no direct implementation like we’re used to Universal Analytics.
The suggestion was GA4 + Google Sheets + Google Data Studio + Google Calendar + Zapier.
Now that is a lot of platforms and accounts to manage for the simple task of adding an annotation. Let’s hope all the things that are missing from GA4 don’t have such convoluted workarounds as this.
So, also add Google Sheets, Google Calendar, Zapier and/or a chrome extension to your toolbox.
By the way, Zapieris a workflow automation tool that integrates web applications, and from a marketing point of view can transmit data between analytics platforms using triggers and zaps.
We’re massive fans of pulling out data from GA and visualising it in Google Sheets/Microsoft Excel-based tables and charts. Unlike Google Data Studio, extracting into sheets allows us to overwrite data if there are anomalies, present large data sets in tables with 000s of rows (for those who like the detail) and connect data sets from different platforms in an automated fashion.
To do this, for many years, we have used Supermetrics. Supermetrics is the connector which picks up all the marketing data you need and brings it to your go-to reporting, analytics, or storage platform. With the advent of GA4 we are still hoping to be able to use this software and process to continue interrogating data sets (albeit we won’t be able to extract more than 14 months in one go) and store longer data ranges. We can also retain synergy in reporting charts and tables as we transition from UA to GA4.
As time goes on I will likely add a few more instances to this list, so bookmark this blog and revisit it in the future!
As you can see, you’re going to need a whole lot of Google products to work with GA4 in the way it was intended. Not everyone wants to be beholden to one behemoth, but this one is certainly trying to make it easier to do so, and harder to break away, unless you go completely cold turkey and find a completely new analytics solution.
Hopefully, this article has made you appreciate the scale of change migrating to GA4 is going to be, and how you’ll need to tool up to get even a fraction of the visualisation and insights that you’ve been used to with Google Analytics.