Google has announced that Universal Analytics (UA) will have its sunset – will be switched off, to put it straight – by the autumn of 2023. Enterprise users are given time to rescue their marketing analytics until the 1st of October; all others only until the 1st of July.
Google Analytics (GA4) should become the main data hub for all relying on Google tracking.
Although GA4 has a few proven advantages, the transition promises to be challenging. Let’s look at what is going to happen and how you can stay on the safe side.
A Brief History of The Co-Existence
Universal Analytics has existed since 2005 and has undergone a lot of changes. It has always been a reliable, but slightly complicated, tool; no wonder Google decided to make a hard cut and retire it completely.
GA4 has been nursed since 2017 and was launched in 2020 to get people accustomed to it. GA4 is an integral part of Google Workspace.
GA4 vs Universal Analytics: Where the Differences Lie
The complicated user interface was not the pressing reason for Google to abandon one of its main products. Rather, it aimed to create a better tool. We have identified a few major differences that should change the lives of digital marketers for good.
Data Generation
Contrary to its predecessor, GA4 does not rely on cookies to grasp user interactions and generate data. Instead, events are triggered directly. Cookies are text files moved in the browser between metrics and dimensions. Events are way more precise for capturing the information.
As a consequence of this change, the new data model has to be implemented inside GA4.
Event-Based Data Model
UA has a session-based model at its core. Although hit types remained the smallest unit of analysis allowing for a considerable flexibility, they were bound to user sessions – restricted periods of time – that shaped the final reports.
GA4 departed from sessions and only left hit types – all called events now – to get rid of the distortion in the reports that was caused by comparing sessions of with different lengths. The new model should ensure more generalizable results.
Cross-Platform Tracking
Another consequence of the new way of data capture and a new data model is that you can compare performance of your digital business across platforms in a reliable way since the data has the same basis.
When you have an app that is accessible through the browser but also has a mobile version, GA4 can provide insights that were not possible with UA.
However, that does not mean that the same events will be captured both in a web browser and mobile application. Events are device-specific.
Less Work With Google Tag Manager
Universal Analytics, as we all know, only receives correct data if you correctly set up tags in Google Tag Manager. This used to require a lot of effort. The main promise of GA4 is that your engagement with Google Tag Manager will be reduced to a minimum. GA4 offers an exhaustive list of the automatically collected events and an opportunity to add other events you need to track. Google Tag Manager won’t be retired.
Private Data Is More Secure
Google announced that GA4 offers an improvement in regard to how user data is handled, e.g., no IP addresses will be saved. Instead, other methods are used to match user data without exposing their privacy is used.
Drawbacks of the Transition
That all sounds like a great deal. But there is a thorny pathway between the status-quo and this shiny future.
Your Historical Data May Be Gone
On the day you activate your GA4, it only starts consuming data that is generated after its activation. GA4 won’t have any historical data since UA and GA4 are completely disconnected. That means that tons of information will stay inside UA, and Google has not said none tells us for how long it will be kept accessible for.
Data Migration Is Help-Yourself
Google does not plan to launch any migration tool to help with moving data between the old and the new platforms. Users will be left alone with their data migrations.
Google silently implies that you should use Big Query. But it is not automatically set up to receive the data from either UA or GA4.
Besides, Big Query is more or less a data lake with a simple query tool but for the forthcoming migration, and we need more than that.
Differences Between Two Data Models
The data migration would mean more than just a one-time export-import operation since the data models on both ends are totally different.
You will need to re-shape your data before ingesting it to GA4.
Even Google recommends you to rethink your existing reporting model before actually migrating the data to GA4.
Data Import Limitations
Although GA4 allows importing external data – which UA does not – it has some limits. Apart from the fact that only manual data ingestions are possible.
For now, you can only import up to 10GB of data on the same day, and no more than 10 imports per day are allowed.
Fewer Default Reports
GA4 will have fewer default reports, i.e., the popular source-medium comparison will be gone. Google pushes you to use Big Query as it would allow you to design any report using SQL queries. Big Query does not have data visualization abilities, contrary to UA, although connecting it to Data Studio is a popular workaround.
Your Plan of Attack
15 months can rush past you very quickly, so be ready to start handling the transition soon enough.
Conduct a Report Inventory
We recommend starting with an inventory of your existing reports. That will allow you to understand which data you will need.
You will have to reach out to all possible stakeholders, discuss the forthcoming transition and make sure that nothing is overlooked and nothing is forgotten. The most difficult thing would be to find a new common ground with business users; that’s why it is important that you redefine the existing reports together.
Preserve Your Historical Data
You need to start gathering your historical data. UA may have collected a huge amount of data but it is often a bit difficult to get to the original data. Raw data is always preferable to extracting aggregated or processed data as you may not be completely aware of the logic behind certain calculations.
You need to keep in mind that UA only offers CSV exports. It means that you will have a lot of manual effort of configuring the exports, a semi-manual – if you are lucky to have someone to program this – effort of downloading CSV files, and you still have to store them before ingesting them into the new system.
Transform and Load?
Google invites you to find a common denominator for your old and new data models, so that you can match your historical data with the newly generated data.
But why do this transformation? We highly recommend you keep your old data in its original form and only merge it with the new data on-the-fly. All you have to do is to store ALL your data in one place and have a query engine that can pull it together when you need it.
Extract-Load-Transform With One Tool
Panoply is a data management platform with an optimized query engine.
It allows you to handle all three phases – extraction, transformation, ingestion – of your move from Universal Analytics to GA4:
- It has a UA connector that exports data from UA.
- It stores your data in a secure cloud.
- It enables data engineers to create custom data pipelines and data analysts to design custom reports.
- It will launch a GA4 connector before the Big Bang to supply your storage with GA4 data.
- Last but not least, Panoply can pipe data into any external visualization tool which is great for those who do not work with Data Studio.
So, any reason you’d export data from Google and reshape it only to ingest it back into Google?
With Panoply, you can have all data in one place, ready to be queried at any time without limitation. You can use our cloud data warehouse as a standalone product or as a bridge between both old and new Analytics and your favorite business intelligence tool.
Looking for more? Read The Analyst's Guide to Google Analytics 4.
