As you may know, Google Analytics is deprecating support for the 13+-year-old Universal Analytics. After it stops collecting data in July of 2023, it officially will be deleting account data one year later in July of 2024.
Go through the 5 stages of grief (see below), then get to work. As the clock runs out on the year, consider the types of requests you start getting for historical data from Universal Analytics. The greater the specificity that people have, the more likely you will need a more in-depth solution for saving UA data.
For example, if your team is only interested in questions like “what was the total views/users for March of last year?”, this kind of question can be solved with a basic option below. If your team are the type that want to know the exact number of campaign conversions that ranged a random timeframe from years ago, you may want to consider one of the more advanced options.
Ways to export your UA data from Google Analytics
Exporting your website data from Universal Analytics is an essential step for keeping a historical record of your analytics performance. Keeping track of your data over time helps you identify trends in user behavior and make informed decisions about how to optimize your analytics strategies. Whether you’re a beginner or an expert, it’s important to understand the different ways you can export data from Universal Analytics to maintain a historical record.
If you’re looking to create a historical record of your Google Analytics data, you’ll need to export the data from Universal Analytics. Fortunately, there are several ways to do this. Here are a few options:
Better Than Nothing Export
Go through the major reports of Audience, Acquisition, Behavior and Conversions and export data in a PDF for 1 year at a time and then save it in an organized series of folders by year. Note this won’t save exact numbers for each month but will give a general idea.
Quick tips to select the date and then choose the max rows because the PDF only snapshots
the information you see in the report. More details on this from Google: Export and share reports – Analytics Help.
Whole Whale tips
Select the date:
View by month:
View by day will be useless for future reference.
Select the max rows you need to save data:
Export to PDF:
Basic CSV Export
Export to CSV: One of the simplest ways to export data from Universal Analytics is to use the Export function within the interface. This allows you to export your data directly to a CSV file that can be opened in Excel or another spreadsheet program. To do this, navigate to the report you want to export, then click on the Export button at the top of the page. Before exporting, make sure you have the particular date range set. Google has a step-by-step process on exporting Universal Analytics data.
The next step is to store this in your company’s cloud storage (Microsoft 360 or Google Drive) in a structured manner. When exporting historical information from Universal Analytics, it’s important to establish a consistent file naming structure to ensure that your data is organized and easy to work with. Here’s an example of a file naming structure that you can use:
[Report Name] – [Date Range] – [Data Type].csv
For example, if you’re exporting a report on website traffic for the month of February 2022, your file name might look like this:
Website Traffic – Jan 2022 – Sessions.csv
In this example, “Website Traffic” is the name of the report, “Jan 2022” is the date range, and “Sessions” is the type of data being exported. By using this naming convention, you can quickly identify the contents of each file and easily sort and organize your data.
At the highest level use folders to group by year then by type GA Archive > [Property] > [Year] > [Report type].
Once you’ve completed naming the file in the structured manner and exporting to your company’s preferred cloud storage platform, we recommend that you visualize each of these reports in a table, widgets and/or bar charts in a Looker Studio dashboard (Sample UA export dashboard might be coming if people are interested let us know). Make sure to clean up the report spreadsheet before connecting it to your dashboard build.
API Code Export To Sheets
Use the API: Another option is to use the Google Analytics Reporting API to export data programmatically. This allows you to automate the process of exporting data and can be useful if you need to export large amounts of data or if you want to integrate your analytics data with other systems. With the Google Analytics Reporting API, you can also build dashboards and automate reporting tasks to display your data and save time. This requires being familiar with programming languages like Python or Ruby to use the API. Google provides a comprehensive guide on how to navigate the ins and outs of the Reporting API.
Google Sheets Export
Google Sheets Add-on: If you prefer to work with data in Google Sheets, you can use the Google Analytics add-on for Sheets. This add-on allows you to import data directly from Universal Analytics into Sheets, where you can manipulate and analyze the data as needed. To use this, you first need to install the add-on in Google Sheets, and add the add-on to your spreadsheet. From there, you can create reports from your connected Google Analytics property and run them on the spreadsheet. For more information on how to use the add-on, check out this starter guide from Google with a full Youtube tutorial.
Expert Full Data Export
This solution involves setting up a full data warehouse to save all data in a way that you can ask any questions needed as though Google didn’t delete your Universal Analytics.
Export Universal Analytics data with a third-party connector: Many data integration providers have solutions to this issue, one great example is the Supermetrics BigQuery Connector Add-on which leverages Google’s data warehouse with Supermetrics’ capabilities. This option can be beneficial for some who may not have the experience of using the Google BigQuery platform, as Supermetrics goes step by step in how to connect and export your Universal Analytics data to BigQuery.
Once your data has been filled into your BigQuery project, Supermetrics has been able to parse your data into different categories, such as Content, Events, Traffic, etc. Though this option provides a pipeline to continuously export your historical data, you would still need to connect this to a data visualization tool like Looker to see the full capabilities of exporting your Universal Analytics data. This solution may cost in the neighborhood of $100/month depending on how you set it up: Supermetrics for Looker Studio (Data Studio) Pricing.
The team at Whole Whale also has a method to handle exporting your historical Universal Analytics data using BigQuery. Talk to Whole Whale about a full BigQuery backup and visualization of your data in Looker Studio. This is the Cadillac option but if your organization is expecting the ability to accurately find past data from any time range this may be the option you need.
The 5 Stages of Grief When Google Analytics Deprecates Support for Universal Analytics
1. Denial: “It can’t be true, Universal Analytics is still a vital part of our data collection strategy. It just can’t be going away!”
2. Anger: “How dare Google retire Universal Analytics without warning? All these years of faithful service and this is how they repay us? Granted it’s been around for over a decade but still…!”
3. Bargaining: “If only we had updated our system sooner, maybe this wouldn’t have happened… People from other organizations didn’t have to go through this…perhaps if we appealed to Google directly for an exemption? Anything—we just want what we had before!”
4. Depression: “Why does nothing ever stay consistent in the world of digital analytics? What do I even do with all these new tags and tracking codes?!” *Buries head in pillow*
5. Acceptance: “While it may not have been the news we wanted, at least now we know where to go forward and start learning about the new systems Google is introducing…and hopefully by then the next one doesn’t come out as soon as this one did!”
Is it possible to import historical Universal Analytics into GA4?
No. Yes, we’re sure because we tried. A lot.
The only option would be to export full data into BigQuery/Snowplow and then do the same with your GA4 into a separate table and then visualize with something like Looker.
When is Google deleting old UA data?
According to alerts the date is still the end of 2023. Universal Analytics is going away. Even if you think they will move the date at the last second, you will still need a solution like one above.
Why is Google Analytics doing this?