How to Export Your Universal Analytics Historical Data

Bye, bye Universal Analytics!

Last year in July, Universal Analytics ceased processing new data and users will soon permanently lose access to the UA interface on July 1, 2024. By this time, we assume that you have already switched to the new Google Analytics 4 as backup for website tracking and measurement.

Say you have been living under a rock. You might notice that you are now using the GA4 property. It’s because Google has automatically created the Google Analytics 4 for you starting March 2023. When applicable, it reused existing site tags that are also present in the new analytics iteration. GA4 contains new data retention limits

One way or another, there could be a benefit to accessing your UA historical data before it gets deleted a few days or weeks after July 1, 2024. Which is why we prepared this handy guide to exporting your Universal Analytics through various options.

Let’s start!

Manual Export of Universal Analytics Data

This is perhaps the most straightforward way to retain your UA data, but can be very tiresome. Be extra careful about exporting large data sets as it could run into some restrictions during the process, lest you’ll receive an incomplete record of your data. This also requires more reckoning on how to organise the files, its storage location, as well as the naming system.

Here’s how you can manually export all your data from Universal Analytics:

Step 1: Access Google Analytics

• Log in to your Google Analytics account.
• Ensure you have administrative access to all the properties and views from which you want to export data.

Step 2: Prepare for Data Export

• Navigate to each property in your Google Analytics account.
• Select the relevant view for each property.

Step 3: Export Data

• For each view:
  • Go to the "Reports" section.
  • Select the standard reports you wish to export or create a custom report to include all the data you need.
  • Set the date range to cover the entire period for which you want to export data.
  • Click on "Export" (usually found at the top of the report) and choose the Excel format (XLSX or CSV).

Step 4: Organise Your Files

• Repeat the export process for each view within each property.
• Save the files with clear, deive names indicating the property, view, report type, and date range.

Step 5: Store Data on Drives

• Create folders on your Google Drive or another cloud drive service to match the organisation of your GA properties and views.
• Upload the exported Excel files to the corresponding folders.
• Ensure your drive is secure and that you've set up appropriate sharing settings.

Export using a third-party data connector

Power My Analytics, Supermetrics, Analytics Canvas - there’s a myriad of third-party tools you can use to import data from Universal Analytics to your preferred database, which is based on your existing data tools, budget, and interface preferences.

An amazing thing about data connectors is they can consolidate data from different platforms. You can streamline your data aggregation process and it eliminates the need for manual imports. As you know, a lot of things can go wrong when you manually import/export huge volumes of data, so a fit-for-purpose automated tool can help you move and update your data more frequently, and with less room for errors.

Export via Google Spreadsheets Add-On

Google developed the Google Analytics Spreadsheet Add-on as another healthy alternative to export data from your UA properties into Google sheets. Because Google Sheets is relatively easy to use and navigate, it gives users more latitude to analyse their data more rigorously without the encumbrance of exploring new UI, to create customer reports, and even to visualise insights.

More recently, there’s a new version of this add-on - Reports Builder for Google Analytics. However, there are reports that it has fewer capabilities available and has challenged many users about its ease to use.

There you have it! At the end of the day, the best method for exporting your UA data depends on your resources, preferences, and future needs. Seeing that you want to deliver accurate reporting to the business, it’s imperative to think long and hard about the option you will select in areas like formatting, capability to automate and customise views, data size, and interoperability with your existing tools and systems.