Summary: This article outlines how to back up and retain historical Google Universal Analytics data, in light of the complete shutdown of the service on July 1, 2024.
Google Analytics has enjoyed a long shelf life as the leader in website traffic monitoring. First released in 2005, the third generation of the platform, commonly known as “Universal Analytics (UA)”, was released in 2012 and was used widely for ten years.
It has been over three years now since Google released its latest rendition of Google Analytics, dubbed “GA4”. GA4 brought many new features to the table and modernized how website and product owners visualize and report on website usage. But with great change came great sacrifice. The historical data stored in Universal Analytics is essentially incompatible with GA4, with no migration path available between the two. For close to two years, Google ran the two systems in parallel. This caused confusion and frustration, as many users continued to use the old version due to the learning curve of GA4.
That struggle came to a predictable end, however, when UA was officially retired from collecting new data in July 2023, forcing all users to adopt GA4. While Universal Analytics is no longer collecting new data, users still have access to the historical data. That changes July 1, 2024 when Google will completely shut down Universal Analytics.
If you have any interest in backing up your historical Google Universal Analytics data, now is the time to act. What follows is a general outline of some of the more popular approaches to preserving your past Google (UA) data.
If you’re looking for the trendiest, Google-recommended solution, BigQuery is it. BigQuery is Google’s premier “Data Warehouse,” allowing massive amounts of data to be stored and queried in a novel way compared to typical databases. This option offers the fewest limitations, combined with notable complexity. While not infinitely free, BigQuery does come with a generous 1tb worth of queries per month within their free tier plan, and with careful configuration, even large sites will find storing and accessing their past data to be priced well within reason.
If you’re already a paid Analytics 360 subscriber, a built-in API exists that can help connect your UA data and export it directly into BigQuery. If you’re not a 360 subscriber, you’re left with two choices, leverage a paid 3rd party application designed to bridge the gap, or export and import that data manually.
For smaller and lower-traffic sites, this option likely makes the most sense. Out of the box, Google UA allows direct exporting of views into the above file formats. For this article, we’ll focus on Google Sheets. Google Sheets offers a free cloud-based storage solution that, like Excel, is easier for most users to view and digest compared to a novel database system like BigQuery. Google Sheets has its limitations. For example, views that generate more than 50,000 to 75,000 rows will easily stall the cloud-based service, leaving many users forced to break their data up into multiple Google Sheets to achieve a complete picture of the past.
If you decide to take this route, choosing which data views to export can be the key to avoiding an unwieldy collection of Google Sheets. We recommend narrowing it down to areas you’ve previously found yourself reviewing every month. For example, most of our clients achieve this by focusing on Visitors by Day, Page Views, Traffic by Channel, Referrals, Source/Medium, and Conversion Data.
While there may be no direct connection between Google UA and BigQuery for non-Analytics 360 users, BigQuery and Google Sheets do play quite nicely together. If your ultimate objective is storage, Google Sheets offers a completely free long-term storage solution. And if your bonus goal was to leverage the power of BigQuery, by importing that exported Google Sheet data directly into BigQuery, you gain the power of both, timeless backups and powerful queried access to that data.
Most users will find Option 3 to be the most well-rounded cost-effective solution.
While looking at CSV Tables and writing your BigQueries can be amusing and useful, most users will quickly long for the days of useful reporting views, charts, graphs, metrics, and more. Google has this covered with its own “Looker Studio” (formally known as Google Data Studio).
Looker Studio offers the ability to visualize your stored data in ways even Google Analytics itself may have fallen short. It supports custom dashboards and reports, as well as sharing and collaborating.
Whether you opt for storing your data in BigQuery or Google Sheets, Looker Studio has the built-in ability to directly connect to either source, and you’ll be setting up dashboards and reports in no time. Looker Studio allows you to custom-tailor your reports around your unique product/website app conversion goals. Let us know if you’d like to see a separate article on how Looker Studio can be leveraged to enhance your standard Google Analytics dashboards.
But what about GA4, is your data safe at last?
Great question, the short answer is no, at least not by itself. Out of the box, GA4 comes with a shorter memory span than even UA had. Google’s commitment to providing year-over-year analysis of your traffic as a built-in feature of Google Analytics is seemingly over for good. Fortunately, however, solutions are in place to streamline how to create your own long-term retention and visualization plans, and we look forward to covering that here in a subsequent article. Stay tuned.
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