How to Get UA Google Analytics

If you're trying to find your old Universal Analytics (UA) data, you might have noticed the interface is gone. Google officially shut down access on July 1, 2024, meaning you can no longer sign in to view your reports or use the API to pull data. This article will walk you through the options you have for accessing your historical UA data and what to do with it now.

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So, Where Did Your UA Data Go?

Google’s shutdown of Universal Analytics happened in two stages. On July 1, 2023, UA properties stopped processing new traffic. For a full year after that, you could still access your historical data in the UA interface. The second stage was July 1, 2024, when Google sunset the interface and the API for good.

So, where is your data? The short answer is: it’s wherever you saved it. If you never exported your data from the Universal Analytics interface or set up a backup solution before the final shutdown, that data is permanently gone and cannot be recovered. However, if you did take steps to preserve your data, it likely exists in one of the formats we'll cover below.

It's important to remember that any data you did manage to save is now a static, historical archive. It won't be updated, but it remains incredibly valuable for year-over-year analysis, understanding long-term trends, and benchmarking performance against your current Google Analytics 4 data.

Method 1: Using Official Google Export Options

Before the full shutdown, Google provided a few standard ways to get your data out of the Universal Analytics platform. Your options depended on whether you were using the free version of UA or the paid enterprise version, Analytics 360.

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Exporting to BigQuery (For Analytics 360 Users)

If you were an Analytics 360 customer, you had the option to link your UA view directly to Google BigQuery, which is Google Cloud's data warehouse. This was the most comprehensive way to back up your data because it provided hit-level, unsampled data. If you had this connection configured, your historical UA data is already safe and sound in your BigQuery project. You can query it directly using SQL, connect it to a BI tool like Looker or Power BI, or even use it as a data source for advanced analysis and data science projects. This method preserved the most granular version of your data, but it was only available to enterprise users.

Manual File Exports (For All Users)

For the vast majority of users on the free version of Universal Analytics, the only option was to manually export individual reports as files. This was a time-consuming process but was the go-to method for saving key website performance data. This process involved:

• Navigating to a specific report in the UA interface (e.g., Channels, All Pages, Source/Medium).
• Setting the date range for the data you wanted to save. For year-over-year reports, this meant exporting data one year or one month at a time.
• Increasing the number of rows shown to the maximum (5,000) to get as much data as possible in one file.
• Clicking the "Export" button and choosing a file format, such as CSV, Excel (XLSX), or Google Sheets.

The biggest downside of this method is its fragmentation. You likely have dozens of separate files, one for each specific report and date range you remembered to save. Furthermore, these exports contained aggregated, and often sampled, data - not the raw, hit-level data. It's better than nothing, but it makes comprehensive analysis a real challenge.

Using the Google Analytics Spreadsheet Add-on

Another popular option was the official Google Analytics Spreadsheet Add-on for Google Sheets. This tool allowed you to pull UA data directly into a spreadsheet by configuring reports within Sheets itself. You could schedule these reports to run automatically, which made it a low-effort way to create a historical backup over time. If you used this add-on before the shutdown, you might have Google Sheets files containing a significant amount of your historical data. However, since the add-on relied on the UA API, it ceased to function after July 1, 2024. Any report configurations you had will now return errors if you try to run them.

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Method 2: Relying on Third-Party Data Connectors

Many businesses already used third-party tools to get their marketing data out of various platforms and into a central location for reporting. If your team was using one of these tools, there’s a good chance it created a backup of your UA data for you.

ETL and Data Pipeline Tools

Tools like Supermetrics, Fivetran, Stitch, and Funnel.io are designed to extract data from sources like Universal Analytics and load it into destinations like Google Sheets, BigQuery, Snowflake, or another data warehouse. They essentially act as data pipelines. If you had a connector like this running, it was continuously pulling your UA data and storing it in your chosen destination. That data is still there and accessible. The process was automated, meaning you have a consistent and fairly comprehensive historical record without needing to perform manual exports.

Turnkey Dashboard and Reporting Platforms

Other platforms, like Databox or DashThis, connect to your various data sources to build reports and dashboards directly within their application. Many of these tools have historically stored the data they pull from sources like Universal Analytics. If you used a platform like this for your marketing reporting, log in and check to see if your historical UA dashboards and data are still accessible. The platform may have saved the data on its own servers, giving you an inadvertent backup.

What to Do with Your Exported UA Data Files

So, you’ve found a folder full of CSVs or a Google Sheet with your old UA data. What now? Your data is siloed and static, but you can still make it useful for analysis.

1. Consolidate and Clean Your Data

Your first step is to bring your fragmented files together. If you have multiple CSV exports for the same report but different time periods (e.g., Channel-Report-2022.csv, Channel-Report-2023.csv), you'll need to combine them into a single file or tab in a spreadsheet. As you merge the data, pay attention to cleaning:

• Consistent Headers: Ensure the column names are identical across all files before you merge them.
• Data Types: Check that dates are formatted as dates, and metrics like Sessions and Users are formatted as numbers.
• Remove Duplicates: If your date ranges overlapped in your exports, you may need to remove duplicate rows.

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2. Analyze the Data in a Spreadsheet

Once you have a clean master file for a specific report (like your channels data), you can start analyzing it using the tools in Excel or Google Sheets. Pivot tables are your best friend here. For example, you could create a pivot table to see sessions by channel for each month over a two-year period. From there, you can create a simple line chart to visualize trends over time and identify sources of seasonality in your traffic.

3. Visualize Your Data in a BI Tool

For more flexible reporting, you can connect your consolidated Google Sheet to a free data visualization tool like Looker Studio (formerly Google Data Studio). Simply create a new data source in Looker Studio and select "Google Sheets." From here, you can build interactive charts, graphs, and tables from your historical UA data. You can recreate some of your favorite old UA reports to have on hand for quick reference. The primary drawback here is that this dashboard will be disconnected from your live GA4 data, forcing you to check two different places to see the full picture of your performance.

Final Thoughts

Getting your hands on historical Universal Analytics data today completely depends on whether you backed it up before the July 2024 shutdown. If you did, your data likely lives in BigQuery, a collection of CSV files, Google Sheets, or a third-party reporting tool, where you can still use it for valuable trend analysis. We know firsthand how frustrating it is to have your historical performance data stranded in offline files while your new data streams into GA4. Instead of wrestling with spreadsheet exports and trying to manually stitch old and new reports together, you can bring it all into a single, unified view. Within Graphed, we make it easy to connect data from a Google Sheet alongside your live data from GA4, letting you use simple conversational language to build dashboards and ask questions across your complete historical and current performance.