How to Export Google Analytics Historical Data

With Universal Analytics (UA) officially phased out, you might be wondering what happens to the years of valuable website data you've collected. The good news is that you can still access and export your historical data - but for a limited time. This guide will walk you through the essential methods for exporting your Universal Analytics data, ensuring you don't lose those critical insights for future analysis and year-over-year reporting.

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Why You Absolutely Should Export Your Historical GA Data

On July 1, 2023, Universal Analytics properties stopped processing new data. While you can currently still access the interface and your old reports, Google has stated that this access is temporary and all UA data will eventually be deleted permanently. Losing this data means losing the ability to answer key questions about your business's past performance.

Here’s why saving that history is so important:

• Long-Term Trend Analysis: How has your traffic grown over the last five years? When do seasonal peaks and valleys typically occur? Your historical data holds the answers, allowing you to spot long-term patterns that inform future strategy.
• Year-over-Year (YoY) Benchmarking: Comparing this month’s performance to the same month last year is a fundamental business practice. Without your exported UA data, YoY reporting becomes impossible once Google deletes it.
• Understanding Past Successes: What were your most successful blog posts or marketing campaigns from three years ago? Having a record allows you to revisit what worked and apply those learnings today.
• Building a Cohesive Data Narrative: While GA4 is the future, your business journey didn’t start in 2023. By exporting your UA data, you can (with some effort) stitch it together with your new GA4 data to create a more complete picture of your performance over time.

Essentially, not exporting your data is like throwing away your business's old financial records. You might not need them every day, but when you do, they’re indispensable.

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Method 1: The Quick and Easy Manual Export

The simplest way to save your data is by manually downloading reports directly from the Universal Analytics interface. This method is perfect for saving top-level summaries or specific, high-value reports without needing any technical skills.

It's best suited for saving key performance indicators (KPIs) and getting a general overview, but it can be time-consuming if you need to export dozens of reports.

Step-by-Step Instructions:

1. Log in to Universal Analytics: Navigate to the correct UA property and view that you want to export data from. Make sure you haven't accidentally selected a GA4 property.
2. Open the Report You Need: Go to any standard or custom report you want to save. For example, let's say you want to save your top traffic channels. You would navigate to Acquisition > All Traffic > Channels.
3. Set Your Date Range: In the top-right corner, select the date range for the data you want to export. To get the full history, you might set a custom range from the day you installed UA through June 30, 2023.
4. Adjust the Row Count: At the bottom-right of the report table, find the "Show rows" dropdown. To capture as much data as possible in one export, set this to the maximum value (often 5,000).
5. Click 'Export': In the upper-right corner of the screen, just below the date range, you'll see an "EXPORT" button. Click it.
6. Choose Your File Format: You'll be given several options:

Repeat this process for every key report you want to save, such as top landing pages, goal completions by source, and user device types.

Pros and Cons of Manual Exports

Pros:

• Extremely simple, no technical expertise required.
• Fast for saving a few high-level reports.
• Multiple format options to suit your needs.

Cons:

• Time-Consuming: Repeating this for dozens of reports and date ranges is tedious.
• Data Sampling: If your site had high traffic, UA may have sampled your data to generate the report. Exported reports will contain this sampled data, not the full, raw dataset.
• Row Limits: Even with the row count set to 5,000, you might not capture long-tail keywords or pages if your site has a lot of content. The API has its own limits, too.

Method 2: The Automated Approach with Google Sheets Add-ons

If the manual process sounds too slow and you need more granular data, a Google Sheets add-on is your best friend. The official "Google Analytics" add-on lets you pull data directly from the UA API into a spreadsheet, giving you more control and automation.

This method is ideal for marketers and analysts who are comfortable working in spreadsheets and want to pull specific combinations of dimensions and metrics that may not exist in a standard report.

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Step-by-Step Instructions:

1. Install the Add-on: Open a new Google Sheet. Go to Extensions > Add-ons > Get add-ons. Search for "Google Analytics" and install the official add-on from Google. You’ll need to grant it permission to access your Google account.
2. Create a New Report: Once installed, go to Extensions > Google Analytics > Create new report. A sidebar will appear on the right.
3. Configure Your Report:
4. Run the Report: Click "Create Report." This will add a new sheet named "Report Configuration." Go back to Extensions > Google Analytics > Run reports. The add-on will query the API and populate a new sheet with your requested data.

To avoid sampling, you can break up your requests. For example, instead of running one report for the last five years, run separate reports for each year. This sends smaller requests to the API, which are less likely to be sampled.

Pros and Cons of the Add-on

Pros:

• More efficient than manual exports for large amounts of data.
• Gives you full control over the exact dimensions and metrics you export.
• Helps mitigate data sampling by allowing for smaller, batched requests.

Cons:

• Has a steeper learning curve, you need to understand metrics and dimensions.
• Still subject to the underlying GA API quotas and limitations.

Method 3: The Professional Grade Option: Exporting to a Data Warehouse

For businesses that are serious about data, the gold standard is exporting the raw, unsampled data to a data warehouse like Google BigQuery. If you were a Google Analytics 360 (the paid enterprise version) user, you may have already had a native integration sending your data to BigQuery. If so, your historical data is already safe.

For standard UA users, this native option wasn't available. The best path was (and still is) to use a third-party ETL (Extract, Transform, Load) tool like Supermetrics, Stitch, or Fivetran. These platforms act as a bridge, pulling your data from the Google Analytics API and loading it into a destination of your choice.

The General Process:

1. Set Up a Data Warehouse: You'll first need a destination for your data. Google BigQuery has a generous free tier and is a popular choice.
2. Choose an ETL Tool: Sign up for a service like Supermetrics for BigQuery.
3. Connect Your Sources: In the ETL tool's interface, authenticate your Google Analytics account (the source) and your BigQuery project (the destination).
4. Configure the Data Transfer: Define which dimensions, metrics, and reports you want to continuously pull from UA and send to BigQuery.
5. Backfill Your Data: Run a one-time "backfill" job within the tool. This will query the GA API for all your historical data and load it into your BigQuery tables.

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Pros and Cons of a Data Warehouse Approach

Pros:

• You get the most complete, unsampled, and granular data possible.
• Your data is centralized and secure for any future analysis you might need.
• Highly scalable and can be combined with data from other sources (e.g., your CRM, ad platforms) for holistic reporting.

Cons:

• Technically complex and requires some knowledge of data warehousing concepts.
• Involves costs for the ETL tool and for data storage/querying in BigQuery (though often modest for many businesses).

What Data Should You Prioritize Exporting?

It can feel overwhelming to decide what to save. Start by focusing on the reports you checked most often. Here's a checklist to get you started:

• Audience Overview: Monthly reports of Users, New Users, Sessions, Pages/Session, and Avg. Session Duration. Be sure to include dimensions like Device Category, Country, and City.
• Acquisition Channels: Your Acquisition > All Traffic > Source/Medium report is critical. Export this on a monthly basis with metrics like Sessions, Users, Bounce Rate, and Goal Completions.
• Top Landing Pages: Found under Behavior > Site Content > Landing Pages. This tells you which pages were the most effective at drawing in traffic.
• Top Content: The Behavior > Site Content > All Pages report shows your most viewed content over time.
• Goal Completions & Ecommerce: Any conversions data is non-negotiable. If you're an ecommerce store, this includes Transactions, Revenue, and Ecommerce Conversion Rate. Be sure to segment this by Source/Medium.

Final Thoughts

Preserving your Universal Analytics data is a critical step for ensuring you have a complete history of your business's online performance. Whether you choose a simple manual download or a more robust warehouse solution, taking action now ensures you’ll have the benchmarks and trends needed to make smart decisions long after the UA interface is gone for good.

Dealing with historical data exports and then trying to connect it with live data from GA4 and other platforms is exactly the kind of manual work that consumes countless hours. We built Graphed to solve this by seamlessly connecting to all your data sources - including Google Analytics and Google Sheets where you may have saved your exports. You can instantly visualize all your marketing and sales data in one place, using simple, natural language to create dashboards and reports without the headache.