How to Archive Google Analytics Data

Your old Google Analytics data is about to disappear forever. After shutting down Universal Analytics (UA) in 2023, Google will permanently delete all historical data associated with those properties starting July 1, 2024. This article will show you exactly how to archive your Google Analytics data so you don't lose years of valuable business insights.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Why You Need to Archive Your Universal Analytics Data - Now

For over a decade, Universal Analytics was the primary tool businesses used to understand their website performance. That data contains the complete history of your digital growth, seasonal trends, and marketing campaign performance. Losing it means you lose the ability to perform crucial year-over-year analysis or benchmark future performance against your historical patterns.

The deadline to save this data is real and fast approaching. After July 1, 2024, you will no longer be able to access your Universal Analytics properties or the data within them. It will be permanently deleted with no chance of recovery. Taking a few proactive steps now to export and save this information ensures you retain your business's historical record for future strategic planning.

Choosing Your Archiving Method

There are a few different ways to save your GA data, ranging from quick and simple to more technical and comprehensive. The right method for you depends on your technical comfort level, the amount of data you have, and how you plan to use it in the future.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

Method 1: Manual Exports (The Quick & Dirty Approach)

The most straightforward method is to manually export individual reports directly from the Google Analytics interface. This involves saving each report you care about as a PDF, CSV, or Google Sheets file.

This approach is best for businesses that only need to save a few key high-level reports, like an overview of annual traffic sources or top-performing pages. It’s non-technical but extremely repetitive.

How to Manually Export Reports:

• Step 1: Log in to your Universal Analytics property. While you can't see new data, you can still access historical reports.
• Step 2: Navigate to a specific report you want to save. Good examples include:
• Step 3: At the top right of the report, select your desired date range. To get everything, you might need to export data one year at a time due to potential sampling or row limits.
• Step 4: Below the date range, click the "Export" button.
• Step 5: Choose your preferred file format.
• Step 6: Repeat this process for every single report, dimension, and date range you want to keep.

Pros: Easy to do, requires no special tools.

Cons: Extremely time-consuming, not scalable for large amounts of data, leaves you with dozens of separate files, and you lose all report interactivity.

Method 2: Google Sheets Add-on (The Balanced Approach)

A more powerful and scalable method is using the official Google Analytics Spreadsheet Add-on for Google Sheets. This tool lets you query the Google Analytics API directly from a spreadsheet, allowing you to pull specific combinations of metrics and dimensions for any date range.

This is the recommended method for most businesses as it provides more flexibility and control than manual exports without requiring you to write any code.

How to Use the Google Sheets Add-on:

• Step 1: Open a new Google Sheet.
• Step 2: In the menu, navigate to Extensions > Add-ons > Get add-ons. Search for "Google Analytics" and install the official add-on made by Google.
• Step 3: Once installed, go to Extensions > Google Analytics > Create a new report. A configuration sidebar will appear on the right.
• Step 4: Give your report a name (e.g., "Monthly Traffic by Channel - All Time"). Then, select the specific Google Analytics Account, Property, and View you want to pull data from.
• Step 5: Now, define what data you want. You have to select your desired "Metrics" (the numbers you want to measure) and "Dimensions" (how you want to segment those numbers). For example:
• Step 6: Click "Create Report." This will create a new sheet called "Report Configuration." Here you can fine-tune your request, setting specific date ranges (like 2012-01-01 to 2023-06-30), and adding filters or sorting preferences.
• Step 7: Once your configuration is set, go to Extensions > Google Analytics > Run reports. The add-on will now query the API and populate a new sheet with your requested data.

Pros: A more automated and detailed way to export data, allows you to pull custom data sets, and it's free.

Cons: Has a bit of a learning curve, you're limited by API quotas which can be an issue for very large sites, and the result is a raw data table that needs further work to visualize.

Graphed

Build AI Agents for Marketing

Build virtual employees that run your go to market. Connect your data sources, deploy autonomous agents, and grow your company.

Build Your First Agent

Method 3: Third-Party Tools & API (The Developer Approach)

For maximum control and the most comprehensive archive, you can use the Google Analytics API directly. This typically involves writing a script (e.g., in Python or R) to programmatically pull data and save it to a database or data warehouse like BigQuery. Some third-party ETL (Extract, Transform, Load) tools can also automate this process for a fee.

This approach is designed for developers, data analysts, or businesses with access to technical resources. It's overkill for most small and medium-sized businesses but is the most robust way to create a complete and usable data archive.

Pros: Fully automated, completely customizable, and provides the rawest, most granular data possible.

Cons: Requires coding skills and an understanding of APIs, takes significant time to set up, and may incur costs for data storage or tool subscriptions.

What to Do With Your Archived Data

Simply having the data isn't enough, you need to make it usable. A folder full of 100 disconnected CSV files isn't very helpful when you need a quick answer.

1. Organize Your Files

If you used the manual export method, create a logical folder structure immediately. Organize your exported files by the report type and date. For example: Google Analytics Archive/Acquisition Reports/Channel Performance - 2022.csv.

AI Agents for Marketing

Crash Course

Graphed

Free PDF · the crash course

AI Agents for Marketing Crash Course

Learn how to deploy AI marketing agents across your go-to-market — the best tools, prompts, and workflows to turn your data into autonomous execution without writing code.

Download the PDF

2. Prioritize Key Reports

You probably don't need to save every single report available in GA. Focus on the data that has historically provided the most value to your business decisions. This usually includes:

• Audience Overviews: Monthly trends of Users, Sessions, and Bounce Rate.
• Acquisition Reports: Traffic breakdown by Channel, Source/Medium, and major Campaigns.
• Behavior Reports: Your top 100 Landing Pages and All Pages.
• Conversion Reports: Goal completions by channel and page (if applicable).

3. Visualize Your Archive

Raw data tables can be hard to interpret. To make your archive useful for at-a-glance insights, connect it to a visualization tool. If you exported your data to Google Sheets, you can easily connect that sheet as a data source in Google Looker Studio (formerly Data Studio). This allows you to recreate some of your key dashboards, build interactive charts, and actually explore your historical trends without having to sift through spreadsheets manually.

Final Thoughts

Saving your Universal Analytics data before the July 1, 2024, deletion deadline is a critical, one-time task to preserve your business's history. Whether you choose fast manual exports for key reports or use the Google Sheets add-on for a more detailed archive, taking action now ensures you retain valuable context for future growth.

The whole scramble illustrates a bigger problem with modern reporting - data is siloed and manual work is required to get a clear picture. At Graphed, we’ve built a solution to this problem by connecting your live data sources like Google Analytics 4, your ad platforms, and your CRM in one place. Instead of dealing with manual CSV exports, you can simply ask questions in plain English and instantly get real-time dashboards and reports, so you can focus on insights instead of tedious data wrangling.