[UA→GA4] Archive your Google Universal Analytics data

As the July 1, 2024, deadline for Google Analytics 4 (GA4) migration approaches, it's crucial to prioritize archiving your historical Google Universal Analytics (UA) data. If you used to rely on UA for tracking and analyzing your website data, it’s crucial to take steps to preserve your data and ensure a smooth transition to GA4.

Follow these 4 steps and utilize the best archiving method for your needs.

Step 1: Make a Plan

(a)? Determine Important Data

1. Identify Key Data: Focus on data you regularly use, such as conversion and sales metrics.
2. Compile a Data List: Create a comprehensive list of data points to archive.

(b) Decide on Data Retention Period

1. Historical Data: Assess whether you need data going back nearly 20 years.
2. Recommended Minimum: Consider archiving data from at least 2018 onwards to include pre-pandemic data.

(c) Review Cadence

1. Reporting Frequency: Reflect on how often you review data (weekly, monthly).
2. Organize Data: Structure the data into time increments based on your review frequency.

Step 2: Choose an Archiving Method

Option 1: Manual File Downloads

• Pros: Simple, free.
• Cons: Labor-intensive, limited to 5,000 rows, hard to access later.

Process:

• Access each report in UA, adjust date, dimension, and metric settings.
• Change rows to 5,000, export to Google Sheets, Excel, or CSV.
• Repeat until all data is downloaded.

Option 2: Google Sheets with Google Analytics Add-on

• Pros: User-friendly, free, quick.
• Cons: Timeframe restrictions, data sampling issues, cell limitations.

Process:

• Create a Google Sheet, add the Google Analytics add-on.
• Build and run reports using the add-on’s interface.
• Address sampling by splitting data pulls and managing sheet limitations.

Option 3: Google Analytics API

• Pros: Fast data retrieval.
• Cons: Requires development skills, sampling issues, API quotas.

Process:

• Utilize development resources to pull data via the Google Analytics API.
• Configure API calls based on your archiving plan.

Option 4: BigQuery

• Pros: Easy data access for reporting, enhanced data insights, flexible.
• Cons: Complex setup, potential costs, technical resources needed.

Process:

• Set up BigQuery and export data from UA to BigQuery.
• Use SQL queries to access and analyze the archived data.

Step 4: Ensure Comprehensive Archiving

• Verification: Double-check that all planned data has been archived.
• Consistency: Ensure that data integrity is maintained throughout the process.

By following these steps, you can ensure that your organization retains essential historical data from Universal Analytics, enabling continued insights and reporting capabilities after the transition to GA4.

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