A Guide to Archiving Your Universal Analytics Historical Data
As the deadline for another Google Analytics 4 migration project approaches, organizations using Universal Analytics properties need to prioritize archiving their historical data. On July 1, Google will delete all historical data from Universal Analytics properties, including for Analytics 360 customers. With just a month left until the deadline, it is crucial for organizations to make a plan and choose an archiving method to ensure they retain their valuable data.
Phase 1: Make a Plan
Before archiving data, it is important to decide what specific data is important to your organization. It is recommended to prioritize downloading data that you regularly refer to, such as conversion and sales data. Make a full list of the data you need to archive. Consider how many years of data you want to keep. While many organizations have been using Google Analytics since the mid-2000s, it may not be necessary to archive data from nearly 20 years ago. It is recommended to archive data from at least 2018 or so to ensure you have pre-pandemic data. Additionally, consider the cadence at which you review data and organize the data into specific time increments.
Phase 2: Choose an Archiving Method
There are four main options available for archiving your Universal Analytics data, each with its own pros and cons.
Option 1: Manual file downloads
This option is easy for almost all users to do and is free. However, it can be time-consuming and cumbersome. It may also be difficult to access the data for reporting later, and there is a limitation of 5000 rows.
Option 2: Download data to Google Sheets using the Google Analytics add-on
This option is fairly simple to implement for most users with spreadsheet experience. It is free and fast to download. However, it is restrictive to a set timeframe (e.g., monthly) and each sheet has total data limitations. It may also encounter sampling issues.
Option 3: Download data using the Google Analytics API
This option requires web development knowledge and resources. It pulls data quickly once set up but doesn’t solve the data sampling issue and has API quota limitations.
Option 4: Download data to BigQuery
This option is the best overall, as it allows for easy access to data later for reporting. It provides increased data insights and is the most flexible for data. However, it can be complicated for novices to set up initially and may involve fees for BigQuery. It may also require technical resources to set up and the involvement of an additional tool.
Phase 3: Ensure You’ve Captured It All
Before considering the project complete, it is important to double-check the archived data to ensure everything has been captured. On July 1, access to Universal Analytics data will no longer be available either through the API or the interface.
Archiving your Universal Analytics historical data is crucial to preserving valuable insights and trends. By following these recommended phases and choosing the appropriate archiving method for your organization, you can ensure that your data is securely stored for future analysis and reporting. Don’t wait until it’s too late – prioritize archiving your historical data now.
