google analytics sampling

How to Avoid Sampling When Exporting Universal Analytics Data

Synopsis: Options are limited if you’re looking to avoid sampling when exporting your historical universal analytics data in preparation of the migration to GA4.  Our new tool, the Analytics Data Extractor (ADE), reliably and accurately extracts, stores and visualizes your historical Universal Analytics data and prevents your data from being lost.  Learn how you can back-up 5 years (or more) of accurate, completely unsampled data today!

What is Sampling in Google Analytics?

In Google Analytics, sampling is the process of selecting a subset of data from a larger set of data for analysis. This is done to speed up processing time and to reduce the amount of data that needs to be analyzed.

For example, if you have a website with millions of pageviews per month and you want to analyze user behavior on a specific page, Google Analytics may only sample a percentage of the total pageviews for that page. This allows the data to be processed more quickly, but it also means that the analysis is based on a smaller sample size and may not be as accurate as analyzing the entire dataset. In our agency’s experience, even a nominal amount of sampling can lead to significant discrepancies between the reported and actual data sets.

By default, Google Analytics will use sampling when analyzing large datasets, but you can adjust the sampling rate to get more accurate results. This is particularly important if you’re analyzing smaller subsets of data, such as specific user segments or conversion paths, where sampling can have a bigger impact on the accuracy of your analysis. To adjust the sampling rate, you can use the Sampling Level option in the report settings, but keep in mind, this option is only available in the Google Analytics interface.  It’s not an option that is available when exporting data to Excel, and that brings us to a much bigger issue facing digital marketers in 2023.

Sampling and the GA4 Migration

Google’s Universal Analytics will stop collecting data on July 1, 2023, and data will be permanently removed following the close of 2023 (the exact deletion date is TBD). Google is currently urging customers to export historical reports to prevent permanently losing their data.  

Unless you’re a GA360 customer, Google suggests manually downloading your GA data via Excel/CSV.  This is problematic because:

  • To pull unsampled data for multiple years, you would need to run hundreds of smaller reports and stitch them together.
  • Attempting to stitch together hundreds of reports would take significant time, and it will ultimately crash Excel and exceed Google Sheets’ data limits.
  • Most exported data for long date ranges will be sampled, making it highly inaccurate.

How to Avoid Data Sampling?

To combat this issue, we’ve spent the last six months trying to develop a solution to back-up historical Universal Analytics data while automatically avoiding sampling.  We’re excited to announce the launch of our new Analytics Data Extractor (ADE), which:

  • Accurately backs-up 5 years of data with no-sampling and 100% data accuracy.
  • Archives and store data in a cloud-based database (Google BigQuery).
  • Links archived historical GA3 data directly to Google’s Looker Studio (formerly Google Data Studio), where both pre-formatted and custom reports (with Excel exports) will be available.

Historical Universal Analytics data will be safely preserved and fully accessible through GDS for a large number of custom queries and entirely customizable date ranges.  The extraction process can be initiated as soon as you’ve made the switch to use GA4 as your primary reporting platform.  We estimate that most advertisers will be doing that in the April – June time period, and we are currently offering reservations to secure a date for the backup process. We have 5 critical data sets we’ve identified that will be backed up for 5 years, and additional custom data sets (up to 6 dimensions and 10 metrics per data set) can be extracted for an additional fee.

Learn more about how to avoid data sampling while exporting your historical universal analytics data at