Benard Kiplangat Data sampling in Google Analytics can negatively impact your data reporting. It can also be extremely difficult to avoid their drawbacks in your Analytics reports. The good news is that you can evade their limitations. And today, we will discuss the five ways to help you avoid data sampling in Google Analytics. So, let’s dive in!
Google Analytics is the heart of website and mobile analytics. With the help of Google Analytics, you can access essential tools and data points that provide useful insights for your data analysis. One of the essential features of Google Analytics is Data Sampling, which directly impacts how you view and handle your data.
Data sampling in Google Analytics can be beneficial. However, it often leads to data inaccuracies. If you need to work with unsampled data, this article will discuss the five ways you can use to avoid data sampling.
What is data sampling in Google Analytics?
If you are analyzing a large data set, it can be difficult or expensive to uncover meaningful information from the entire dataset. Therefore, to make the process faster, easier, and more effective, Google Analytics will take a subset of your data for analysis through Data Sampling.
How can you identify sampled data?
You can tell whether your data is sampled or not by observing the color of the shield icon at the top of your report. When the shield icon is green, the data you are looking at is unsampled. If you see a yellow shield, then your data is sampled.
You can also change the nature of your sampling to increase or reduce the sample size by selecting ‘Greater precision’ for a bigger sample size or ‘Faster response’ for a smaller sample size in the dropdown menu.
How does Google Analytics’ Sampling work?
As we said earlier, data sampling in Google Analytics aims to speed up the process of analyzing millions of data by using just a portion of your data to represent the whole. This happens especially when your data set exceeds the default threshold of 250,000, which is adjustable. Data sampling in Google Analytics activates automatically when you exceed this threshold.
When sampling is active, Google Analytics will identify the number of visits within the highlighted date range. Then, the percentage needed by the sampling rate is calculated based on the sampling setting.
When selecting data from the date range, it uses the sampling rate. For example, if you have a sampling rate of 50%, and a day like Saturday had 100,000 visits, it will select 50,000 visits at random.
| Monday | Tuesday | Wednesday | Thursday | Friday | |
| Total sessions | 400,000 | 100,000 | 200,000 | 420,000 | 300,000 |
| 50% sample | 200,000 | 50,000 | 100,000 | 210,000 | 150,000 |
| 20% sample | 80,000 | 20,000 | 40,000 | 84,000 | 30,000 |
When does Google Analytics sample data?
If you are using the free version of Google Analytics, there will be limited access to unsampled data when you exceed the threshold limit of 500,000 sessions.
There are two reasons why Google data sampling feature was developed: to save time and increase speed. Therefore, Google Analytics will sample data when the dataset involved is very large and may take too long to process. In this case, it will only pick a portion of the data to process.
Limitations of data sampling
There are two main reasons why data sampling may not be preferable:
- If you select a minimal sample size, you will not get a good representation of your data.
- As your website grows, the reports for your sampled data may become more inaccurate.
An example of why we do not fully trust sampled data is taking the example that you own an eCommerce store. You may realize that your Google Analytics reports are not matching with the actual sales data because of data sampling. In Google Analytics, you may be seeing a month’s revenue as $1 million, while the actual sales are $900K.
Sampling led to inaccurate sales data, which may lead to adverse financial effects if you make your decisions based on Google Analytics. So, it is crucial to know that what you get from a sampled Google Analytics report is estimated rather than the actual figures.
Another disadvantage of working with sampled data is that you may miss the chance to see things clearly as your data grows, thus increasing your chances of making risky decisions.
Remember, Google Analytics data sampling reports tend to be more inaccurate as your dataset grows. Therefore, you cannot make decisions for a large business based on reports that could be inaccurate or assumptive.
So, how can we get away with these limitations in data sampling? Let’s dive right into it!
5 Ways to avoid data sampling in Google Analytics
There are several options to choose from when you want to avoid data sampling. The option depends on the type of analysis you perform, the time you want to create the report, and your budget. Let us explore some of those options.
Use a smaller date range
Reducing the date range of your report is the fastest way to avoid data sampling. Therefore, it is reasonable to include fewer days if you need unsampled reports for your data.
The smallest date range you can have is a single day. A smaller date range will give you visits that are below 500,000. If your daily visits per day exceed 500,000, you will automatically get sampled data for your reports.
Therefore, you can always consider using it when you are in a hurry and need an accurate report for your data, as this is the easiest and quickest way to avoid data sampling.
Make your report simple
Simplification of your reporting also plays a crucial role in reducing data sampling in Google Analytics. Whenever possible, use the primary dimensions to improve data accuracy for your reporting.
We recommend checking out the standard reports to know whether they meet your needs. The standard reports include pre-processed data that is always unsampled in Google Analytics. These reports include:
Use a premium version of Google Analytics
Yes, it costs, but how valuable is accurate data? Using the premium Google Analytics allows data sampling to occur only when you get more than 100 million sessions within the range of your reports. If you have the budget and want to take care of a large-scale website, you can upgrade to Google Analytics 360, giving you higher limits and the ability to access and export large sets of unsampled data.
Use Dataslayer to get unsampled data from Google Analytics
You can access raw, unsampled data by sending data from Google Analytics to Google Sheets, Google Data Studio, or Google BigQuery. If you have not yet connected Dataslayer to your Google Analytics, here are the articles that will help you get started faster:
- Dataslayer for Google Sheets: Getting Started
- Getting Started with Dataslayer for Google Data Studio
- Dataslayer for Google BigQuery: Getting Started
Using Google Analytics API allows you to pull to your favorite data destination. However, doing it manually is time-consuming and may be prone to errors. That is why it is more efficient to use Dataslayer to pull your unsampled data to these destinations.
When you connect to these destinations using Dataslayer, you will have a bigger advantage for working with unsampled data for your reporting. You will also enjoy better data analysis that you may never get while using Google Analytics platform alone. So, go try out for free today!
Tip: Use Dataslayer for Google Sheets, Data Studio, & BigQuery to patch all your Google Analytics into these platforms and unlock powerful tools for your data analysis.
Upgrade to the new Google Analytics 4 Properties
Using Universal Analytics properties for your data reporting will give you more limitations than the new GA4 properties. To avoid data sampling in your reports, you can set up Google Analytics 4 property, which was previously branded as App+Web property in Google Analytics.
Read more: What You Should Know About The New GA4 Data API and UA Property API
Unlike the previous versions of Google Analytics properties, App+Web has 14 months of historical data. Therefore, the App+Web property can provide a higher limit of data sampling.
In Google Analytics 4 custom report, data sampling occurs only when your events exceed 10 million rows. The GA4 properties combine data from different websites and mobile apps in a single set of reports to allow you to do cross-platform analysis.
They allow you to gather data from your website using the Google Tag Manager and your mobile App using GA4 Firebase integration. GA4 also has powerful features like ‘Enhanced Measurement,’ which automatically tracks the scroll depth, embedded YouTube videos, file downloads, and outbound links.
Also, this version allows you to transfer your data to other Google Analytics properties. GA4’s properties unlock reports which allow you to analyze your audience in new ways, such as ad-hoc funnel and path analysis.
Conclusion
Data sampling aims to save time by increasing processing speed in Google Analytics reporting. The relevance of Sampling depends on the type of report you are analyzing. If your website has grown too large, the wrong sample size can negatively impact your data analysis because your sampled data will become more inaccurate.
The easiest and quickest way to avoid data sampling is by selecting a shorter date range. More advanced solutions include using powerful tools like Dataslayer to take your data to other platforms for deeper analysis. So, don’t forget to start your free trial today and see how Dataslayer can help you to get unsampled data for your data reporting!
