Google Analytics has been an age-old trusted tool for website owners and marketers to gain insights into user behavior, track conversions, and optimize campaigns. However, there’s one that users often struggle with – data sampling.
Google Analytics Sampling is the silent enemy of data accuracy and can significantly impact the reliability of Google Analytics reports. So, if Google Analytics sampling is the limiting factor behind your upscaling plans, it’s time to understand it in detail.
In this blog, we’ll discuss what Google Analytics sampling is, how it works, and ways to avoid it. Stay tuned!
What is Google Analytics Sampling?
Google Analytics Sampling refers to selecting a subset of data from a larger dataset for analysis and estimating the behavior of the entire dataset based on the smaller representative sample.
Let’s say you have a popular e-commerce website that receives millions of visits per day. With GA4, you want to understand the behavior of your website visitors to optimize your marketing campaigns. Instead of analyzing every single visit, GA4 can randomly select a representative sample of data, such as 10% or 20%, analyze it, and provide you with insights. This sample represents a smaller but statistically significant portion of your overall traffic.
Google Analytics is the most widely used web analytics tool worldwide. It handles massive amounts of data in the shortest possible time. To reduce the computational load and provide results more quickly, Google randomly samples a percentage of the traffic data when the dataset exceeds the threshold.
The sampling situation in Google Analytics 4 (GA4) is somewhat similar to Universal Analytics. The default reports aren’t sampled. However, if you choose advanced analysis like Cohort or Funnel analysis, or segment overlap, sampling may occur.
When does Google Analytics sample data?
Here are some of the cases when Google Analytics sampling data is used to deduce insights or make generalizations:
Sampling Thresholds and Dataset Size
Google Analytics sampling occurs when the amount of data exceeds the following thresholds within the specified reporting period:
- Google Analytics 4 Standard (free)- 10 million events
- Google Analytics 4 360- up to 1 billion events
On the other hand, if your website has limited users and the data is too little, Google Analytics 4 will sample data until you start generating enough traffic.
Sampling based on Reports
GA4 always shows unsampled data on standard reports, even if you utilize filters, comparisons, and custom parameters. Therefore, sampling is more likely when analyzing custom reports, advanced segments, or non-standard configurations requiring extensive processing power.
- Advanced Reports can be sampled depending on the data you want to view. This typically happens when your data exceeds 10 million, and the report differs from the default or standard report.
- The Demographic report in GA4 often produces sampled data to protect user privacy.
- Exploration reports usually are unsampled; however, the moment you add dimensions to your reports, data sampling can occur. Since these reports query raw events and user-level data, these queries may be asked to process more events or users than the GA4 quota limit.
GA4, unlike Universal Analytics (UA), is free from any hit limits or session limits. Yet the challenge of sampling data persists. And whenever sampling occurs, it introduces uncertainty into the observations.
How does Sampling Work in Google Analytics?
When Google Analytics samples a dataset, the sample is then used to generate aggregated reports and metrics, which are assumed to represent the behavior of the entire data set.
If there’s an orange sign at the top of the report saying that the report is based on less than 100% of sessions, it indicates the data sampling.
Google Analytics sampling may save computational resources, but it can compromise the accuracy and reliability of the insights derived.
This serves as a crucial selling point for Google when targeting large enterprises. Upgrading to premium GA4 360 may be the only choice for more accurate reporting.
Here’s an example of the impact of Google Analytics Sampling:
Assume your SaaS website received 30 million page views during a specific reporting period. However, Google Analytics sampling dataset used only 10 million page views (33.3% of the total) to generate the metrics. The data shows that a particular blog received a high average time-on-page and many social media shares. But later, you realize it generated traffic from other referral websites. This oversight could strongly affect your content strategy leading to a discrepancy between the GA4 revenue reports and the actual sales.
Why Is Data Sampling Not Preferred?
Here are a few reasons why data sampling is not preferred:
Inaccuracy
Google Analytics sampling data tends to become more inaccurate as your dataset grows. Therefore, making budgeting decisions for a large business based on inaccurate or assumptive reports could lead to a financial loss for the company.
On the contrary, if the sample rate is less than 50%, you may be able to analyze your audience’s demographics, but a comparative analysis wouldn’t be possible.
Loss of Granularity
Google Analytics sampling reduces the level of detail in the data, making it challenging to identify and analyze specific patterns or outliers for decision-making.
Limited Customization
Google sampling can hamper the creation of custom reports and application advanced segments.
Missed Opportunities
Sampling dataset may overlook essential nuances or trends present in the unsampled data. This can significantly impact understanding user behavior and optimizing marketing efforts.
If you are overlooking opportunities due to Google Analytics data sampling, here are 5 effective ways to avoid data sampling and a bonus method at the end that provides a comprehensive analytics solution.
5 Ways to Avoid Data Sampling
Work with Standard Google Analytics Reports
In GA4, standard reports are unsampled. This means you can improve your reports’ accuracy by simply omitting segments and secondary dimensions and streamlining your queries.
However, this does not help fulfill a rapidly growing business’s specific analysis requirements.
Reduce Date Ranges
By narrowing the date range for your analysis, such as a specific day, week, or month, you can reduce the amount of data processed and avoid the risk of Google sampling data. Focusing on specific timeframes enables you to derive more precise insights without overwhelming the system.
It may still limit the ability to analyze long-term trends or patterns. As a result, you could overlook significant variations or anomalies outside the selected date range.
Use Parallel Tracking
Implementing parallel tracking allows your website or app to load faster, reducing the chances of high traffic volumes that trigger data sampling. This ensures that user interactions are accurately captured and included in the data set.
A drawback of this method is that it requires technical implementation and potential adjustments to track codes and server configurations.
Use Google BigQuery export
If your data is growing rapidly, getting a data warehouse will be a great option to easily store granular data from different sources. One of the key benefits of GA4 is the free export of raw unsampled data to Google BigQuery.
Consider the setup, configuration, and maintenance of data transfer from GA4 to BigQuery and the storage costs. It can also involve a delay in data availability which may impact real-time or near-real-time analysis requirements.
Explore Premium Solutions
Google Analytics 360, the enterprise-level version of GA4, offers higher data limits and more extensive processing capabilities. It also provides access to advanced features and integrations for more sophisticated analysis.
However, the enterprise version comes with a hefty price tag. The pricing model is less-predictable and usage-based, the primary variable being the amount of data you wish to collect. The cost of Google Analytics 360 starts at a retail price of USD 50,000/year, and as you collect more data, your costs increase.
By exploring the aforementioned strategies, you can avoid or minimize the impact of Google sampling. All alternatives have their pros and cons.
However, the most cost-effective way to ensure that your data analysis is robust and actionable is to leverage Growth Nirvana.
Avoid Sampling with Growth Nirvana
One powerful solution to avoid Google Analytics sampling data is Growth Nirvana.
Growth Nirvana is a marketing analytics tool that helps users easily visualize their data, creating compelling dashboards and comprehensive reports.
While both Growth Nirvana and GA4 are analytics solutions, there are several aspects where Growth Nirvana may offer advantages over GA4.
✅Data Sampling Avoidance
Unlike GA4 and many analytics platforms, Growth Nirvana claims to provide accurate and complete data analysis without sampling. Processing the entire dataset eliminates the risk of missing out on valuable insights or making decisions based on a data subset.
✅Advanced Segmentation and Cohort Analysis
Growth Nirvana is designed to offer advanced analytics capabilities, often surpassing the standard features provided by GA4. We offer advanced segmentation capabilities, allowing you to slice and dice your data based on various dimensions and attributes. This enables you to analyze specific user segments or cohorts effectively, gaining deeper insights without relying on sampled data.
✅Granular Data Access
Growth Nirvana can provide more granular access to your data, allowing you to drill down to individual events or interactions. This level of granularity ensures that each data point is accurately represented.
✅Custom Analytics Models
Growth Nirvana can build custom analytics models tailored to your specific business needs. It can leverage advanced statistical techniques or machine learning algorithms to derive insights directly from the raw data, enhancing the accuracy of your analysis.
✅Data Integration and Enrichment
Growth Nirvana can integrate with various data sources such as web analytics, CRM systems, advertising platforms, and other external databases. Enriching your data with additional sources reduces the reliance on sampled data, leading to more comprehensive insights.
✅User Interface and Intuitiveness
Growth Nirvana’s user-friendly interface with intuitive navigation and visualizations help simplify the data exploration process.
✅Additional Support and Services
Our dedicated support services, training, and consulting help users make the most of our analytics platform. This is valuable, particularly for organizations with specific business objectives requiring tailored analytics solutions.
By leveraging the powerful features of Growth Nirvana, you can unlock the full potential of your data, make informed decisions and drive business growth whilst completely sidestepping the problem of Google Analytics sampling.
Want to learn more about our platform? Schedule a demo today!
