About sampled data
Understand what sampling is, and why it's happening.
Sampling in Google Analytics (or in any analytics software) refers to the practice of selecting a subset of data from your traffic and reporting on the trends detected in that sample set. Sampling is widely used in statistical analysis because analyzing a subset of data gives similar results to an analysis of a complete data set, but can produce these results with a smaller a computational burden and a reduced processing time.
In Google Analytics, sampling can occur in your reports, during your data collection, or in both places.
Sampling in reports
When a report is based on data from a large number of sessions, you may see the following notice at the top of the report: This report is based on N sessions. This notice alerts you to the fact that the report is based on sampled data. Sampling occurs automatically when more than 500,000 sessions are collected for a report, allowing Google Analytics to generate reports more quickly for those large data sets. When your report is based on sampled data, you have the option to adjust the sample size to increase accuracy or increase speed. Note that Flow Visualization reports are sampled after 100,000 sessions and 1 million conversions in the Multi-Channel Funnel report.
Sampling in data collection
If you have many millions of sessions per month, you should consider configuring your tracking code to sample your traffic, or collect data from a subset of your total traffic. By sampling your data collection, you can get good report results without ever getting a decrease in processing speed.
Learn how to set up collection sampling for different tracking methods using the appropriate Developer Guide for your environment:
- Web tracking: Universal Analytics (if using analytics.js) and classic Google Analytics (if using ga.js)
The changes you need to make depend on which tracking code you’re using. See if you have Classic Analytics (ga.js) or Universal Analytics (analytics.js).
- App tracking: Android apps and iOS apps