Data differences between reports and Analysis

Understand why your data may differ depending on where you see it.

Reports and Analysis are complementary areas in Google Analytics, designed to provide actionable insights into your web and app data. Usually, you'll see the same data in both areas. There are times, however, when you may see differences in the data shown in each area. These differences are expected, and are explained below.

In this article:

Reports and Analysis support different fields

By design, Reports and Analysis give you different views of your data, at different levels of granularity. For example, some dimensions and metrics available in Reports aren't supported in Analysis. When you open a report in Analysis that includes unsupported fields, those fields are dropped from the exploration. If the report displayed a visualization based on the unsupported fields (for example, a line chart showing an unsupported metric), that visualization won't appear in the resulting exploration.

Differences between segments and comparisons

Comparisons in Reports can use fields that aren't supported in Analysis. Comparisons present in a report you open in Analysis are converted into segments, and any unsupported metrics or dimensions in the comparison won't be included in the resulting segment in Analysis. This can change the data included or excluded from the segment.

Attribution model differences

Analysis currently only supports the Cross-channel last click attribution model. If your report uses one of the other models, it will have the Cross-channel last click model applied instead. Learn more about Firebase conversions and attribution models.

Date differences

Date ranges in Analysis are limited to your property's data retention settings. If you create a report with a date range outside the user and event level data retention settings, and then open it in Analysis, data prior to that range won't be included.

Sampling differences

Reports that use the aggregated data tables are always based on 100% of the available data. Analysis, on the other hand, may apply sampling when querying user and event level data if the size of your query exceeds your quota. For users of the free Google Analytics product, the unsampled data quota is 10 million events.

In the upper right of your analysis, hover over the shield icon to see the current sampling rate.

When working with sampled data, the ratio between the size of the overall population compared to the sample size can affect the accuracy of your query results. In general, the bigger the sample size (as a percentage of the population) the higher the accuracy of your results.

If the sample size for an analysis is too small, try adjusting the population. For example, shortening the date range of the analysis can reduce the size of the population to which sampling is applied, resulting in higher accuracy.

Processing time differences

The data in Analytics comes from a number of different systems, and may be processed at different times. You may notice slightly different results when running queries for the past 48 hours, due to processing time differences.

Was this helpful?
How can we improve it?

Need more help?

Sign in for additional support options to quickly solve your issue