Reports and explorations both 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 explorations support different fields
By design, reports and explorations 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 explorations. When you open a report in explorations 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 explorations. Comparisons present in a report you open in explorations are converted into segments, and any unsupported metrics or dimensions in the comparison won't be included in the resulting segment in explorations. This can change the data included or excluded from the segment.
Attribution model differences
Explorations 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 ranges in explorations 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 explorations, data prior to that range won't be included.
Reports that use the aggregated data tables are always based on 100% of the available data. explorations, 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 explorations, 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 explorations is too small, try adjusting the population. For example, shortening the date range of the explorations 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.