Could you please explain the reason, as shown in the attached screenshots, for the increase in the values of "New Users" in Google Analytics 4 when the "Total User" column is removed? I noticed that there is a research filtering on the right, but it seems that this filtering does not affect the "New Users" metric. Consequently, there is a significant discrepancy between the number of new users reported in these two analyses.
July 24, 2023
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ModHi @mmadhu,
The number of new users in a free form exploration within GA4 may increase when you remove the "Total Users" column due to the following reasons:
The "Total Users" column includes both new and returning users. By removing this column, the "New Users" metric will only display the count of users who have visited your site or app for the first time within the specified period.
However, there are a few other potential explanations for the increase in new users when the "Total Users" column is removed:User filtering: When creating a free form exploration, you have the option to apply filters to exclude certain user groups from the data. For instance, you might choose to filter out users who have not converted. By applying such filters, the number of new users reported may exceed the total number of users.
Date range changes: Altering the date range of the free form exploration can also impact the number of new users displayed. For example, if you shorten the date range, the count of new users may appear higher.
Possible GA4 bug: There is a slight chance that a bug within GA4 could be causing the increase in new user numbers upon removing the "Total Users" column. If you suspect this might be the case, you can seek assistance from Google Analytics support: support.google.com/analytics/answer/9026876?hl=en
If you are still uncertain about the reason behind the increased new user count after removing the "Total Users" column, you can try creating a new free form exploration to see if the same pattern occurs. If it does, there might be a bug in GA4. Conversely, if the issue does not persist, it is more likely that user filtering or date range changes contributed to the discrepancy.
Hope this helps!
