As a business owner, you'd like to do a deeper breakdown and analysis of the data that's displayed in your standard table report. Which feature would help you do that?
Filters would help you do a deeper breakdown and analysis of the data.
Secondary Dimension would help you do a deeper breakdown and analysis of the data.
Breakdowns would help you do a deeper breakdown and analysis of the data.
Comparisons would help you do a deeper breakdown and analysis of the data.
Explanation
Analysis of Correct Answer(s)
- A Secondary Dimension is the correct feature for a deeper data breakdown. In standard Google Analytics reports, data is organized by a primary dimension (the "what," like Traffic Source) against various metrics (the "how many," like Sessions).
- Adding a Secondary Dimension introduces a second data category into the same table, creating more granular rows. For example, if your primary dimension is Country, you can add Device Category as a secondary dimension. This will break down the data for each country to show you user counts for desktop, mobile, and tablet, enabling a more detailed analysis.
Analysis of Incorrect Options
- Filters: This feature is used to narrow down the data included in a report. For instance, you can apply a filter to view traffic from a single country. Filters reduce the dataset; they do not add another layer of detail to it.
- Comparisons: This feature is used to evaluate two or more segments of data side-by-side. For example, you can compare data from "Mobile Traffic" against "Desktop Traffic." This sets up a parallel analysis between different groups, rather than subdividing the existing rows in your report.
- Breakdowns: While "Breakdowns" is a term used in Google Analytics 4 to describe a similar function, Secondary Dimension is the specific, traditional feature in many reports that allows for this type of deeper data analysis.