Editorial
Analysts are demanding analytic tools deliver features that make fast, ad-hoc analysis easier to do. Google has worked to make its latest version of Google Analytics, GA4, deliver ad-hoc insights faster through its analysis hub. The analysis hub relies on templates designed for ad hoc analysis, giving analysts a central location to find analysis and to decide what visualization should appear for stakeholders.
Why Google Analytics Introduced Analysis Hub
The Analysis Hub was introduced as an exclusive feature to Google Analytics 360. It was added as a menu feature in Google Analytics 4 to better arrange reports.
To understand why we need the analysis hub, just look at the templates in the hub. Google Analytics users will see many familiar choices. The templates are the specialty reports that appeared in the previous versions of Google Analytics — path analysis, funnel and cohort analysis, which I explained in an earlier post. These reports were introduced well after the launch of Google Analytics.
Although the reports usually required only a few drop-downs to access, the menu quickly grew longer to accommodate all the reporting features. Thus Google's objective with GA4 was to streamline account menus. Grouping the ad-hoc reporting makes searching for and finding reports less overwhelming and more intuitive, especially as users access accounts from smart devices as well as a standard computer.
Related Article: New Data Import for Google Analytics GA4 Is a Workflow Boon
How to Access the Analysis Hub
The templates can be accessed through the Analysis Hub. To start, analysts navigate to the Analysis section of the main menu, then click Analysis Hub.
What appears is a selection of three columns: variable, tab setting and exploration. Each one of these has a different function to help create the desired final report.
The first column is the variable column. The variable column provides a place to set the dimension, metrics and segments for the desired report. Users can set the date range as well as name their dimensions. Two months of data is retained as a default.
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The next column, Tab Settings, provides data visualization. The selection is the data visualization choices most familiar to analyst exist, such as bar charts, time series, and pie charts.
You also have a section for selecting the cohort, funnel, segment overlap, or path analysis templates. A pre-selected visualization template can be used. The six selections are basic: a table, scatterplot, bar graph, line graph, donut graph and a geomap.
The last section, Exploration, is the end visual (or report). It displays what will be the final output. The report appears on tabs, allowing a side-by-side comparison between the templates. This is helpful in deciding what to use within the report on an ongoing basis.
The base exploration template is a bar chart. Exploration helps analysts quickly explore how changes in the analytics data impact what the reporting would look like. Users can visualize data in a tabular graph, and apply filters and segments as needed.
The Analysis hub templates can enhance a number of standard requests, such as anomaly detection. Because Google added data import feature — which I wrote about here — you now have an opportunity to explore how such ad-hoc analysis appear with additional data alongside GA4-collected data.
Overall, Analysis Hubs give analysts a new feature to handle stakeholder what-if requests a bit faster.
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