Page scrolling analysis in Google Data Studio

Good afternoon, my name is Chakkanbaev Ilkhom I am the author of the SeoPulses blog, I would like to share the translation and practical implementation of the article michaelhoweely.com . In order to create a complete and understandable report for a blog or article site in Google Data Studio, you will need to use the following tools:

• Google Tag Manager
• Google Analytics

Preparing to create a report

To do this, go to GTM and select in the variable settings:

• Scroll Depth Threshold;
• Scroll Depth Units;
• Scroll Direction.

Next, go to the "Triggers" section and create a new one with the type "Scroll Depth".







In the trigger settings, select “Vertical Scroll Depth” and percentages (Necessary for you).







Now create a new tag, and select Google Analytics as the type.







In the tag, fill in:

• Tracking Type: Event;
• Category: Scroll or Scroll Page. The name is required for navigation;
• Action: {{Page Path}};
• Label: {{Scroll Depth Threshold}}.
• As a setting for Google Analytics, we use the desired Analytics ID.

As a trigger, select the Page Scroll trigger that was previously created.







After the new version is published, it will be possible to verify that the events are passed to Google Analytics.

Report Creation in Google Data Studio

In order to create a report in Data Studio we use:



A histogram in which:

• Parameter: Event Label;
• Metric: unique events.

Also put a tick in the "Apply Filter" and click on "Add Filter". Here we indicate the “event category” contains “scroll” (or another name given when creating the tag in GTM).











For the convenience of viewing, it is recommended to select “Data Labels” in the histogram styles.



Table:

• Parameter: Page Name;
• Metric: Pageviews.

It is also worth adding a filter as a date range.

Ready report

Now choosing the desired date period we see:

• The name of the page and the number of its views for this date range;
• By clicking on the desired page, you can see to which part users mostly read.

An example of this report can be viewed in Data Studio by clicking on the link .