Question from Reddit:
Hey all,
I’m trying to analyze user journeys from start to finish in terms of the pages they visit. I’ve tried using the ‘User Explorer’ in the Explorations report, but all I get are a bunch of effective user IDs. When I click on these IDs, I’m only shown a list of events like page_view, but there’s no indication of which page these events correspond to.
Am I missing something obvious here? It feels like understanding which pages users navigate through is one of the most basic features of analytics. My goal is to look at the page journey across all sessions in a user journey for a given date range, not just a single session.
Is there another way to do this in GA4, or am I just going about it the wrong way?
Any help or tips would be greatly appreciated!
Thanks!
Answer from Nabil:
The short answer is:
You are not missing anything obvious; GA4’s default User Explorer is deliberately designed to focus on the chronological stream of events rather than the sequential pages visited, which can make entire user journey analysis difficult.
The solution is to use the Path Exploration report within GA4 Explorations.
To see the specific pages, you need to set the Node Type in the Path Exploration report to either Page title or Page path and screen class, rather than the default Event name.
For a robust, cross-session analysis that uses all the events you need, exporting your data via the Google Analytics Data API to a platform like Looker Studio will give you the complete freedom you need.
The long answer is:
It certainly feels like page journey analysis should be a basic, straightforward function, and in a sense, it is, but GA4’s event-centric model makes it less intuitive than it was in Universal Analytics.
The reason your User Explorer report only shows a list of events like page_view is that, by design, the page_location (the full URL) and page_title are not main-level event parameters; they are custom parameters attached to the page_view event itself.
When you click an effective User ID in the User Explorer, GA4 shows the stream of events.
You have to click into the individual page_view event to see the page details, which is far too tedious for large-scale analysis.
The feature you should be using within GA4 is the Path Exploration report, found under the Explorations tab.
When you build a Path Exploration report, you must adjust the Node Type setting from the default Event name to either Page title or Page path and screen class to analyze the sequence of pages.
Furthermore, to see the journey across all sessions for a given user within your date range, you need to ensure the Analysis technique in the Exploration is set up to analyze the user-level path, which it is by default in the Path Exploration report.
However, even the Path Exploration report has limitations, such as sample rates on very large data sets and constraints on the number of steps it can display.
For the comprehensive, cross-session analysis of all users over a wide date range you desire, the most powerful and scalable solution is to leverage the Google Analytics Data API.
You can use this API to systematically extract all page_view events along with their associated user IDs, session IDs, timestamps, and page details (page_path and page_title) for your specified date range.
You can also use Google Tag Manager to enrich your page_view events by setting custom dimensions for things like the current user ID or category, which are then exported as well.
This raw data can be ingested and modeled in a data warehousing environment like Google Cloud Platform or directly fed into a visualization tool like Looker Studio using the Looker Studio API.
In Looker Studio, you can then build a completely custom, unsampled report that precisely strings together every single page visit in order for every user, across every session, giving you the complete user journey visualization you are looking for without the native limitations of the GA4 interface.
A server-side solution like Stape could also be used to enhance the quality of your user ID tracking before it even reaches GA4, ensuring higher fidelity of the user-level path data you ultimately export via the API.
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