How to Fix Consecutive Pages in Google Analytics 4 Explores

Having issues custom reports in explore section

Iโ€™ve created a custom report in the Explore section, where I want to track the audience that has reached on the Thank You page. To achieve this, I set up a flow chart and a reverse path analysis for the Thank You page.

However, the report is showing the same page multiple times in the flow. Iโ€™m attaching a screenshot for reference.
Kindly share how can I overcome this.

Thanks

The short answer is:

How do I filter out duplicate consecutive pages in a GA4 Path Exploration?

The issue of repeat pages in your Google Analytics 4 (GA4) Explore report, specifically in Path Exploration or Funnel Exploration, often stems from rapid, consecutive interactions on the same page, such as dynamic content loading, AJAX updates, or slightly different event parameters triggering multiple page_view events.

To overcome this, you need to refine your GA4 tracking logic using either Google Tag Manager (GTM) or Stape for server-side GTM to implement a de-duplication mechanism.

This mechanism, typically a custom JavaScript variable in GTM or a custom client/transformer in Stape, should check if the current page location is the same as the previous one within a very short timeframe (e.g., 500ms) and only fire the ‘page_view’ event if they differ, effectively filtering out the spurious repeats at the data collection layer.

This approach ensures cleaner data collection, which is crucial for accurate reporting with the Google Analytics Data API for more flexible external analysis.

The long answer is:

The phenomenon you are observing in your Google Analytics 4 Explore report, where the same page appears multiple times in a sequence within a Path or Funnel analysis, is a common data fidelity issue, especially in single-page applications (SPAs) or sites with complex, dynamic client-side interactions, and it primarily relates to how the page_view event is being triggered.

When a user interacts with a page, multiple events can fire in quick succession – sometimes even legitimate ‘page_view’ events if the URL fragment changes without a full page reload – but often these consecutive identical steps are noise.

The most robust and cost-effective solution is to fix the data at the source using a server-side tracking setup via Google Tag Manager and Stape or by implementing the logic directly in your client-side GTM container.

The technical solution involves creating a deduplication logic for the page_view event.

In client-side GTM, you would create a Custom JavaScript Variable that stores the last recorded page location (document.location.pathname + document.location.search) and the timestamp of the last page_view event.

Your page_view trigger would then be modified to fire only if the current page location is different from the stored last location, or if a certain minimum time (e.g., 500ms to 1 second) has passed since the last identical page view.

If you are using server-side tracking with Stape, you would implement a similar logic using a Custom Client or Transformer to inspect the incoming GA4 request payload and the previous events in the user’s session, only forwarding the event to Google’s endpoint via the Google Analytics Measurement Protocol if it meets the non-duplication criteria.

Utilizing Stape for this server-side deduplication is highly cost-effective because it shifts the processing load off the user’s browser, potentially improving site performance, and provides a much cleaner dataset for GA4 without relying on complex and often fallible client-side hacks.

Furthermore, for advanced analysis of your refined audience data, leveraging the BigQuery API to export the clean GA4 event data into Google BigQuery allows for powerful SQL-based segmentation and joining with other datasets, such as your CRM data via the HubSpot API or Salesforce APIs.

You can then use the Looker Studio API to build custom, flexible dashboards that visualize the clean path data, moving beyond the limitations of the GA4 UI and ensuring that your custom reports accurately reflect true user journeys without the noise of duplicate steps, giving you a comprehensive, flexible, and powerful reporting structure.

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