Data discrepancies in Google Analytics 4 (GA4)Understanding how events are set up in Google Analytics 4 (GA4) is crucial, as it directly impacts the accuracy and consistency of the data you collect. Different setups can lead to discrepancies in results, and here’s why:

1. Event Naming and Configuration:

Inconsistency in Naming: In GA4, the naming of events is flexible, allowing for customized names. If similar events are named differently across various sections of a website or in different campaigns (e.g., “purchase” vs. “buy_now”), it leads to fragmented data, making it difficult to analyze overall user behavior.

Event Parameters: Events in GA4 can carry additional information through parameters. If parameters are not consistently set up (e.g., some “purchase” events carry price information while others don’t), this can lead to incomplete data and discrepancies in reporting.

2. Triggering Conditions:

Different Triggers: If events are set to trigger based on different conditions or user interactions, this inconsistency can cause discrepancies. For example, a “video_play” event triggered on some pages when the play button is clicked, and on others after the video starts, will yield inconsistent data

Timing Issues: The timing of when an event is fired (e.g., immediately when a page loads vs. after a delay) can also impact the data collected, especially in user engagement metrics.

3. Data Layer Integration:

In websites where GA4 events rely on a data layer, discrepancies can arise if the data layer is not uniformly implemented across all pages. Inconsistent or incorrect data layer configurations can lead to inaccurate event tracking.

4. Tag Manager Implementation:

If you’re using Google Tag Manager (GTM) to manage GA4 events, discrepancies can occur due to differences in how tags, triggers, and variables are set up. Inconsistent implementations across different parts of a website can lead to varied tracking results.

5. Enhanced E-commerce Tracking:

E-commerce websites using GA4 face additional complexities. Variations in how product views, add-to-cart actions, and checkouts are tracked can significantly impact the accuracy of revenue and conversion data.

6. Cross-Device and Cross-Platform Tracking:

Discrepancies can also arise if events are not uniformly tracked across all devices and platforms (desktop, mobile, app). Users often switch devices, and inconsistent tracking can lead to fragmented user journey data.

7. User Consent and Privacy Settings:

With increasing focus on user privacy and consent, varying consent management implementations can lead to differences in the amount of data collected, especially in regions with strict privacy laws like the EU under GDPR.

8. Filtering and Data Views:

How data is filtered and viewed in GA4 reports can also cause discrepancies. For example, applying different filters or comparing unfiltered data with filtered data can lead to confusion and inconsistent insights.


To minimize discrepancies in GA4, it’s vital to ensure consistency in event setup across your entire digital ecosystem. Standardizing event naming, parameters, triggering conditions, and ensuring uniform data layer and GTM implementations are key steps. Regular audits and testing of your GA4 configuration can help identify and rectify any inconsistencies, ensuring the reliability of your analytics data.