MTU vs. Google Analytics

You may notice variations in usage statistics between Insider and Google Analytics 4 (GA4) for several reasons. Here are some factors to consider:

Different implementation rules for GA4 and Insider scripts

Ensure that GA4 and Insider scripts follow the same implementation rules. Integrate their JavaScript files in exactly the same manner. If using Google Tag Manager or another tag manager, ensure you maintain consistent trigger rules and implemented pages for both platforms.

Deduplication of identified users via Insider Object

Thanks to Insider Object, Insider's user-centric approach ensures that interactions on different devices are attributed to the same user. Verify that this process aligns with GA4's user identification to avoid discrepancies.

Users that are blocking GA4 via their ad blocker extensions

Users employing ad blocker extensions can impact GA4 statistics. Consider using a self-hosted analytics service to minimize the impact of ad blockers on your user data.

Different date range selection in GA4 and Insider

Ensure that the date range selections in GA4 and Insider are consistent when comparing statistics.

To have a better understanding of the difference, you can test the following methods:

Check Google Analytics 4 and Insider implementations

Google Analytics 4 and Insider should have the same implementation methods. You should integrate their JavaScript files exactly the same way. Whether using a tag manager or not, ensure the pages are implemented the same way.

Use a self-hosted analytics service

You should use a self-hosted analytics service to not miss any users.

Google Analytics 4 and other analytics services that are hosted on the cloud side are vulnerable to ad blockers. In 2021, 42.7% of all internet users reported using ad blockers.

Popular ad blockers, such as uBlock and Adblock Plus, have the capability to automatically block Google Analytics scripts, leading to potential data discrepancies. Additionally, some browsers like Brave and Firefox come with default tracking prevention settings, further impacting data collection.

The suggestion to conduct tests and assess the accuracy of Google Analytics results on your website using a self-hosted analytics solution like Umami or Matomo is a practical approach. These self-hosted solutions can provide insights into the percentage of users who actively block Google Analytics, allowing you to better understand the potential impact of ad blockers on your analytics data.

Overall, the recommendation aligns with best practices for ensuring data accuracy in the face of ad blockers and browser tracking prevention settings. However, as always, it's important to consider the specific requirements and constraints of your website and analytics setup when implementing such solutions.

Implement an event-driven analytics solution

The recommendation to implement an event-driven analytics solution, especially when comparing Insider's user identification by user ID with Google Analytics' cookie-based identification, is grounded in addressing cross-device and cross-browser tracking challenges.

Insider's approach of using a user ID (custom variable or data point like email or phone number) allows for the identification of a user across various touchpoints, providing a more holistic view of user behavior. This user-centric approach ensures that interactions on different devices are attributed to the same user.

The content correctly points out the limitation of Google Analytics' cookie-based identification, which may lead to the same user being counted as multiple users when accessing a website from different devices or browsers. GA4, in particular, focuses on an event-driven model, allowing for better user unification across devices; it addresses this issue by making their identification event-driven which results in the unification of users across different devices. 

The suggestion to use an analytics solution that identifies users by their user IDs instead of cookie IDs aligns with the industry trend towards more robust user-centric tracking methods. This can enhance the accuracy of user analytics and provide a more comprehensive understanding of user journeys.

As always, the successful implementation of such recommendations depends on the specifics of your analytics setup and business requirements. Testing and monitoring the impact of these changes are crucial to ensure data accuracy and consistency across platforms.