The Challenges of Google Analytics 4 (GA4) and How to Double-Verify Your Data

Since its rollout, Google Analytics 4 (GA4) has been met with both excitement and frustration within the digital marketing community. While it offers advanced features and deeper insights compared to its predecessor, Universal Analytics (UA), GA4 has also been plagued by several issues that have left marketers scrambling to make sense of their data. In this article, we'll discuss some of the common problems users have reported with GA4 and provide strategies for double-verifying the accuracy of the information you're receiving.

Common Issues with GA4

1. Delayed Data Processing

GA4 has been criticized for its delayed data processing, with reports indicating that it can take 24 to 48 hours for data to be fully processed and available for analysis. This delay can cause significant issues when timely decisions need to be made based on real-time data.

2. Complex Conversion Tracking

One of the biggest challenges in GA4 is the complexity of setting up conversion tracking. Unlike UA, where setting up goals was relatively straightforward, GA4 requires a deeper understanding of event tracking and often necessitates the use of Google Tag Manager. This has made it more difficult for less technically savvy users to effectively track conversions [source].

3. Inconsistent Attribution Models

The attribution models in GA4, particularly at the event level, can sometimes yield inconsistent results when compared to the attribution models in UA. These discrepancies can lead to confusion and mistrust in the data, particularly when trying to understand the performance of marketing campaigns [source] [source].

4. Limited Data Retention

For users on the free version of GA4, data retention is limited to 14 months, which restricts the ability to perform year-over-year comparisons and other long-term analyses. This limitation has been a significant pain point for marketers who rely on historical data to make informed decisions [source].

Strategies to Double-Verify Your GA4 Data

1. Cross-Check with Universal Analytics

If you're still running Universal Analytics alongside GA4, compare key metrics between the two platforms. While the data won't match exactly due to differences in how the two systems track and report data, it should be close enough to provide a sanity check. Focus on metrics like session counts, conversion rates, and traffic sources to identify any major discrepancies.

2. Leverage BigQuery for Raw Data Analysis

For users who need more granular control over their data, exporting GA4 data to BigQuery allows for in-depth analysis without the limitations of GA4's UI. In BigQuery, you can run custom queries to validate the accuracy of your data, perform advanced calculations, and compare it against other data sources [source].

3. Use DebugView for Real-Time Troubleshooting

GA4's DebugView is an invaluable tool for troubleshooting tracking issues in real-time. By monitoring events as they happen, you can quickly identify and correct issues with your GA4 implementation before they cause significant data inaccuracies [source].

4. Regularly Audit Event and Conversion Tracking

Periodically review your event and conversion tracking setup to ensure everything is working as intended. This includes checking that all necessary tags are firing correctly and that the data collected aligns with your business objectives. If you're using Google Tag Manager, verify that all tags and triggers are correctly configured and aligned with GA4's event-based data model [source].

5. Employ Alternative Analytics Tools

If you find GA4's issues too cumbersome, consider using alternative analytics platforms like Matomo or Piwik PRO, which offer more user-friendly interfaces and fewer restrictions. These tools can serve as a backup or even a primary source of analytics data, allowing you to cross-verify the insights you gain from GA4 [source].

Conclusion

While GA4 is a powerful tool, it's clear that it still has some growing pains. By understanding the common issues and implementing strategies to double-verify your data, you can ensure that your analytics insights are accurate and actionable. Remember, the key to effective analytics is not just collecting data, but trusting the data you collect.