How to check your data across different platforms
Addressing the inconsistencies between META and Google Analytics 4 (GA4) is crucial for marketers seeking accurate data and actionable insights. In this guide, we'll explore why these differences happen and offer straightforward solutions to align the two platforms effectively.
For marketers aiming for accurate data and practical insights, it's vital to tackle the inconsistencies between META Ads and Google Analytics 4 (GA4). Discrepancies between META and GA4 arise from various factors, including platform functionality and technical challenges. Fundamentally, limitations such as Google's difficulty in perceiving impression data and META's inability to capture view-through conversions pose significant hurdles. Resolving these issues requires a multifaceted approach involving first-party attribution, multi-touch marketing, and comprehensive conversion modeling.
Understanding Data Discrepancies:
Data discrepancies occur when META and GA4 show different information, impacting our understanding of marketing performance. Small differences are normal due to tracking methods of META and GA4 but significant ones can lead to incorrect conclusions, affecting our bottom line.
Challenges and Technical Issues:
Fundamental Challenges:
Walled gardens: META and Google are considered walled gardens, limiting accessible data for comprehensive reporting.
Limitations in tracking impressions on META by GA4.
META's inability to track view-through conversions due to third-party cookie deprecation such as Apple iOS 14.5 and ITP.
Platform & Technical Issues:
Varied definitions of sessions and clicks between GA4 and META.
Users clicking on the same ad multiple times and tracking differences.
Variances in user tracking methods between META and GA4.
Reducing Discrepancies:
To minimise data discrepancies, consider the following strategies:
Create Custom Parameters for URLs:
Use URL parameters to bridge data gaps and measure META traffic more effectively in GA4.
Differentiate paid traffic from organic posts by setting up URL parameters.
Use Both Click and Session Metrics:
Manage expectations by including both META clicks and GA4 session metrics in reports.
Emphasize the impact of campaigns over metric consolidation.
Addressing Fundamental Challenges with Tracking & Modeling:
While platform reporting has limitations, third-party alternatives could offer solutions to fundamental challenges:
Track First-Party Clicks with Multi-Touch Attribution:
Monitor individual customer journeys and attribute revenue back to META Ads.
Integrate with multiple data sources for a comprehensive view of the conversion path.
Model Impressions to Impact on Revenue:
Utilise marketing mix modeling to assess the impact of META ads on revenue.
Predict potential campaign adjustments and evaluate budget scenarios.
Conversion Modeling to Fill Gaps in META's Insight:
Combine data-driven attribution models with predictive elements to identify high-converting users.
Feed conversions back to META, enhancing campaign optimization and targeting.
Conclusion:
Recognising the disparities between META and GA4 is crucial. There are many tools out there that can help extend beyond the basic conversion tracking. This enhances reporting quality, validates the impact on the bottom line, and facilitates strategic budget allocation for optimal results.
