In our project most users refuse cookies, and GA4 misses part of the events. I’ve seen funnels diverge when parts of the path aren’t captured.
This undermines trust in the metrics and calls the forecasts into question: with incomplete data you easily miss the real behavior and budget needs.
What problems do data losses and view of attribution create?
Losses distort attribution of conversions: it feels like part of the journey disappeared, while the numbers tell one thing and reality tells another.
As a result budgets and optimization plans wander in the dark, and the business can’t point to a clear cause.
How to extract meaning from losses and where to look for scale?
• Measure losses in BigQuery: compare conversions and events between granted and denied, check consent status in privacy_info.analytics_storage and assess impact on key metrics.
• This gives a clear view of missing data and helps pinpoint where data drops occur.
How to move forward: pilot, unified truth, and forecasts? Implement a single approach to accounting for gaps: GA4+BigQuery+CRM, adjust forecasts and budget, regularly update reports and expand the analysis.
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