Amazon Advertising Sampling, Missing Data, Filters, etc.

Sampling, Missing Data, Filters, etc.

Provide playbooks for detecting and correcting reporting gaps that affect Amazon Advertising.

Detection Playbook

• Dashboards or queries that surface sampling, filtering, or attribution anomalies.
• Thresholds for acceptable sampling levels and when to escalate.
• Cross-check process comparing platform exports with analytics or warehouse data.

Root Cause Patterns

• Common configuration mistakes (date ranges, breakdowns, report settings).
• Platform-specific quirks such as reporting delays or limited lookback windows.
• Interactions with consent mode, ad blockers, or privacy settings that suppress data.

Remediation Steps

• Immediate mitigation actions (adjust reports, request reprocessing, update filters).
• Long-term fixes (revise tracking, enhance data layer, improve export logic).
• Communication plan to keep stakeholders informed about data limitations.

Prevention Checklist

• Pre-launch QA to validate reporting configuration and sampling risk.
• Documentation updates when filters, segments, or dashboards change.
• Recurring audit schedule to confirm fixes remain effective.