Google Analytics Sampling, Missing Data & Filters

Known Sampling Behavior

• Document how Google Analytics applies sampling or threshold limits across products and plans.
• Record metrics or reports most susceptible to sampling.
• Note historical examples from the client environment when sampling occurred.

Detection Checklist

• Outline warning signs (UI messages, API flags, data volume drops) that indicate sampling.
• Capture queries or API endpoints used to confirm sample rates.
• Track monitoring tasks that alert analysts when sampling thresholds are crossed.

Mitigation Strategies

• Provide options to reduce sampling (date range changes, filter adjustments, upgraded plans).
• Recommend export paths (raw data APIs, warehouse connectors) when precision is required.
• Describe communication expectations with stakeholders when numbers are approximate.

Handling Missing or Delayed Data

• List common causes for gaps (tag outages, consent opt-outs, ad blockers, ETL failures).
• Capture standard operating procedures for backfilling or annotating reports.
• Note tools and contacts required to restore data integrity quickly.

Follow-Up Actions

• Track outstanding investigations into unresolved sampling or loss issues.
• Maintain a log of incidents and resolutions for future reference.