Connect experiment data with the next decision
The guide starts with primary business metrics, supporting diagnostic measures, and checks related to test validity. It then introduces a dashboard structure and a validation process for incomplete, duplicated, or inconsistent data. Statistical-analysis sections lead into interpreting patterns and turning the findings into possible campaign actions.
The framework gives marketers a sequence for reviewing evidence before drawing conclusions, with documentation helping make the basis of each recommendation visible to the rest of the team.
What you’ll find inside
- Primary, secondary, and control metrics
- Analysis-dashboard planning
- Data cleaning and tracking verification
- Statistical significance and interpretation
- Findings, reporting, and campaign decisions
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