A practical review for making sure the numbers used in marketing or operations reports actually describe the intended events.
Last reviewed: September 29, 2026 Editorial standard: Martzine Editorial Team.
What this resource is for
Use Analytics Quality Check when Analytics work needs one place for the inputs, the decision and the follow-up that comes from the review.
Use analytics quality check when the related work needs one clear review record rather than scattered notes.
What to check
- Event definitions
- Source
- Date range
- Attribution
- Exceptions
How to use it
Step 1: Event definitions
Record the part that changes the decision, then attach an owner and a date to anything that still needs evidence.
Step 2: Source
Work through the checks in the order the task happens. Mark missing information instead of filling the gap with an assumption.
Step 3: Date range
Finish by deciding what changes, what stays the same and when the result should be reviewed again.
Step 4: Attribution
Run the resource against one real case. A live example usually exposes a missing field or vague definition faster than another planning meeting.
Step 5: Exceptions
Work through the checks in the order the task happens. Mark missing information instead of filling the gap with an assumption.
What a useful result looks like
A useful Analytics Quality Check result should tell the team what changes next, who owns it and what still needs to be checked. A practical review for making sure the numbers used in marketing or operations reports actually describe the intended events.
Common mistakes
Mixing figures from different periods, definitions or systems and then treating them as one consistent set.
Related Martzine work
The surrounding work is usually easier to handle when the resource sits next to the relevant calculation, tool or guide.
Martzine Solutions · Martzine Services.
Sources and further research
For Analytics Quality Check, use the primary source when the subject depends on current rules, technical specifications or definitions outside Martzine’s own working framework.
- Google Analytics documentation (Official documentation for analytics implementation, measurement and reporting.)
Martzine note
Keep the resource close to the process it supports. A document that lives outside the workflow tends to become stale faster.
For Analytics Quality Check, the page keeps definitions, assumptions and limitations close to the working result so the method can be checked before it reaches a material decision. Where the subject depends on current rules or specifications, the linked primary source remains the final reference.
Last reviewed: September 29, 2026 · Martzine Editorial Team