Attribution · Incrementality · Data · Reporting
Compared with what?
Most marketing measurement measures correlation and calls it causation. This site is about the difference — what the data can support, what it cannot, and where the gap costs money. Teams that need a practical example of how work activity is recorded can review Monitask. For a formal treatment of ranges and uncertainty, see NIST guidance on measurement uncertainty.
6 articles
Measurement
What the data can and cannot tell you: attribution, incrementality, causation and the counterfactual you never observe.
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Collection
Tracking, consent, identity and invalid traffic — what actually reaches your reports and what does not.
Read the section →10 articles
Analysis
Tests, metrics, cohorts, forecasts and the reports built on them.
Read the section →9 articles
Practice
Measurement plans, data quality, stakeholders and the conversations that decide whether any of it is used.
Read the section →Six to start with
Measurement
What Attribution Actually Measures, and What It Does Not
An attribution report tells you which touchpoints appeared before a conversion. It does not tell you which caused it, and no model weight changes that.
Measurement
Incrementality: The Only Question Worth Asking
What would have happened without the spend. How to actually measure it, what each method costs, and why the answer is usually smaller than the report.
Data Collection
What Actually Broke When Third-Party Cookies Went Away
Chrome reversed the deprecation and shut down most of Privacy Sandbox. The cookieless future was cancelled; the cookieless present arrived anyway.
Analysis
A/B Tests: The Five Ways They Go Wrong
Peeking, underpowering, multiple comparisons, broken randomisation and the wrong metric. Each produces a confident result that is not true.
Practice
Answering \\"Did the Campaign Work?\\" Honestly
The question has no clean answer without a comparison group. What to say instead of guessing, and how to get a real answer next time.
Analysis
Metrics That Mislead: Rates, Averages and Survivorship
A rate can move because the denominator changed. An average can describe nobody. And the data you have is the data that survived. Three failures, everywhere.