Correlation vs. Causation

The principle that two metrics moving together does not prove one causes the other; establishing cause requires experiments or causal methods.

By Brandon MinaCEO, BrandPilot AIUpdated November 2026

Short answer

Correlation vs. causation is the principle that two metrics moving together does not prove one causes the other. A third factor, such as seasonality, may drive both. In marketing, proving that a campaign caused results requires controlled experiments, incrementality tests or causal modeling rather than simply observing that sales rose alongside spend.