A Correlation Heatmap Is Not A Cause Map
Explain why correlated metrics do not automatically establish cause and effect.
A relationship between two metrics is evidence of association, not automatic evidence of mechanism. Why correlation still matters Correlation helps teams spot patterns worth investigating. It is excellent for finding leads, monitoring risk, and identifying segments that behave differently. Why it is not enough The same pattern can come from reverse causation, selection bias, or a third variable that affects both measures. Without addressing those possibilities, the causal story is fragile. The business discipline Use correlation to generate hypotheses. Use stronger design and better controls before you call something a cause.
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