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Summary
Randomized controlled trials remain the gold standard for measuring advertising effectiveness, but they are often too costly and complex to deploy across every campaign. This MSI Working Paper introduces Predicted Incrementality by Experimentation (PIE), a new framework that uses data from a limited set of experiments to predict causal advertising effects for campaigns that are not directly tested. The research demonstrates that PIE can dramatically outperform traditional attribution metrics, offering marketers a practical way to scale causal measurement without scaling experimentation itself.
