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Which operational miscalculations undermine marketing mix modeling?
| Miscalculation | Root cause | Econometric failure | Corrective protocol |
|---|---|---|---|
| Accepting high $R^2$ as proof of causality | Overfitting dozens of regressors to limited time periods | Mistaking collinear trend-fitting for true causal elasticity | Evaluate out-of-sample prediction and holdout tests |
| Omitting organic demand drivers | Failing to model pricing moves, product releases, and PR events | Marketing coefficients artificially absorb baseline sales | Instrument explicit controls for price changes and macro index |
| Ignoring spend endogeneity | Automated ad tools spend more when sales are already surging | Regression interprets correlation as advertising persuasion | Implement instrumental variables or experimental priors |
| Using static adstock parameters | Forcing identical decay rates across diverse digital channels | Overestimates search longevity; underestimates brand half-life | Calibrate channel-specific decay parameters via decay audits |
| Operating MMM without experiments | Relying entirely on observational historical data | Model drifts into statistically confident delusion | Mandate quarterly randomized holdouts to anchor priors |
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Reference & Evidence
Source: Table from this essay. Sources and interpretation are given in the article.
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