Calibrating Marketing Mix Models (MMMs) with Incrementality Tests

Varun Chivukula

doi:10.15662/IJRAI.2023.0605009

Authors

Varun Chivukula University of California, Berkeley Author

DOI:

https://doi.org/10.15662/IJRAI.2023.0605009

Keywords:

MMM, ATT, GDPR, Randomized Control Trials, Bayesian Priors

Abstract

Marketing Mix Models (MMMs) are essential tools for determining the effectiveness of various marketing activities, but their reliance on aggregated data can limit causal insights. Incrementality tests, on the other hand, offer robust causal evidence at a granular level. This paper proposes a systematic approach to calibrating MMMs using incrementality test results to enhance predictive accuracy and decision-making. We also emphasize the evolving importance of MMMs in the context of heightened privacy regulations and changes such as Apple’s App Tracking Transparency (ATT) framework. We outline a step-by-step methodology, discuss potential challenges, and provide a case study to demonstrate the practical application of this integration.

References

1. Berger, J., & Schwartz, E. M. (2011). What drives immediate and ongoing word of mouth? Journal of Marketing Research, 48(5), 869-880.

2. Chan, T. Y., & Perry, M. K. (2017). Incrementality testing in digital marketing: Theory and applications. Marketing Science, 36(4), 500-519.

3. Hanssens, D. M. (2015). Empirical generalizations about marketing impact. Journal of Advertising Research, 55(3), 239-244.

4. Lewis, R. A., & Rao, J. M. (2015). The unfavorable economics of measuring the ROI of incremental advertising. Quarterly Journal of Economics, 130(4), 1941-1973.

5. Shapley, L. S. (1953). A value for n-person games. Contributions to the Theory of Games, 2(28), 307-317.

6. Srinivasan, V., & Hanssens, D. M. (2009). Marketing and firm value: Metrics, methods, findings, and future directions. Journal of Marketing Research, 46(3), 293-312.

7. Tellis, G. J., & Weiss, D. L. (1995). Does TV advertising really affect sales? The role of measures, models, and data aggregation. Journal of Advertising, 24(3), 1-12.

8. Wiesel, T., Pauwels, K., & Arts, J. (2011). Practice prize paper—Marketing's profit impact: Quantifying online and off-line funnel progression. Marketing Science, 30(4), 604-611.

9. Fisher, R. A. (1925). Statistical methods for research workers. Edinburgh: Oliver and Boyd.

10. Blattberg, R. C., & Neslin, S. A. (1990). Sales promotion: Concepts, methods, and strategies. Prentice Hall.