Strategic Implementation of Marketing Mix Model Analytics for Data-Driven Decision Making: A Holistic View

Marketing Mix Modeling (MMM): Even with the evolution of traditional and digital marketing, marketing mix modeling has remained an area of primary focus. The sophistication within the econometric and statistical aspect of modern MMM might be impressive, but there are still numerous organizational and practicality problems left unresolved, especially for the data teams that have to work with broken datasets, trust problems, and implement solutions. In this paper, I single out the most important strategic steps needed for the successful implementation of MMM in data research. It unpacks the contemporary approaches that utilize diverse category data integration and reach-and-frequency powered funnels. It also analyzes real world examples of MMM cross-channel budget optimization. The final sections outline the remaining problems and issues with the suggested solutions and forms of future MMM, such as causal tests and modeling with constraints to privacy-sensitive data.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-07
DOI
https://doi.org/10.5281/zenodo.14945314
Primary Topic
Customer churn and segmentation
Type
article
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article

Strategic Implementation of Marketing Mix Model Analytics for Data-Driven Decision Making: A Holistic View

Zenodo (CERN European Organization for Nuclear Research)
Customer churn and segmentation
article

Strategic Implementation of Marketing Mix Model Analytics for Data-Driven Decision Making: A Holistic View

article en

Abstract

Marketing Mix Modeling (MMM): Even with the evolution of traditional and digital marketing, marketing mix modeling has remained an area of primary focus. The sophistication within the econometric and statistical aspect of modern MMM might be impressive, but there are still numerous organizational and practicality problems left unresolved, especially for the data teams that have to work with broken datasets, trust problems, and implement solutions. In this paper, I single out the most important strategic steps needed for the successful implementation of MMM in data research. It unpacks the contemporary approaches that utilize diverse category data integration and reach-and-frequency powered funnels. It also analyzes real world examples of MMM cross-channel budget optimization. The final sections outline the remaining problems and issues with the suggested solutions and forms of future MMM, such as causal tests and modeling with constraints to privacy-sensitive data.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 43%
Customer churn and segmentation
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