After creating your Marketing Mix Model, you need to provide the business with actionable insights they can use to optimize the performance of their brands. This is where Optimization comes in, as part of the deployment phase of the MMM workflow. If you’re not confident yet with your model performance, check the previous article, from…
Previously in the series, we explained the powerful uses of log-linear modeling. In this article, we learn about nested modeling, the advanced technique used to disentangle the impact of interactions between marketing channels. When doing MMMs, you would ideally have each marketing variable influence sales separately: Search activity influences sales. TV influences sales etc. This…
Imagine you’re the CEO of an ice cream company. You have the best-selling ice cream in the nation. Very tasty stuff! One day, you notice your sales numbers dropping. You look at the possible suspects but you’re not seeing an obvious reason for the decrease. You look for a way to understand exactly what’s driving…
Discover the Difference between Frequentist and Bayesian Regression in Marketing Mix Modeling. Learn how they impact your marketing strategies
Read this article to know how you can get Insights through Pooled Regression in Marketing Mix Modeling with MASS Analytics.
Two of the key concepts in Marketing Mix Modeling is the relationship between ROI and Contribution. Because of diminishing returns, as the contribution increases, and the more the business spends on a channel, the less marginal contribution it will generate. This translates into a decreasing ROI. Because of this dilemma, the MMM analyst must ensure…
In the previous part of this MMM Guide series, we explored one of the corner stones of Marketing Mix Modeling, which is Regression Analysis. In this article we cover some of the ways in which you can ensure the robustness of your model and reliability of your results.
In MMM, it is inevitable that some variables are not relevant to the model. Often they contain such a large measurement error that they become irrelevant for the analysis. The question that should be asked now is: what is the procedure that should be applied to ensure only relevant variables are kept? That’s where model
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Learn about regression analysis in this comprehensive guide. Explore the concepts of simple and multiple regression, and how to apply them to your data. Enhance your statistical skills for Marketing Mix Modeling today.