Standardization before Regularization in MMM
Standardization before Regularization in MMM In my last post (link under resources), I covered the topics of Multicollinearity and Endogeneity. And how solving for Multicollinearity
Marketing Mix Modeling
How common are S-curves in Marketing Mix Models (MMM)?
How common are S-curves in Marketing Mix Models (MMM)? Before we dwell on the S-curves, let’s talk about the Hill function. Did you know that
Multicollinearity is one of the enemies of Marketing Mix Modeling (MMM).
Multicollinearity is one of the enemies of Marketing Mix Modeling (MMM). Multicollinearity generally occurs when there is a high correlation between independent variables. Multicollinearity does
CMMMO = CSO
The Chief Scrutinizing Officer (CSO) Every Marketing Mix Modeling (MMM) project or for that matter any Data Science project needs a Chief Scrutinizing Officer (CSO).
MMM Model Update – What, Why and When
Wondering when to update your MMM model? Here is a guide 👇 Predominantly, a Machine Learning model needs to be updated for two reasons: 1.
What is the best Marketing Budget Allocation
Marketing Budget Allocation One of the important use cases of MMM is the Marketing Budget Allocation. The results of MMM are directly leveraged to provide
Marketing Mix Modeling (MMM) and MTA are like X-ray into your marketing strategy.
Marketing Mix Modeling (MMM) and MTA are like X-ray into your marketing strategy. Much like an X-ray. They tell you: ✅ Which strategy is broken.
7 key steps to get your Multi Touch Attribution (MTA) right
7 key steps to get your Multi Touch Attribution (MTA) right !! We have built 30 Markov Attribution models for companies across geographies in the
Don’t Stepwise Regression your MMM model
So recently a client hired us to build MMM models for them after failed attempts to in-house the MMM capability. Earlier their in-house Machine Learning
How Marketing Mix Modeling (MMM) can help you learn Linear Regression from first Principles.
How Marketing Mix Modeling (MMM) helped me learn Linear Regression from first Principles. Some of you have appreciated my posts on Linear Regression and other
