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
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).
Wondering when to update your MMM model? Here is a guide 👇 Predominantly, a Machine Learning model needs to be updated for two reasons: 1.
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 !! We have built 30 Markov Attribution models for companies across geographies in the
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) helped me learn Linear Regression from first Principles. Some of you have appreciated my posts on Linear Regression and other
Why we report both confidence Interval and Prediction Interval in our MMM models. MMM is a type of linear regression but with lot more bells
Selecting MMM models via AIC? Some key pointers 👇 The Akaike information criterion (AIC) is given by: AIC = 2k -2ln(L) where k is the
Calibration vs Validation A lot of people use calibration and Validation interchangeably. The two are not the same. ▪ Calibration In a regression setting, calibration
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