Episode 2:

Data Smoothing in MMM 

Episode 2:

Data Smoothing in MMM 

Data processing is one of the most important steps in the marketing mix flow. This stems from the variables that need to be transformed before being ingested into the model. In this video we explore the following processors:

1. Moving Average: It smoothens the input variable by sliding a window and calculating the local average using that window.

2. Median Filter: replaces each data entry with the median of neighboring entries. The pattern of neighbors is called the “window”, which slides, entry by entry, over the entire variable.

3. Seasonality: Detecting a seasonal pattern in sales is very important when dealing with highly seasonal products/ packages

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Data processing is one of the most important steps in the marketing mix flow. This stems from the variables that need to be transformed before being ingested into the model. In this video we explore the following processors:

1. Moving Average: It smoothens the input variable by sliding a window and calculating the local average using that window.

2. Median Filter: replaces each data entry with the median of neighboring entries. The pattern of neighbors is called the “window”, which slides, entry by entry, over the entire variable.

3. Seasonality: Detecting a seasonal pattern in sales is very important when dealing with highly seasonal products/ packages

Download the Presentation