This new feature allows comparing a segment with a selected benchmark (either the entire data set, or another segment). The comparison is based on how the observable variables of the segment can impact the Target node value.
The Impact for each observable variable is computed as follow:
is the analyzed segment,
is the benchmark,
is the mean value of on the data set defined by the segment or the benchmark,
is the effect of on the Target node, evaluated on the benchmark.
Four types of effects are available:
Let's take the Perfume example for which we have defined five segments with the Breakout Variable Product, namely Prod3, Prod4, ProdG1, ProdG5 and Prod G6.
Below is the table with the Standardized Total Effects of all the observable variables on Purchase Intent, and the mean values of these variables, computed on the entire data set, and on the segment represented by Prod3.