Decision Tree is a feature that allows user to select a specific audience.
How does it work ?
Tree illustration
Once the advertiser has clicked on the dot corresponding to the audience he wants to target, he will get the corresponding segmentation tree at the bottom of the interface
This tree enables to identify and visualize the key predictors (most explanatory variables) explaining a performance (conversion…)
These explanatory variables are the result of the Khi2 test which calculates the dependency of the variables vs the variable to explain
The red nodes are those that constitute the audience selected
Illustration:
The 3 segments in red represent 9.83 % (6.02+1.52+2.29) of the Negative segment and 17.6 % (12.60+2.98+1.98) of the Positive Segment
The number of Unique Users is 1768 (1445+239+84)
They have the highest performance index vs the other segment (2.94; 2.06 and 1.09)
For the first segment, the strongest explanatory variable is that they don’t play videogames (>9.5 index)
How to create audiences from decision tree ?
Once the audience is selected, save this segment by clicking on the
button at the bottom of the segmentation tree
Tip: audience label
Keep label of the audience created automatically. The pattern of the label is standardized
Illustration:
Test C-clones_2_UU_2.48_G_38.25
«2» is the second point of the abacus, starting from the left
« UU 2.48 » means 2.48% of the Negative segment
« G » is the expected performance
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