Decision Tree is a feature in C-clone that allows user to select a specific audience.
How does it work ?
1- Select a Cclone audience segment then click on a graph one point (Volume of Unique Users and Gain)
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2- Decision Tree is displayed with the different segments and volume from selected previous point
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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
Explanation
Negative segment = Sum of “Database” % points in red (0.70+1.80+0.83+1.06 = 4.39)
Positive Segment =Sum of “% Target” points in red (1.09+2.06+1.06+1.08 = 5.29)
number of Unique Users = Sum of “Volume Target” points in red (140+59+73+6 = 278)
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)
3- Audience can be saved
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Keep label of the audience created automatically. The pattern of the label is standardized
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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)
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How to create audiences from decision tree ?
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