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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 then click on a graph one point (Volume of Unique Users and Gain)

2- Decision Tree is displayed with the different segments and volume from selected previous point

3- Audience can be saved


Keep label of the audience created automatically. The pattern of the label is standardized

Illustration:

Cclone main segments label = test

CCclone newly created label = test_4_UU_4.39_G_13.25

  • «4» is the second point of the abacus, starting from the left

  • « UU 4.39 » means 4.39% of the Negative segment

  • « G » is the expected performance

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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