Decision Tree is a feature in C-clone that allows user to select Gain and Volume of unique users from an audience to target specific users
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1- Select a Cclone segment then choose one point on the graph (Volume of Unique Users and Gain)
The graph shows the output of the algorithm, which is a classification of the internet users according to their affinity vs the parameter of the positive segment (variable to explain)
The vertical axis (expected gain) represents the performance index: a performance index is a cumulative % of the positive target within the segments over the % of the target within the negative segments defined as the reference population
The horizontal axis (% in database recency 1 day) represents the % of Weborama internet users defined as negative segment
Each blue dot along the green scoring curve represents a strong classifier family
These families are cumulated along the curve, so the advertiser can select his audience by checking the points along the curve, arbitrating between the % of the internet users targeted and the expected performance index
The dot with the most performing internet users is on the far left of the graph, but with the smallest volume of us
The dot with the largest volume of internet users is on the far right of the graph, but with a weaker performance index
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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
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For the first segment, the strongest explanatory variable is that they most probably have a psychotherapy (>=0.5 index)
3- Audience can be saved (and will be available in Audience monitoring)
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Keep label of the audience created automatically. The pattern of the label is standardized
Illustration:
Cclone main segments label = test
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