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In the telecommunications industry,
the “churn”and “no churn” prediction is
usually expressed as a lift curve.
The lift curve plots the fraction of all churners
having churn probability above the threshold
against the fraction of all subscribershaving
churn probability above the threshold.
The lift curve indicates the fraction of all churners
can be caught if a certain fraction of all subscribers were contacted.
Since the customer services centers of a carrier
only have a fixed number of staff that is
able to contact a fixed fraction of all subscribers,
the lift curve, which can estimate the fraction of churners
can becaught given the limited resources, is very useful in
the telecommunications industry.
The lift curve representing perfect discrimination of
churners from nonchurners and that representing
no discrimination of churners from nonchurners
under a churn rate of 5% are shown in Fig. 8(a) and (b), respectively.
We refer to the former and the latter as
perfect churn predictor and random churn predictor
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