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Uplift modelling : ウィキペディア英語版 | Uplift modelling Uplift modelling, also known as incremental modelling, true lift modelling, or net modelling is a predictive modelling technique that directly models the incremental impact of a treatment (such as a direct marketing action) on an individual's behaviour. Uplift modelling has applications in customer relationship management for up-sell, cross-sell and retention modelling. It has also been applied to political election and personalised medicine. Unlike the related Differential Prediction concept in psychology, Uplift Modelling assumes an active agent. == Introduction == Uplift modelling uses a randomised scientific control to not only measure the effectiveness of a marketing action but also to build a predictive model that predicts the incremental response to the marketing action. It is a data mining technique that has been applied predominantly in the financial services, telecommunications and retail direct marketing industries to up-sell, cross-sell, churn and retention activities.
抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Uplift modelling」の詳細全文を読む
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