CUSTOMER RESPONSE PREDICTIVE ANALYSIS USING UPLIFT MODELLING
Authors
Keywords
uplift modeling, customer response modelling, decision tree, direct marketing
Summary
Traditional customer response models are based on the understanding that marketing campaign effectiveness could be measured by predicting response probabilities of each customer. Such approach seems to be very reasonable and in most cases it gives better results than random targeting. A fundamental problem of response modelling is that it does not separate the impact of a campaign from other stimuli and spontaneous responses because response models predict the wrong thing. They model and predict response probabilities, not the change in those probabilities as a result of the given marketing intervention. Following the understanding that traditional response models do not give optimal marketing decisions, the goal of this study is to define, estimate and apply on a real data base uplift model for predicting the change in customer behaviour resulting from marketing action. The specific tasks relate to studying the opportunities of a relatively new and less familiar methodology for identifying hesitant and persuadable customers. The study illustrates the application of the direct approach for uplift modeling and demonstrates its significant advantages over targeting based on uplift models over traditional response models.
Pages: 33
Price: 3 Points
