Churn Prediction using Dynamic RFM-Augmented …

Churn Prediction using Dynamic RFM-Augmented node2vec Sandra Mitrovi , Jochen de Weerdt, Bart Baesens & Wilfried Lemahieu Department of Decision Sciences and Information Management, KU Leuven 18 September 2017, DyNo Workshop, ECML 2017 Skopje, Macedonia Outline Introduction Motivation Methodology Experimental evaluation Results Conclusion Future work 2 Churn Prediction using Dynamic RFM-Augmented node2vec Introduction Churn Prediction (CP) Predict which customers are going to leave company s services o Still considered as topmost challenge for Telcos (FCC report, 2009) Due to acquisition/retention cost imbalance Different types of data used for CP o Subscription, socio-demographic, customer complaints etc.

Churn Prediction using Dynamic RFM-Augmented node2vec Sandra Mitrovi ć, Jochen de Weerdt, Bart Baesens & Wilfried Lemahieu …

Loading..

Tags:

  Using, Dynamics, Prediction, Augmented, Prediction using dynamic rfm augmented, Prediction using dynamic rfm augmented node2vec, Node2vec

Information

Related search queries