Predicting And Clustering Customer to Improve Customer Loyalty and Company Profit
Predicting And Clustering Customer to Improve Customer Loyalty and Company Profit
Author : JUDI ALHILMAN; WIYONO; MARINA YUSTIANA LUBIS; moch. rian m Published on : ICoICT 2014(Telkom University - Bandung Indonesia)
Abstract
A PT X is a state-owned enterprise that provides the largest telecommunications services and network in Indonesia. By the growing challenges in the telecommunications industry, PT X must carefully take care of their customers by improving its services in order to make them satisfied and loyal. One of the effort that can be done by PT X is determining and predicting their customer???s category, so that PT X knows their customer???s behaviour and can better treat them. Some algorithms in data mining, as well as databases including customer data bank, usage, revenue, and payment were collected and merged to form a master data, are brought into play for this purpose using IBM SPSS Modeller software. The outcomes are customer???s category prediction and customer???s cluster who moved from productive (generating revenue) category to unproductive category (not generating revenue), and based on these outcomes we then recommend actions to be taken, like up selling, cross selling, customer education, switching to other packet best suited customer???s need.
