The task requires that a classifier model can give high prediction accuracy over 3G customer, while keeping reasonable misclassification rate for 2G customer. In this report, we firstly learn a classification model with high AUC(The area under the ROC curve) based on our latest research result in classification algorithm, and then find a optimal decision threshold from the resulting ROC(Receive...

A Joint Model of Usage and Churn in Contractual Settings As firms become more customer centric, concepts such as customer equity come to the fore. Any serious attempt to quantify customer equity requires modeling techniques that can provide accurate multi-period forecasts of customer behavior. While a number of researchers have explored the problem of modeling customer churn in contractual sett...

In this paper, we solve the customer credit card churn prediction via data mining. We developed an ensemble system incorporating majority voting and involving Multilayer Perceptron (MLP), Logistic Regression (LR), decision trees (J48), Random Forest (RF), Radial Basis Function (RBF) network and Support Vector Machine (SVM) as the constituents. The dataset was taken from the Business Intelligenc...

This paper studies the topic of customer attrition in the context of a European financial services company. More specifically, we investigate predictors of churn incidence as part of customer relationship management (CRM). We contribute to the existing literature: (1) by combining several different types of predictors into one comprehensive retention model including several ‘new’ types of time-...

Although much research on customer behaviors has demonstrated the positive role of inertia in the action loyalty phase, previous studies on inertia still emphasize the spurious dimension of customer loyalty. This study seeks to analyze how inertia varies with differing levels of alternative attractiveness, relationship length, and commitment in affecting customer loyalty. The results suggest th...

With the rising growth of telecommunication industry, customer churn problem has grown in significance as well. One most critical challenges data and voice service industry is retaining customers, thus reducing by increasing satisfaction. Telecom companies have depended on historical to measure churn. However, does not reveal current satisfaction or future likeliness switch between telecom comp...

Studying about the customer segmentation and begetting customer ranking plan diverts more attention in recent years. In this regard, this study tries on providing a methodology for segmenting customers based on their value driver parameters which extracted from transaction data and then ranks customers with regard to their customer lifetime value (CLV) score. Discovering hidden pattern between ...

Customer segmentation involves an identification of distinct customer groups. Traditionally, customers were segmented by some criteria such as location, type of business, and customer value. In this paper we determine a methodology for identifying appropriate customer segments by using customer satisfaction-demanding behavior that is characterized by the disparity of derived global satisfaction...

In this work, we presented the strategies and techniques that we have developed for predicting the near-future churners and win-backs for a telecom company. On a large-scale and real-world database containing customer profiles and some transaction data from a telecom company, we first analyzed the data schema, developed feature computation strategies and then extracted a large set of relevant f...

Different from explicit customer needs that can be identified directly by analyzing raw data from the customers, latent customer needs are often implied in the semantics of use cases underlying customer needs information. Due to difficulties in understanding semantic implications associated with use cases, typical text mining-based methods can hardly identify latent customer needs, as opposite ...