Abstract The telecommunications market is well developed but characterized by oversaturation and high levels of competition. Based on this, the urgent problem to retain customers predict outflow customer base switching subscribers services competitors. Data Science technologies data mining methodology create significant opportunities for companies that implement analysis modeling development ch...

In today’s competitive world, organizations are in a constant struggle to retain their current customers while attracting new through various methods. Customer churn is major challenge different industries and companies. Despite initial successful attempts at customers, soon face the fact that may turn away toward rivals. By identifying candidates, will be able guarantee future success by revis...

Abstract Customer churn has been considered as one of the key issues in operations corporate business sector, it influences turnover directly. In particular, telecom industries are seeking to develop new approaches predict potential customer churn. So, needs appropriate algorithms overcome increasing problem This work proposed a prediction model that employs both strategies classification and c...

INTRODUCTION: Customer churn is a severe problem of migrating from one service provider to another. Due the direct influence on company's sales, companies are attempting promote strategies identify prospective consumers. Hence it necessary examine issues that customer yield effective solutions minimize churn. OBJECTIVES: The major purpose this work create model prediction assists telecom operat...

The availability of abundant data posts a challenge to integrate static customer data and longitudinal behavioral data to improve performance in customer churn prediction. Usually, longitudinal behavioral data are transformed into static data before being included in a prediction model. In this study, a framework with ensemble techniques is presented for customer churn prediction directly using...

Recent studies suggest that unstructured data such as customer comments or feedback can enhance the power of existing predictive models. SAS® Text Miner can generate SVD (Singular value decomposition) units from text documents which is a vectorial representation of terms in documents. These SVDs when used as additional inputs along with the existing structured input variables often prove to cap...

With the increasing competition pressure among tourism e-commerce platforms, how to reduce customer churn greatest extent is of great significance platforms. Based on this, this paper takes Ctrip's hotel customer-related data as an example, and first uses a supervised feature selection method based mutual information select features that have important impact churn. Then, by using cross-validat...