International Journal of Engineering and Technical Research (IJETR) ISSN: 2321-0869, Volume-3, Issue-5, May 2015 46 www.erpublication.org Abstract— Telecommunication market is expanding day by day. Companies are facing a severe loss of revenue due to increasing competition hence the loss of customers. They are trying to find the reasons of losing customers by measuring customer loyalty to regain the lost customers. The customers leaving the current company and moving to another telecom company are called churn. The research paper is using data mining technique and R package to predict the results of churn customers on the benchmark Churn dataset available from (http://www.dataminingconsultant.com/data/churn.txt). The R tool has represented the large dataset churn in form of graphs which depicts the outcomes in various unique pattern visualizations. The Churn Factor is used in many functions to depict the various areas or scenarios where churners can be distinguished. The paper is considering churn factor in account to depict various patterns for churners. R is a powerful statistical programming tool which can represent the dataset graphically with respect to different parameters and it also uses different packages available. Churns can be reduced by analyzing the past history of the potential customers systematically. In the past few years, the fast emerging requirements from both academia and industry has helped R programming language to emerge as one of the necessary tool for visualization, computational statistics and data science Index Terms—Churn, R Tool, Telecommunication, Data mining. I. INTRODUCTION Numerous telecom companies are present all over the world. Telecommunication market is facing a severe loss of revenue due to increasing competition among them and loss of potential customers. Many companies are finding the reasons of losing customers by measuring customer loyalty to regain the lost customers. To keep up in the competition and to acquire as many customers, most operators invest a huge amount of revenue to expand their business in the beginning. Therefore, it has become important for the operators to earn back the amount they invested along with at least the minimum profit within a very short period of time. 1.1 Churn Prediction Churn in the terms of telecommunication industry are the customers leaving the current company and moving to another telecom company. With the increasing number of churns, it becomes the operator‘s process to retain the profitable customers known as churn management. In telecommunication industry each company provides the customers with huge incentives to lure them to switch to their Ms.Manpreet Kaur, Student, Guru Gobind Singh Indraprastha University, Institute Of Information Technology & Management, MCA, Trainee at NIIT TECHNOLOGIES, DELHI , INDIA. Dr. Prerna Mahajan, Professor, Department of Computer Science,Guru Gobind Singh Indraprastha University/ Institute of Information Technology & Management, Delhi/India services, it is one of the reasons that customer churn is a big problem in the industry nowadays. To prevent this, the company should know the reasons for which the customer decides to move on to another telecom company. It is very difficult to keep customers intact for long duration as they move to the service that suits most of their needs. 1.2 Types Telecom Churns can be classified in two main categories: Involuntary and Voluntary. Of the two, Involuntary are easier to identify. Involuntary churn are those customers whom the Telecom industry decides to remove as a subscriber. They are churned for fraud, non-payment and those who don‘t use the service. On the other hand, Voluntary churn are difficult to determine, here it is the decision of the customer to unsubscribe from the service provider. Voluntary churn can further be classified as incidental and deliberate churn. The former occurs without any prior planning by the churn but due to change in the financial condition, location, etc. Whereas, the latter happens for technological advancement, economics, quality factors and convenience reasons. Most operators are trying to deal with these type of churns mainly. 1.3 Managing Churns Churn management is very important for reducing churns as acquiring a new customer is more expensive than retaining the existing ones. Churn rate is the measurement for the number of customers moving out and in during a specific period of time. If the reason for churning is known, the providers can then improve their services to fulfill the needs of the customers. Churns can be reduced by analyzing the past history of the potential customers systematically. Large amount of information is maintained by telecom companies for each of their customers that keeps on changing rapidly due to competitive environment. This information includes the details about billing, calls and network data. The huge availability of information arises the scope of using Data mining techniques in the telecom database. The information available can be analyzed in different perspectives to provide various ways to the operators to predict and reduce churning. Only the relevant details are used in analysis which contribute to the study from the information given. Data mining techniques are used for discovering the interesting patterns within data. One of the most common data mining technique is Classification, its aim is to classify unknown cases based on the set of known examples into one of the possible classes. Here, in case of telecom churn, Classification helps learn to predict whether a customer will churn or not based on customer‘s data stored in database. II. BACKGROUND 2.1. Data Mining Techniques The process of reducing, analyzing the patterns, predicting the hidden and useful required information from large Database is known as Data Mining. Association rule mining, Churn Prediction in Telecom Industry Using R Manpreet Kaur, Dr. Prerna Mahajan