Customer Churn Prediction in Telecommunication Industry. A Data Analysis Techniques Approach

نویسندگان

چکیده

Telecommunications is one of the most dynamic sectors in market, where customer base an important pawn receive safe revenues, so to focus attention paid maintaining them with active status. Migrating customers from network another varies among telecommunication companies depending on different factors such as call quality, pricing plan, minute consumption, data, sms facilities, billing issues, etc. Determining effective predictive model helps detect early warning signals when churn occurs and assigns each a score called “churn score” that indicates likelihood individual might migrate over predefined time period. To this extent, present paper uses more than 10k sample company tries analyse behavior. The aim both test efficiency performance commonly used data mining techniques predict behavior underline main indicators can be conducting analyses. Knowing magnitude phenomenon, prevent instability going occur by applying series measure order increase retention current customers.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Data Mining Techniques in Customer Churn Prediction

Customer churn prediction is one of the most important problems in customer relationship management (CRM). Its aim is to retain valuable customers to maximize the profit of a company. To predict whether a customer will be a churner or non-churner, there are a number of data mining techniques applied for churn prediction, such as artificial neural networks, decision trees, and support vector mac...

متن کامل

A Review on Customer Churn Prediction in Telecommunication Using Data Mining Techniques

Customer churn is the term which indicates the customer who is in the stage to leave the company. Particularly it is happening recurrently in the telecommunication industry and the telecom industries are also in a position to retain their customer to avoid the revenue loss. Prediction of such behaviour is very vital for the present market and competition and Data mining is the one of the effect...

متن کامل

A Comparative Study of Techniques to Predict Customer Churn in Telecommunication Industry

In present days there is huge competition between various companies in the industry. Due to this companies pay more attention towards their customers rather than their product. They become aware of customer churn issue. Basically when a customer ceases one’s relationship with the company, this misfortune of relationship is known as customer churn. Various data mining approaches are used to pred...

متن کامل

Optimizing Coverage of Churn Prediction in Telecommunication Industry

Companies are investing more in analytics to obtain a competitive edge in the market and decision makers are required better identification among their data to be able to interpret complex patterns more easily. Alluring thousands of new customers is worthless if an equal number is leaving. Business Intelligence (BI) systems are unable to find hidden churn patterns for the huge customer base. In...

متن کامل

Customer Churn Analysis In Banking Sector Using Data Mining Techniques

Customer churn has become a major problem within a customer centred banking industry and banks have always tried to track customer interaction with the company, in order to detect early warning signs in customer's behaviour such as reduced transactions, account status dormancy and take steps to prevent churn. This paper presents a data mining model that can be used to predict which customers ar...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Postmodern Openings

سال: 2022

ISSN: ['2068-0236', '2069-9387']

DOI: https://doi.org/10.18662/po/13.1sup1/415