Results 181 to 190 of about 2,799 (223)

Customer churn prediction in telecommunications

Expert Systems With Applications, 2012
This paper presents a new set of features for land-line customer churn prediction, including 2 six-month Henley segmentation, precise 4-month call details, line information, bill and payment information, account information, demographic profiles, service orders, complain information, etc.
Tahar Kechadi
exaly   +2 more sources

ADTreesLogit model for customer churn prediction

Annals of Operations Research, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhou, Y, Li, L, Qi, J, Zhang, L, Liu, Y, Liang, L, Li, H, Shen, Y   +7 more
openaire   +5 more sources

Customer Churn Prediction in B2B Contexts

, 2019
While business-to-customer (B2C) companies, in the telecom sector for instance, have been making use of customer churn prediction for many years, churn prediction in the business-to-business (B2B) domain receives much less attention in existing literature.
Iris Figalist, Christoph Elsner, Jan Bosch, Helena Holmström Olsson   +3 more
openaire   +2 more sources

Customer churn prediction in the telecommunication sector using a rough set approach

Neurocomputing, 2017
Customer churn is a critical and challenging problem affecting business and industry, in particular, the rapidly growing, highly competitive telecommunication sector. It is of substantial interest to both academic researchers and industrial practitioners,
Adnan Amin, Sajid Anwar, Awais Adnan
exaly   +2 more sources

Customer churn prediction for web browsers [PDF]

Expert Systems with Applications, 2022
In the competitive web browser market, identifying potential churners is critical to decreasing the loss of existing customers. Churn prediction based on customer behaviors plays a vital role in customer retention strategies.
Xing Wu 0001, Pan Li, Ming Zhao, Ying Liu 0039, Rubén González Crespo, Enrique Herrera-Viedma   +5 more
openaire   +2 more sources

Customer Churn Prediction [PDF]

, 2020
Churned customers identification plays an essential role for the functioning and growth of any business. Identification of churned customers can help the business to know the reasons for the churn and they can plan their market strategies accordingly to enhance the growth of a business. This research is aimed at developing a machine learning model that
openaire   +1 more source

Employee churn prediction

Expert Systems with Applications, 2011
Customer churn is a notorious problem for most industries, as loss of a customer affects revenues and brand image and acquiring new customers is difficult. Reliable predictive models for customer churn could be useful in devising customer retention plans.
V. Vijaya Saradhi, Girish Keshav Palshikar   +1 more
openaire   +1 more source

Predicting player churn in the wild

2014 IEEE Conference on Computational Intelligence and Games, 2014
Free-to-Play or "freemium" games represent a fundamental shift in the business models of the game industry, facilitated by the increasing use of online distribution platforms and the introduction of increasingly powerful mobile platforms. The ability of a game development company to analyze and derive insights from behavioral telemetry is crucial to ...
Fabian Hadiji, Rafet Sifa, Anders Drachen, Christian Thurau, Kristian Kersting, Christian Bauckhage   +5 more
openaire   +2 more sources

Churn analysis: Predicting churners

Ninth International Conference on Digital Information Management (ICDIM 2014), 2014
Churners have always been a big issue for any service providing company. Churning increases cost of the company as well as decreases the rate of profit. Generally, customer attrition can be identified when they initiate the process of service termination.
Navid Forhad, Md. Shahriar Hussain, Rashedur M. Rahman   +2 more
openaire   +1 more source

A Hybrid Approach to Predict Churn

2010 IEEE Asia-Pacific Services Computing Conference, 2010
Acquiring new customers in any business is much more expensive than trying to keep the existing ones. As a result, many prediction algorithms have been proposed to detect churning customers. In this paper, the ordered weighted averaging (OWA) technique is brought to the attention of marketing researchers.
Javad Basiri, Fattaneh Taghiyareh, Behzad Moshiri   +2 more
openaire   +1 more source