Results 171 to 180 of about 17,717 (205)

Call Churn Prediction with PySpark

2019
Different markets over the world are ending up progressively more saturated, with an ever-increasing number of customers swapping their enrolled benefits between contending organizations. Consequently, organizations have understood that they should center their promoting endeavors in client maintenance instead of client procurement.
Mark Sheridan Nonghuloo, Rangapuram Aravind Reddy, Ganji Manideep, M. R. SarathVamsi, K. Lavanya   +4 more
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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   +4 more sources

Adoption of Churn Recognition System to Predict Customer Churn

2023
In the cutthroat competitive arena, it is a very challenging task for any enterprise to make a balance between retaining its existing loyal customers and attracting new customers. It is a tedious task to find the right segment of active customers and understand the reason behind churn numbers. It is said that it is five times more costly to attract new
Yuvraj Sharma, Rajender Gurram, Naveen Saharan   +2 more
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Customer Churn Prediction for Telecom Services

2012 IEEE 36th Annual Computer Software and Applications Conference, 2012
Customer churn is a big concern for telecom service providers due to its associated costs. This short paper briefly explains our ongoing work on customer churn prediction for telecom services. We are working on data mining methods to accurately predict customers who will change and turn to another provider for the same or similar service.
Utku Yabas, Hakki C. Cankaya, Turker Ince   +2 more
openaire   +1 more source

Customer Churn Prediction in Virtual Worlds

2015 IIAI 4th International Congress on Advanced Applied Informatics, 2015
With the emerging of social network websites, more and more social network online games are booming. Players have more alternatives of VWs games, while platform providers suffer from the problems of high customer turnover rate and low-customer-loyalty.
Hsiu-Yu Liao, Kuan-Yu Chen, Duen-Ren Liu, Yi-Ling Chiu   +3 more
openaire   +1 more source

Deep Neural Pipeline for Churn Prediction

2018 17th RoEduNet Conference: Networking in Education and Research (RoEduNet), 2018
Customer churn is an essential retail metric used in business predictive analytics systems to quantify the number of customers who left a company. All retail and business to consumer companies carefully analyze customer behavior to prevent them to cease their relationship with the company, in other words to make churn.
Andrei Simion-Constantinescu, Andrei Ionut Damian, Nicolae Tapus, Laurentiu-Gheorghe Piciu, Alexandru Purdila, Bogdan Dumitrescu   +5 more
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TreeLogit Model for Customer Churn Prediction

2006 IEEE Asia-Pacific Conference on Services Computing (APSCC'06), 2006
For the purpose of improving the predictive accuracy and interpret ability of churn prediction model, TreeLogit model, which integrates the advantage of AD tree model and logistic regression model, is proposed in this paper to predict customers' churn propensities.
Jiayin Qi, Yangming Zhang, Yingying Zhang, Shuang Shi   +3 more
openaire   +1 more source

Predicting Customer Churn for Insurance Data

2020
Most organisations employ customer relationship management systems to provide a strategic advantage over their competitors. One aspect of this is applying a customer lifetime value to each client which effectively forms a fine-grained ranking of every customer in their database. This is used to focus marketing and sales budgets and, in turn, generate a
Michael Scriney, Dongyun Nie, Mark Roantree   +2 more
openaire   +1 more source

Predicting Customer Churn at QWE Inc.

Darden Business Publishing Cases, 2017
This case exposes students to predictive analytics as applied to discrete events with logistic regression. The VP of customer services for a successful start-up wants to proactively identify customers most likely to cancel services or “churn.” He assigns the task to one of his associates and provides him with data on customer behavior and his intuition
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KNNs and Sequence Alignment for Churn Prediction

2013
Large companies interact with their customers to provide a variety of services to them. Customer service is one of the key differentiators for companies. The ability to predict if a customer will leave in order to intervene at the right time can be essential for pre-empting problems and providing high level of customer service. The problem becomes more
Mai Le, Detlef D. Nauck, Bogdan Gabrys, Trevor Martin   +3 more
openaire   +1 more source