Results 201 to 210 of about 2,799 (223)

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
openaire   +1 more source

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
openaire   +1 more source

Customer Churn Prediction by Hybrid Model

2006
In order to improve the performance of a data mining model, many researchers have employed a hybrid model approach in solving a problem. There are two types of approach to build a hybrid model, i.e., the whole data approach and the segmented data approach.
Jae Sik Lee, Jin Chun Lee
openaire   +1 more source

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

Customer churn prediction for retention analysis

Abstract This abstract provides a comprehensive overview of the research on Customer Churn Prediction for Retention Analysis. In today’s corporate context, understanding and mitigating customer churn has become critical for long-term success.
Rajesh Saturi, Siripothula Rahul, Zuha Siddiqui, Rachamalla Nikhitha   +3 more
openaire   +1 more source

Hybrid model for profit-driven churn prediction based on cost minimization and return maximization

Expert Systems With Applications, 2023
Zhenkun Liu, Lifang Zhang
exaly  

Predicting Churn Rate in Companies

2023
openaire   +1 more source

Customer churn prediction in telecommunication industry using data certainty

Journal of Business Research, 2019
Adnan Amin, Feras Al-Obeidat, Babar Shāh   +2 more
exaly