Results 231 to 240 of about 25,623,750 (294)

Deep Learning Based Customer Churn Analysis

2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), 2019
Traditional customer churn is predicted by machine learning and data mining methods. The advantages of big data are not fully utilized. In this paper, we use deep learning based customer churn analysis to establish a predictive model of customer churn, to achieve a warning real time.
Shulin Cao, Wei Liu, Yuxing Chen, Xiaoyan Zhu 0005   +3 more
openaire   +2 more sources

Client Churn Prediction with Call Log Analysis [PDF]

, 2018
Client churn prediction is a classic business problem of retaining customers. Recently, machine learning algorithms have been applied to predict client churn and have shown promising performance comparing to traditional methods. Despite of its success, existing machine learning approach mainly focus on structured data such as demographic and ...
Nhi N. Y. Vo, Shaowu Liu, James Brownlow, Charles Chu, Ben Culbert, Guandong Xu   +5 more
openaire   +2 more sources

Customer Churn Analysis

2020 28th Signal Processing and Communications Applications Conference (SIU), 2020
In this study, a system has been developed to predict customers who may leave the private pension system. For this purpose, a training data set was formed by combining the churn contracts in the previous months or years with nonchurn contracts for both classes equally. In the train data set, attribute selection was made and learning models were created.
Serdar Yildiz, Onur Aydemir, Iskender Yilmaz, Ayhan Say, Songül Varli   +4 more
openaire   +3 more sources

Customer Churn Analysis in Financial Domain using Deep Intelligence Network

2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 2023
Customer churn analysis is regarded as a crucial indicator that determines the revenues and profitability of the organisation in the modern day due to the advancement of technology and business models. Regardless of the company's size including startups,
Sandeep Kumar Hegde, Rajalaxmi Hegde, S. Nanda, Gururaj Phatak, Pushpa Hongal, Dankan Gowda V   +5 more
semanticscholar   +1 more source

A Data-Driven Decision Support Framework for Player Churn Analysis in Online Games

Knowledge Discovery and Data Mining, 2023
Faced with saturated market and fierce competition of online games, it is of great value to analyze the causes of the player churn for improving the game product, maintaining the player retention. A large number of research efforts on churn analysis have
Yu Xiong, Runze Wu, Shiwei Zhao, Jianrong Tao, Xudong Shen, Tangjie Lyu, Changjie Fan, Peng Cui   +7 more
semanticscholar   +1 more source

Asfalis: A Web-based System for Customer Retention Strategies Optimization of a Car Insurance Company Using Cohort and Churn Analysis

International Congress on Information and Communication Technology, 2023
Customer retention is critical in the car insurance industry, marked by a 22% annual churn rate. Existing customer relationship management platforms primarily cater to e-commerce or online stores, neglecting the unique requirements of the insurance ...
Milagros Ortega, Jericho Quintanilla, Edward Ryan Ong, Raymond Marius Ramos, Carla Joy Trinidad   +4 more
semanticscholar   +1 more source

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

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

Sequential one‐step estimator by sub‐sampling for customer churn analysis with massive data sets

Journal of the Royal Statistical Society: Series C (Applied Statistics), 2022
Customer churn is one of the most important concerns for large companies. Currently, massive data are often encountered in customer churn analysis, which bring new challenges for model computation.
Feifei Wang, Danyang Huang, Tiancheng Gao, Shuyuan Wu, Hansheng Wang   +4 more
semanticscholar   +1 more source

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

Customer Churn Analysis with Deep Learning Methods on Unstructured Data

2021 Innovations in Intelligent Systems and Applications Conference (ASYU), 2021
In this study, customer churn analysis is performed using various deep learning approaches. Customer churn analysis systems try to predict whether customers will continue to use the products or not, and this analysis allows companies to increase their ...
Yunus Emre Özköse, Ali Haznedaroglu, L. Arslan   +2 more
semanticscholar   +1 more source