Results 21 to 30 of about 1,692 (204)

Socio-Transactional Impact of Recency, Frequency, and Monetary Features oN Customers’ Behaviour in Telecoms’ Churn Prediction

open access: yesIraqi Journal for Computer Science and Mathematics, 2022
Due to the increasing competitiveness in telecom’s market, it has now become more necessary for operators to start building personal relationship with customers for targeted retention strategies.
Ayodeji O.J Ibitoye   +3 more
doaj   +1 more source

CUSTOMER CHURN PREDICTION

open access: yesINTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, 2023
Customer churn, the termination of customer relationships with a business or service, is a critical metric that profoundly impacts a company's success. Effectively managing churn not only prevents revenue loss but also provides a competitive advantage by boosting customer retention rates.
openaire   +2 more sources

Fuzzy particle swarm optimization (FPSO) based feature selection and hybrid kernel distance based possibilistic fuzzy local information C-means (HKD-PFLICM) clustering for churn prediction in telecom industry

open access: yesSN Applied Sciences, 2021
Customer churn has been considered as one of the key issues in the operations of the corporate business sector, as it influences the turnover directly.
C. K. Praseeda, B. L. Shivakumar
doaj   +1 more source

Bank Customer Churn Prediction

open access: yesIndian Journal of Data Mining, 2023
In the current challenging era, there is a stiff competition happening between the banking industries. To strengthen the grade and level of services they provide, banks focus on customer retention as well as the customer churning. Customer churning becomes one of the duties of corporate intelligences to speculate the number of customers leaving from ...
Jufin P A, Amrutha N
openaire   +2 more sources

MINIMAX PROBABILITY BASED CHURN PREDICTION FOR PROFIT MAXIMIZATION

open access: yesICTACT Journal on Soft Computing, 2021
Churn prediction has become a significant requirement for all customer centric organizations. Accurate prediction of churn can effectively improve customer loyalty and improve profits for the organization.
V Jude Nirmal
doaj   +1 more source

A Non-Sequential Representation of Sequential Data for Churn Prediction [PDF]

open access: yes, 2009
We investigate the length of event sequence giving best predictions when using a continuous HMM approach to churn prediction from sequential data. Motivated by observations that predictions based on only the few most recent events seem to be the most ...
Eastwood, Mark   +4 more
core   +1 more source

A Model for Customer Churn Management of an Internet Service Provider [PDF]

open access: yesمطالعات مدیریت کسب و کار هوشمند, 2022
Customer churning is one of the most important issues facing Internet Service Providers in a competitive and rapidly saturating market. Due to the high costs associated with attracting new customers, ISPs have turned to a customer retention approach that
Sahar Amiri   +2 more
doaj   +1 more source

B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM

open access: yesJournal of Theoretical and Applied Electronic Commerce Research, 2022
Customer churn prediction is very important for e-commerce enterprises to formulate effective customer retention measures and implement successful marketing strategies.
Xiancheng Xiahou, Yoshio Harada
doaj   +1 more source

Telecom Churn Prediction System Based on Ensemble Learning Using Feature Grouping

open access: yesApplied Sciences, 2021
In recent years, the telecom market has been very competitive. The cost of retaining existing telecom customers is lower than attracting new customers.
Tianpei Xu, Ying Ma, Kangchul Kim
doaj   +1 more source

Customer Segmentation and Churn Prediction via Customer Metrics

open access: yes2022 30th Signal Processing and Communications Applications Conference (SIU), 2022
In this study, it is aimed to predict whether customers operating in the factoring sector will continue to trade in the next three months after the last transaction date, using data-driven machine learning models, based on their past transaction movements and their risk, limit and company data.
Tunahan Bozkan   +3 more
openaire   +1 more source

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