A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy
R Sudharsan, EN Ganesh - Connection Science, 2022 - Taylor & Francis
Owing to saturated markets, fierce competition, dynamic criteria, along with introduction of
new attractive offers, the considerable issue of customer churn was faced by the …
new attractive offers, the considerable issue of customer churn was faced by the …
A churn prediction model using random forest: analysis of machine learning techniques for churn prediction and factor identification in telecom sector
In the telecom sector, a huge volume of data is being generated on a daily basis due to a
vast client base. Decision makers and business analysts emphasized that attaining new …
vast client base. Decision makers and business analysts emphasized that attaining new …
Telecom churn prediction and used techniques, datasets and performance measures: a review
Customer churn prediction in telecommunication industry is a very essential factor to be
achieved and it makes direct impact to customer retention and its revenues. Developing a …
achieved and it makes direct impact to customer retention and its revenues. Developing a …
Customer churn prediction in telecommunication industry using data certainty
Abstract Customer Churn Prediction (CCP) is a challenging activity for decision makers and
machine learning community because most of the time, churn and non-churn customers …
machine learning community because most of the time, churn and non-churn customers …
Amalgamation of customer relationship management and data analytics in different business sectors—A systematic literature review
Customization of products or services is a strategy that the business sector has embraced to
build a better relationship with the customers to cater to their individual needs and thus …
build a better relationship with the customers to cater to their individual needs and thus …
[Retracted] An Empirical Study on Customer Segmentation by Purchase Behaviors Using a RFM Model and K‐Means Algorithm
J Wu, L Shi, WP Lin, SB Tsai, Y Li… - Mathematical …, 2020 - Wiley Online Library
In this paper, we base our research by dealing with a real‐world problem in an enterprise. A
RFM (recency, frequency, and monetary) model and K‐means clustering algorithm are …
RFM (recency, frequency, and monetary) model and K‐means clustering algorithm are …
A social CRM analytic framework for improving customer retention, acquisition, and conversion
S Lamrhari, H El Ghazi, M Oubrich… - … Forecasting and Social …, 2022 - Elsevier
Abstract Social Customer Relationship Management (social CRM) has become one of the
central points for many companies seeking to improve their customer experience. It …
central points for many companies seeking to improve their customer experience. It …
Churn prediction in telecommunication using logistic regression and logit boost
Today in every industry weather, it is ISP, IT products, social network or mobile services
there is the problem of customer churn (Customers changing their services from one service …
there is the problem of customer churn (Customers changing their services from one service …
[PDF][PDF] Machine-learning techniques for customer retention: A comparative study
SF Sabbeh - … Journal of advanced computer Science and …, 2018 - pdfs.semanticscholar.org
Nowadays, customers have become more interested in the quality of service (QoS) that
organizations can provide them. Services provided by different vendors are not highly …
organizations can provide them. Services provided by different vendors are not highly …
Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoring
Y Wang, Y Jia, Y Tian, J Xiao - Expert Systems with Applications, 2022 - Elsevier
Customer credit scoring is a dynamic interactive process. Simply designing the static reward
function for deep reinforcement learning may be difficult to guide an agent to adapt to the …
function for deep reinforcement learning may be difficult to guide an agent to adapt to the …