Most research about Machine Learning (ML) models for churn prediction has focused on sectors like telecommunications, while this problem can be particularly challenging in industries with High Customer Turnover (HCT) like food delivery, e-commerce,...

Customer loyalty is a crucial factor for retail business success. This paper illustrates an AI approach, named CENTAURO, to learn customer loyalty prediction models that may help retailers to run powerful loyalty programs and take better ...

Context: The technology of machine learning and data science is gradually evolving and improving. In this process, we feel the importance of data science to solve a problem. Objective: In this article our main objective is to predict the customer ...

A key toward intelligent decision-making in industries lies in the ability to process and analyze vast quantities of business data. Concept drift and class imbalance are co-existing problems in real-life data sets, and the telecommunication sector ...

Telecommunication industry is one of the major sectors which is at higher risk of losing revenue due to customer churn. Thus, when churn management is done effectively, it provides a competitive advantage to the telecom company over its ...

Mobile number portability (MNP) across telecommunication networks entails the movement of a customer from one mobile service provider to another. This, often, is as a result of seeking better service delivery or personal choice. Churning prediction ...

In subscription-based businesses, the churn rate refers to the percentage of customers who discontinue their subscriptions within a given time period. Particularly, in the mobile games industry, the churn rate is often pronounced due to the high ...

In a rapidly growing industry like telecommunications, customer churn prediction is a crucial challenge affecting the sustainability of the business as a whole. The fact that retaining a customer is more profitable than acquiring new customers is ...

Several machine learning models have been proposed to address customer churn problems. In this work, the authors used a novel method by applying deep convolutional neural networks on a labeled dataset of 18,000 prepaid subscribers to classify/identify ...

Accurate customer churn classification is vital in any business organisation due to the higher cost involved in getting new customers. In telecommunication businesses, companies have used various types of single classifiers to classify customer churn, ...

As Location-Based Social Networks (LBSNs) have become widely used by users, understanding user engagement and predicting user churn are essential to the maintainability of the services. In this work, we conduct a quantitative analysis to understand user ...

Churn prediction is a major focus that all the companies need to concern. Many studies have shown that class imbalance has a significant impact on churn prediction, but there is still no consensus on which technique is the best to cope with this issue. ...

The advent of price and product comparison sites now makes it even more important to retain customers and identify those that might be at risk of leaving. The use of data mining methods has been widely advocated for predicting customer churn. This paper ...

The customer churn is a crucial activity in the competitive and rapidly growing telecommunication industry. Due to the high cost of acquiring a new customer, customer churn prediction is one of the greatest importance for project managers. It is ...

200 words for Intelligent Data Systems The class imbalance problem is a relatively new challenge that has attracted growing attention from both industry and academia, since it strongly affects classification performance. Research also established that ...

Customer churn prediction is becoming an increasingly important business analytics problem for telecom operators. In order to increase the efficiency of customer retention campaigns, churn prediction models need to be accurate as well as compact and ...