Customer is the heart and soul of any organization. The era of globalization and cut throat competition has changed the basic concept of marketing, now marketing is not confined to selling the products to the customers, but the objective is to reach to the hearts of the customers so that they feel belongingness towards the organizations and hence should remain the loyal customers. In the dynami...

The key question of this study is: How long should the length of customer event history be for customer churn prediction? While most studies in predictive churn modeling aim to improve models by data augmentation or algorithm improvement, this study focuses on a another dimension: time window optimization with respect to predictive performance. This paper first presents a formalization of the t...

For brands, gaining new customer is more expensive than keeping an existing one. Therefore, the ability to keep customers in a brand is becoming more challenging these days. Churn happens when a customer leaves a brand to another competitor. Most of the previous work considers the problem of churn prediction using CDRs. In this paper, we use micro-posts to classify customers into churny or nonc...

The digital world is very dynamic. ability to timely identify possible vendor migration trends or customer loss risks important in cloud-based services. This work describes a churn risk prediction system and how it can be applied guide cloud service providers for recommending adjustments the subscription level, both promote rational resource consumption avoid CSP loss. A training dataset was bu...

We study unlimited infinite churn in peer-to-peer overlay networks. Under this churn, arbitrary many peers may concurrently request to join or leave the overlay network; moreover these requests may never stop coming. We prove that unlimited adversarial churn, where processes may just exit the overlay network, is unsolvable. We focus on cooperative churn where exiting processes participate in th...

Customer churn is a problem virtually all companies face, and the ability to predict it reliably can be cornerstone for successful retention campaigns. In this study, we propose an approach customer prediction in non-contractual B2B settings that relies exclusively on invoice-level data feature engineering uses multi-slicing maximally utilize available data. We cast as binary classification ass...