Sales managers are unlikely to reap the benefits of implementing predictive analytics
applications when salespeople show aversion to or lack understanding of these …

Due to market deregulation and globalisation, competitive environments in various sectors
continuously evolve, leading to increased customer churn. Effectively anticipating and …

Given the pervasive ubiquity of data, sales practice is moving rapidly into an era of predictive
analytics, using quantitative methods, including machine learning algorithms, to reveal …

In this paper, we study the staying power of various churn prediction models. Staying power
is defined as the predictive performance of a model in a number of periods after the …

The key question of this study is: How long should customer event history be for customer
churn prediction? While most studies in predictive churn modeling aim to improve models by …

This article provides a descriptive analysis of how methodological factors contribute to the
accuracy of customer churn predictive models. The study is based on a tournament in which …

Understanding consumer churn is pivotal for companies in the USA to develop efficient
strategies for consumer retention and reduce its negative effects on revenue and profitability …

We studied the problem of optimizing the performance of a DSS for churn prediction. In
particular, we investigated the beneficial effect of adding the voice of customers through call …

For customer-centric firms, churn prediction plays a central role in churn management
programs. Methodological advances have emphasized the use of customer panel data to …

This paper presents a systematic review of marketing research on the burgeoning new area
of “marketing analytics” and considers the importance of marketing analytics for marketing …