Application of data mining techniques in customer relationship management: A literature review and classification
Despite the importance of data mining techniques to customer relationship management
(CRM), there is a lack of a comprehensive literature review and a classification scheme for it …
(CRM), there is a lack of a comprehensive literature review and a classification scheme for it …
Forecasting and operational research: a review
From its foundation, operational research (OR) has made many substantial contributions to
practical forecasting in organizations. Equally, researchers in other disciplines have …
practical forecasting in organizations. Equally, researchers in other disciplines have …
Creating enduring customer value
One of the most important tasks in marketing is to create and communicate value to
customers to drive their satisfaction, loyalty, and profitability. In this study, the authors …
customers to drive their satisfaction, loyalty, and profitability. In this study, the authors …
Time-to-event prediction with neural networks and Cox regression
New methods for time-to-event prediction are proposed by extending the Cox proportional
hazards model with neural networks. Building on methodology from nested case-control …
hazards model with neural networks. Building on methodology from nested case-control …
[PDF][PDF] Evaluation measures for models assessment over imbalanced data sets
M Bekkar, HK Djemaa, TA Alitouche - J Inf Eng Appl, 2013 - eva.fing.edu.uy
Imbalanced data learning is one of the challenging problems in data mining; among this
matter, founding the right model assessment measures is almost a primary research issue …
matter, founding the right model assessment measures is almost a primary research issue …
Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction
Customer retention campaigns increasingly rely on predictive analytics to identify potential
churners in a customer base. Traditionally, customer churn prediction was dependent on …
churners in a customer base. Traditionally, customer churn prediction was dependent on …
New insights into churn prediction in the telecommunication sector: A profit driven data mining approach
Customer churn prediction models aim to indicate the customers with the highest propensity
to attrite, allowing to improve the efficiency of customer retention campaigns and to reduce …
to attrite, allowing to improve the efficiency of customer retention campaigns and to reduce …
Comparing oversampling techniques to handle the class imbalance problem: A customer churn prediction case study
Customer retention is a major issue for various service-based organizations particularly
telecom industry, wherein predictive models for observing the behavior of customers are one …
telecom industry, wherein predictive models for observing the behavior of customers are one …
Profit-driven weighted classifier with interpretable ability for customer churn prediction
Customer churn prediction methods aim to identify customers with the highest probability of
attrition, improve the effectiveness of customer retention campaigns, and maximize profits …
attrition, improve the effectiveness of customer retention campaigns, and maximize profits …
[BOOK][B] Why database marketing?
A basic yet crucial question is: why should the firm engage in database marketing? We
discuss three fundamental motivations: enhancing marketing productivity, creating and …
discuss three fundamental motivations: enhancing marketing productivity, creating and …