An intelligent system for customer targeting: a data mining approach
Decision Support Systems
Expert Systems with Applications: An International Journal
Customer segmentation based on neural network with clustering technique
AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Expert Systems with Applications: An International Journal
Marketing Segmentation Through Machine Learning Models
Social Science Computer Review
Feature Selection in Marketing Applications
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Machine learning and genetic algorithms in pharmaceutical development and manufacturing processes
Decision Support Systems
Optimal ensemble construction via meta-evolutionary ensembles
Expert Systems with Applications: An International Journal
Application of data mining techniques for customer lifetime value parameters: a review
International Journal of Business Information Systems
Tuning metaheuristics: A data mining based approach for particle swarm optimization
Expert Systems with Applications: An International Journal
Using the Taguchi method for effective market segmentation
Expert Systems with Applications: An International Journal
Improved response modeling based on clustering, under-sampling, and ensemble
Expert Systems with Applications: An International Journal
Ensemble learning for customers targeting
KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
Traditional and IS-Enabled Customer Acquisition on the Internet
Management Science
Expert Systems with Applications: An International Journal
Churn management optimization with controllable marketing variables and associated management costs
Expert Systems with Applications: An International Journal
Audience targeting by B-to-B advertisement classification: A neural network approach
Expert Systems with Applications: An International Journal
Review: Soft computing applications in customer segmentation: State-of-art review and critique
Expert Systems with Applications: An International Journal
Direct mailing decisions based on the worst and best practice cross-efficiency evaluations
International Journal of Business Information Systems
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One of the key problems in database marketing is the identification and profiling of households that are most likely to be interested in a particular product or service. Principal component analysis (PCA) of customer background information followed by logistic regression analysis of response behavior is commonly used by database marketers. In this paper, we propose a new approach that uses artificial neural networks (ANNs) guided by genetic algorithms (GAs) to target households. We show that the resulting selection rule is more accurate and more parsimonious than the PCA/logit rule when the manager has a clear decision criterion. Under vague decision criteria, the new procedure loses its advantage in interpretability, but is still more accurate than PCA/logit in targeting households.