Journal article
Customer Targeting: A Neural Network Approach Guided by Genetic Algorithms
Management science, Vol.51(2), pp.264-276
02/01/2005
DOI: 10.1287/mnsc.1040.0296
Abstract
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.
Details
- Title: Subtitle
- Customer Targeting: A Neural Network Approach Guided by Genetic Algorithms
- Creators
- YongSeog KimW. Nick StreetGary J. RussellFilippo Menczer
- Resource Type
- Journal article
- Publication Details
- Management science, Vol.51(2), pp.264-276
- Publisher
- Institute for Operations Research and the Management Sciences
- DOI
- 10.1287/mnsc.1040.0296
- ISSN
- 0025-1909
- eISSN
- 1526-5501
- Language
- English
- Date published
- 02/01/2005
- Academic Unit
- Bus Admin College; Marketing; Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984380523102771
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