Conditional market segmentation by neural networks

An artificial neural network (ANN) algorithm is proposed that incorporates both cluster and discriminant (or regression) analysis of the segments. The method simultaneously estimates the models relating consumer characteristics to market segments, i.e., subjects are assigned to (unique) segments so...

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Bibliographic Details
Published in:Proceedings of the Thirtieth Hawaii International Conference on System Sciences Vol. 5; pp. 455 - 464 vol.5
Main Author: Natter, M.
Format: Conference Proceeding
Language:English
Published: IEEE 1997
Subjects:
Aggregates
Algorithm design and analysis
Artificial neural networks
Backpropagation algorithms
Clustering algorithms
Industrial economics
Information processing
Monte Carlo methods
Neural networks
Psychology
ISBN:0818677430, 9780818677434
ISSN:1060-3425
Online Access:Get full text
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Summary:An artificial neural network (ANN) algorithm is proposed that incorporates both cluster and discriminant (or regression) analysis of the segments. The method simultaneously estimates the models relating consumer characteristics to market segments, i.e., subjects are assigned to (unique) segments so that subjects within a class show similar purchase behavior and share the same characteristics (psychographics/sociodemographics). Parameters of all models are estimated by the backpropagation algorithm. The performance of the ANN methodology is assessed in a Monte Carlo study. In contrast to the usual stepwise approach adopted in segmentation studies, our study found that simultaneous segmentation and discrimination are preferable for finding an overall optimum in that this way clusters are formed not only to create homogeneous submarkets but also to show a good discriminatory behaviour.
ISBN:0818677430
9780818677434
ISSN:1060-3425
DOI:10.1109/HICSS.1997.663205