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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 1/2014

01.07.2014 | Original Article

Combining visual customer segmentation and response modeling

verfasst von: Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back

Erschienen in: Neural Computing and Applications | Ausgabe 1/2014

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Abstract

Customer relationship management is a central part of Business Intelligence, and sales campaigns are often used for improving customer relationships. This paper uses advanced analytics to explore customer behavior during sales campaigns. We provide a visual, data-driven and efficient framework for customer-segmentation and campaign-response modeling. First, the customers are grouped by purchasing behavior characteristics using a self-organizing map. To this behavioral segmentation model, we link segment-migration patterns using feature plane representations. This enables visual monitoring of the customer base and tracking customer behavior before and during sales campaigns. In addition to the general segment-migration patterns, this method provides the capability to drill down into each segment to visually explore the dynamics. The framework is applied to a department store chain with more than 1 million customers.
Vorheriger Artikel A novel approach for estimating heat transfer coefficients of ethylene glycol–water mixtures
Nächster Artikel Adaptive neural control using reinforcement learning for a class of robot manipulator

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Metadaten
Titel
Combining visual customer segmentation and response modeling
verfasst von
Zhiyuan Yao
Peter Sarlin
Tomas Eklund
Barbro Back
Publikationsdatum
01.07.2014
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 1/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-013-1454-3

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