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Combining visual customer segmentation and response modeling

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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.

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Acknowledgments

The financial support of the Academy of Finland (Grant Nos. 127656 and 127592) and the Foundation of Economic Education is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Information Technologies, Åbo Akademi University, Joukahaisenkatu 3–5, 20520, Turku, Finland

    Zhiyuan Yao, Peter Sarlin, Tomas Eklund & Barbro Back

Authors
  1. Zhiyuan Yao
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  2. Peter Sarlin
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  3. Tomas Eklund
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  4. Barbro Back
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Corresponding author

Correspondence to Zhiyuan Yao.

Appendix

Appendix

See Table 3.

Table 3 The summary statistics of the demographic variables
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Yao, Z., Sarlin, P., Eklund, T. et al. Combining visual customer segmentation and response modeling. Neural Comput & Applic 25, 123–134 (2014). https://doi.org/10.1007/s00521-013-1454-3

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