Unfolding large-scale marketing data

Ying Ho, Yuho Chung and Kin-nam Lau

International Journal of Research in Marketing, 2010, vol. 27, issue 2, 119-132

Abstract: Marketers use multidimensional unfolding to understand the relationship between customer preferences and product positioning through a joint display of customers and brands on a map. In today's information age, unfolding marketing data is challenging, as marketing data can be large in size and high-dimensional in nature. Moreover, the unfolding model is always subject to the curse of the degeneracy problem. We propose a new approach to unfold customer-by-brand transaction data and customer-by-customer network data in a reduced space. The proposed approach can recover the true configuration with reasonable accuracy, is scalable in terms of the number of estimated parameters, and can produce non-degenerate solution. We compare its performance with existing approaches by simulation experiments and real data analyses with interesting results.

Keywords: Information visualization; Multidimensional unfolding; Network data; Degenerate solution (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ijrema:v:27:y:2010:i:2:p:119-132

DOI: 10.1016/j.ijresmar.2009.12.009

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