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Abstract:

Purpose – To describe the process of customer segmentation by data mining and expert judgment in a real-world setting.

Design/methodology/approach – Data collected in four case studies of on-line enquiries via one web-based intermediary and customer profiling were used as the input to K-means clustering calculations relating to four tourist destinations in Thailand, two already familiar internationally and two less so.

Findings – The case study illustrates the use of data mining techniques to unravel the basic pattern of customer enquiries across various attributes, as an input to actionable strategies.

Research limitations/implications – The methodology limits inferences to the single organization studied across the four destinations.

Practical implications – The findings suggest a practical planning strategy for customer segmentation in similar on-line situations. The methodology incorporates both qualitative and quantitative phases, and can be easily be applied in practice.

Originality/value – The paper, focusing on Thailand, presents an application of data mining techniques in the on-line travel industry.

Keywords:

Cluster analysis, Market segmentation, Thailand, Tourism, Travel

Article Type:

Research paper

Article URL:

http://www.emeraldinsight.com/10.1108/02634500810847156

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