Application of data mining techniques in the on‐line travel industry

Pongsak Hoontrakul (Department of Marketing, Sasin of Chulalongkorn University, Bangkok, Thailand)
Sunil Sahadev (School of Management, University of Sheffield, Sheffield, UK)

Marketing Intelligence & Planning

ISSN: 0263-4503

Publication date: 8 February 2008



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


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.


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.


The paper, focusing on Thailand, presents an application of data mining techniques in the on‐line travel industry.



Hoontrakul, P. and Sahadev, S. (2008), "Application of data mining techniques in the on‐line travel industry", Marketing Intelligence & Planning, Vol. 26 No. 1, pp. 60-76.

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Copyright © 2008, Emerald Group Publishing Limited

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