Application of data mining techniques in the on‐line travel industry : A case study from Thailand

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.