Airline Customer Value Analysis Based on Entropy Weight Method and WKmeans Clustering Algorithm

Saixin Wu

Abstract: As the industry becomes more competitive, airlines are placing more emphasis on customer experience and personalized services for different customers in their marketing strategies. This requires us to make accurate customer segmentation so that we can target our limited resources to different types of customer groups to maximize the benefits. Since customer groups are not marked in advance, this problem is a typical unsupervised problem. In this paper, based on the traditional LRFMC customer analysis model, we propose a clustering analysis method combining entropy weight method and WKmeans algorithm to achieve customer classification, and finally give corresponding marketing strategies for different types of customers.

Keywords: LRFMC model, entropy weight method, WKmeans algorithm, data mining