Cluster Analysis Method of Aviation Customer Value Based on Optimized LRFMC Model
Conference: ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application
12/17/2021 - 12/19/2021 at Shenyang, China
Proceedings: ICMLCA 2021
Pages: 5Language: englishTyp: PDF
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Authors:
Wang, Hong; Huang, Siming (School of Information Science and Engineering, Shenyang Ligong University, Shenyang, Liaoning, China)
Abstract:
This article designs and implements an aviation customer value clustering analysis process based on LRFMC model. This customer value analysis use Python and related database to perform data cleaning, feature extraction, clustering, weight comparison and other operations on customer data. The LRFMC model is constructed as the model of aviation customer value analysis, On this basis use k-means clustering algorithm to classify customers and conduct feature research for the purpose of value analysis. Classification results show that this scheme has certain reference value in solving the problem of customer value analysis and further developing the corresponding marketing strategy.