Abstract
In the era of Big Data, enterprise marketing focuses on customers instead of product center, and customer relationship management has become the core issue. In the aviation field, how to tap the high-quality customer base is more important. How to classify customers according to the characteristics of air passengers, and then make personalized marketing strategies for them, is the key problem to be solved. Aiming at optimizing resource allocation, with the help of aviation big data, a customer value analysis method is proposed based on the LRFMC model. First, Python was applied to clean, reduce and transform the data on the big data platform, and then to classify them. Moreover, characteristics of different customer categories were analyzed, and the customer value was evaluated. Finally, optimization methods based on K-Means algorithm were proposed, and the data were visualized, so that personalized services can be developed for different customers.
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Acknowledgment
The project is provided with technical training guidance by China Soft International Education Technology Group. This paper is supported by the Ph.D. Research Initiation Fund of Nanchang Institute of Science and Technology with the Project (No. NGRCZX-18-01).
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Tao, Y. (2020). Analysis Method for Customer Value of Aviation Big Data Based on LRFMC Model. In: Zeng, J., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2020. Communications in Computer and Information Science, vol 1257. Springer, Singapore. https://doi.org/10.1007/978-981-15-7981-3_7
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DOI: https://doi.org/10.1007/978-981-15-7981-3_7
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