Caiyue Wang
ABSTRACT
The competition among Chinese coastal ports is becoming increasingly fierce, but the means of low-price competition is not conducive to the healthy and sustainable development of ports. It is necessary to improve the level of customer relationship management and develop towards precision marketing, and customer value classification is an important basis for achieving precision marketing. This paper proposes a classification method of bulk port customer value based on improved RFM model. Firstly, based on the RFM model, the original indicator M is modified to the average transaction value V, and new indicators L the length of cooperation time and D the trend of order weight are introduced to construct the RFVLD model and define the customer value; then use the AHP to determine the weights of the RFVLD model indicators; finally, use the K-means algorithm to cluster customers and analyze the segmentation results, which provides a basis for accurate marketing of bulk port business.
- Dashan Jia. The Historic Transformation of Coastal Port Development (Part Two)[J]. China Ports, 2018(10): 1-7.Google Scholar
- Xumei Yuan, Xu Zhang. Research on PROMETHEE Multi-criteria Decision Method Based on Cloud Model[J]. Fuzzy Systems and Mathematics, 2018, 32(02): 92-103.Google Scholar
- Junyao Zhang. Research on Port Customer Classification and Business Decision System Based on Web Data[D]. Beijing Jiaotong University, 2017.Google Scholar
- Hughes A M. Strategic database marketing: the masterplan for starting and managing a profitable[J]. Custom-based marketing program, 1994: 127-132.Google Scholar
- PAULERABC G. Maximizing profit of a food retailing chain by targeting and promoting valuable customers using Loyalty Card and Scanner Data[J]. European Journal of Operational Research, 2006, 174(2): 1260-1280.Google ScholarCross Ref
- Arthur Middleton Hughes. Strategic Database Marketing: The Masterplan For Starting And Managing A Profitable, Custom-Based Marketing Program[M]. Second Edition. New York: McGraw-Hill, 2000: 105-136.Google Scholar
- Stone, Bob. Successful Direct Marketing Methods[M]. Lincolnwood: NTC Business Books, 1994.Google Scholar
- MIGLAUTSCH J R. Thoughts on RFM scoring[J]. Database Mark, 1995, 8(1): 143-170.Google Scholar
- Aiying Yin, Yunbing Wu, Minchen Zhu, Ying Zhang. Improved K-means algorithm based on MapReduce framework[J]. Application Research of Computers, 2018, 35(08): 2295-229.Google Scholar
- Kim G, Bae J. A novel approach to forecast promising technology through patent analysis[J]. Technological Forecasting and Social Change, 2017, 117: 228-237.Google ScholarCross Ref
Index Terms
- Customer Value Classification Method of Bulk Port Based on RFVLD
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