Research on precision marketing strategy of hotel based on machine learning
XIONG Hao1， ZHAO Longsheng1， YAN Huili2， ZHAO Xiaolan1， JIA Chengrui1
（1. International Business School， Hainan University， Haikou 570228；2. International Tourism and Public Administration School， Hainan University， Haikou 570228）
Abstract：With the development of the Internet plus， big data of hotel order became increasingly abundant. Accurate marketing based on big data of hotel order become a popular trend. Based on the evaluation indicators of accurate marketing， a new machine learning method is proposed to predict the ordering behavior of hotel customers. According to the predict results， accurate marketing strategies are presented. First， the random forest method and support vector machine are combined to be a two-phase machine learning method， which is designed to forecasting the ordering action of customers for the purpose of accurate marketing. Then， coverage-hit rate and clustering analysis are used to further cluster the customers. And some accurate marketing strategies are proposed according to the customer categories. Finally， this article uses the hotel desensitization data of the Ctrip platform to conduct an empirical study. The results suggest that the RF-SVM two-stage prediction method outperform other basic prediction models in accuracy， ROC curve， discrimination and calibration error indicators.
熊浩,赵龙升,鄢慧丽,赵晓岚,贾承瑞. 基于机器学习的酒店客户精准营销策略研究[J]. 华中师范大学学报(自然科学版), 2025, 59(6): 843-854.
XIONG Hao,ZHAO Longsheng,YAN Huili,ZHAO Xiaolan,JIA Chengrui. Research on precision marketing strategy of hotel based on machine learning. journal1, 2025, 59(6): 843-854.
2025, Vol. 59 
