基于聚类分析的航空公司客户群细分及营销策略

Airline Customer Group Segmentation and Marketing Strategy Based on Cluster Analysis

随着互联网行业的发展,为了提高航空公司经济效益,航空企业将营销策略调整为由产品过渡到客户需求为主,对客户细分是关键的一步。客户细分本意就是利用现有的各类交易数据进行数据分析和挖掘,找出客户在数据中的内在联系,从而提取特征客户对营销的偏好进行分类,进一步完善现有航空公司按照客户需要来定制个性化的营销策略。文中利用K-Means聚类算法工具,对某航空公司的数据建立了一个客户细分结构模型,并根据模型将航空客户准确、有效地划分成了三类,并建议某航空公司制定精准营销的市场定位体系、与特定顾客建立个性传播沟通体系、建立符合精准营销的销售组织体系并提供符合企业特色个性化的产品等,来提高航空公司经济效益。

With the development of the Internet industry,in order to improve the economic efficiency Airline companies have adjusted their marketing strategies from product tiansit to customer demand.This is a key step for customer segmentation.Customer segmentation is intended to utilize existing various types of transaction data for data analysis and mining to find out the potential links of customers in the data,so as to extract the characteristic customers marketing preferences,classification and further improve the existing marketing strategies of airlines to customize their individuality according to customer needs.This paper uses the K-Means clustering algorithm tool to establish a customer segmentation structure model with the data of a certain airline company,based on the model,the aviation customers are accurately and effectively divided into three categories.It is recommended that the airline develop precise market positioning system to establish a personalized communication system with specific customers,establish a sales organization system in line with precision marketing and provide personalized products in line with corporate characteristics,etc.,to improve the company s economic efficiency.