电子商务视角下基于车联网数据的车险客户画像构建与营销创新研究

Research on Auto Insurance Customer Profile Construction and Marketing Innovation Based on Telematics Data under the Perspective of E-Commerce

随着互联网和人工智能的发展,车联网技术在车险的发展中逐渐发挥着重要作用。传统车险的费率厘定和客户画像分析往往仅考虑年龄、性别、出险情况等因素,对于驾驶行为考虑有所欠缺。基于此,本文首先梳理了车联网车险发展现状,以及客户画像常用的技术手段,为本文的技术分析提供理论支撑。其次,为了解决传统车险客户画像由于信息不足导致客户细分能力有限的问题,本文基于车联网获取的驾驶行为数据,运用K-means聚类算法对客户进行分类,对不同的客户群体提出车险费率厘定和风险管理的建议。通过基于车联网的客户画像分析,可以为不同的客户提供不同的车险产品。既能满足客户的需求,提升客户黏性,也能满足保险公司对于风险控制的要求。对社会而言,车联网的监测功能可以规范驾驶行为,减少城市道路的交通风险,并对生态环境产生积极影响,助力把中国打造成全球领先的智慧交通创新示范。With the development of the Internet and artificial intelligence, the Internet of vehicles technology has gradually played an important role in the development of auto insurance. The rate determination and customer portrait analysis of traditional auto insurance often only consider factors such as age, gender, and accident situation, and lack consideration of driving behavior. Based on this, this paper firstly sorts out the development status of car network car insurance, as well as the technical means commonly used in customer portraits, to provide theoretical support for the technical analysis of this paper. Secondly, in order to solve the problem of limited customer segmentation ability due to insufficient information in traditional auto insurance customer portraits, this paper uses the K-means clustering algorithm to classify customers based on the driving behavior data obtained from the Internet of vehicles, and propose auto insurance fees for different customer groups. Through the analysis of customer portraits based on the Internet of vehicles, different auto insurance products can be provided for different customers. It can not only meet the needs of customers, improve customer stickiness, but also meet the requirements of insurance companies for risk control. For society, the monitoring functions of telematics can regulate driving behaviour, reduce traffic risks on urban roads and have a positive impact on the ecosystem, helping to make China a leading global demonstration of intelligent transport innovation.