某酒类电商精准营销系统的设计与实现

发布时间：2018-10-12 16:01

【摘要】：随着信息技术的快速发展和广泛应用,电子商务、网上购物、在线交易等已经成为消费者现实生活中不可或缺的一部分。因此酒类电商也应运而生,猛烈地冲击着传统的酒类营销模式,精准营销作为电商营销的新趋势,伴随着数据仓库、数据挖掘算法等新技术的发展,以及清晰的客户定位和精准的商品推荐等广泛的商业应用,能为企业实现更好的效益。本文的精准营销系统针对该电商的营销现状,从电商的营销需求分析入手,分析其目前在营销过程中所遇到的主要问题,针对其导入流量利用效率低的问题,提出了精准营销系统的设计方案。系统采用B/S架构,SSM三层框架,开发平台为J2EE,页面使用JSP和jQuery技术,以及数据仓库等技术。系统通过对消费者的消费数据进行分析,通过使用K-means聚类分析进行精准的客户定位,对客户进行分类和使用Apriori算法对商品的关联规则找出强关联规则,进行精准营销,实现降低营销成本,提高消费者的购物体验的目标。经过验证,采用Apriori算法能够有效的挖掘出潜藏在商品中有价值的关联规则。采用k-means聚类分析有效地将用户群进行聚类分类,系统开发完成后,通过实际测试效果非常理想。本文的数据挖掘系统采用SSM三层框架,有利于后期对系统的维护和功能的扩展。同时,也可为其他电商的精准营销策略提供一定的借鉴,创造更大的商业价值和社会价值。
[Abstract]:With the rapid development and wide application of information technology, e-commerce, online shopping and online trading have become an indispensable part of consumers' real life. Therefore, the ecommerce of alcohol comes into being, which impinges on the traditional liquor marketing mode. Precision marketing, as a new trend of e-commerce marketing, is accompanied by the development of new technologies such as data warehouse, data mining algorithm, etc. As well as clear customer positioning and accurate commodity recommendation, such as a wide range of commercial applications, for enterprises to achieve better benefits. The precision marketing system of this paper aims at the current marketing situation of the e-commerce company, starting with the analysis of the marketing demand of the e-commerce company, analyzing the main problems encountered in the marketing process, and aiming at the problem of low efficiency in the utilization of the import flow. The design scheme of precision marketing system is put forward. The system adopts B / S architecture, SSM three-tier framework, J2EE development platform, JSP and jQuery technology, data warehouse and so on. The system through the consumer consumption data analysis, through the use of K-means clustering analysis for accurate customer positioning, customer classification and use of Apriori algorithm to find strong association rules of commodities, accurate marketing. To achieve the goal of reducing marketing costs and improving consumer shopping experience. It is proved that the Apriori algorithm can effectively mine the valuable association rules hidden in commodities. The k-means clustering analysis is used to classify the user groups effectively. After the development of the system, the test results are very satisfactory. The data mining system in this paper adopts SSM three-tier framework, which is beneficial to the later maintenance and function expansion of the system. At the same time, it can also provide some reference for the precision marketing strategy of other e-commerce companies, and create greater commercial value and social value.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.52;TP311.13

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