以电力客户行为数据挖掘为基础的营销策略研究
发布时间：2018-11-20 17:53
【摘要】：“十三五”是我国全面深化改革的关键时期,面对改革新形式,电网企业应打破固有的垄断思维、着眼于未来,更加注重发展客户服务质量和效益、更加注重量化管理与精益管理、更加注重以市场为导向、以客户为中心,工作开展要始于客户需求、终于客户满意,变被动服务为主动服务、变粗放服务为精准服务,围绕客户的特质和要求,推行价值营销,更好地为客户创造价值、让渡价值。本文首先对目前国内电力行业在客户行为方面的数据挖掘和营销策略制定现状进行了研究,对传统营销策略的不足进行了分析,提出数据挖掘对于新形势下开展较为精准的营销策略制定的优势。然后对客户行为的基本概念、全寿命周期的客户行为理论,以及影响客户行为的主要因素和客户决策的过程进行了研究。本文确定了客户行为分析的五个方面。从客户行为的五个方面选取了主要的、典型的行为作为分析对象。第一方面为客户正常用电的行为,选取了增量用电和缩量用电两个方向,进行相应的关联分析;第二个方面为客户非正常用电行为,主要为违约用电和窃电两种类型,通过聚类寻找不同客户间的行为共通点和差异点;第三个方面为客户缴费行为的数据挖掘,对客户缴费方式上的选择和缴费时间上的规律进行挖掘和聚类;第四个方面为客户欠费行为的研究,针对欠费客户的欠费趋势、行业分布和缴费方式进行数据挖掘;第五方面,研究的是为客户诉求中重要的诉求——投诉,对客户投诉的类型构成、地区分布和投诉时间规律进行挖掘,并对投诉进行聚类分析和预测。在对五个部分的客户行为的开展数据挖掘的基础上,针对各部分客户行为所反映的现象,提出了相应的营销策略。以数据挖掘的为基础的客户行为分析更加量化、客观、真实,以数据说话,让电网企业制定营销策略更加科学、有效,同样对于其他行业也有较为积极的借鉴意义。
[Abstract]:The 13th Five-Year Plan is a key period for our country to comprehensively deepen its reform. In the face of the new form of reform, power grid enterprises should break the inherent monopoly thinking, focus on the future, and pay more attention to the development of customer service quality and efficiency. Pay more attention to quantitative management and lean management, pay more attention to market-oriented, customer-centered, work development must begin with customer demand, finally customer satisfaction, change passive service into active service, change extensive service into precision service, Focus on the characteristics and requirements of customers, promote value marketing, better create value for customers, transfer value. Firstly, this paper studies the current situation of data mining and marketing strategy formulation in domestic electric power industry, and analyzes the shortcomings of traditional marketing strategy. The advantage of data mining for developing accurate marketing strategy in the new situation is put forward. Then, the basic concept of customer behavior, the theory of customer behavior in the whole life cycle, the main factors affecting customer behavior and the process of customer decision-making are studied. This paper identifies five aspects of customer behavior analysis. The main and typical behaviors are selected from five aspects of customer behavior. On the one hand, for the behavior of customer's normal power consumption, the author chooses the incremental power consumption and the condensed power consumption to carry on the corresponding correlation analysis; The second part is the abnormal electricity consumption behavior of customers, mainly two types of electricity breach and electricity theft, through clustering to find common points and differences between different customers; The third aspect is the data mining of customer payment behavior, mining and clustering the choice of customer payment mode and the rule of payment time; The fourth aspect is the research on the behavior of the customer in arrears, aiming at the trend of the overdue fee, the distribution of the industry and the way of payment. In the fifth aspect, the author studies the important appeal of customer-complaint, excavates the type constitution, regional distribution and time rule of customer complaint, and makes cluster analysis and prediction of complaint. Based on the data mining of customer behavior in five parts, this paper puts forward the corresponding marketing strategy in view of the phenomenon reflected by customer behavior in each part. The customer behavior analysis based on data mining is more quantitative, objective, real, and data speaking, which makes the marketing strategy of power grid enterprises more scientific and effective, and also has a more positive reference significance for other industries.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.13;F426.61;F274
本文编号：2345577
[Abstract]:The 13th Five-Year Plan is a key period for our country to comprehensively deepen its reform. In the face of the new form of reform, power grid enterprises should break the inherent monopoly thinking, focus on the future, and pay more attention to the development of customer service quality and efficiency. Pay more attention to quantitative management and lean management, pay more attention to market-oriented, customer-centered, work development must begin with customer demand, finally customer satisfaction, change passive service into active service, change extensive service into precision service, Focus on the characteristics and requirements of customers, promote value marketing, better create value for customers, transfer value. Firstly, this paper studies the current situation of data mining and marketing strategy formulation in domestic electric power industry, and analyzes the shortcomings of traditional marketing strategy. The advantage of data mining for developing accurate marketing strategy in the new situation is put forward. Then, the basic concept of customer behavior, the theory of customer behavior in the whole life cycle, the main factors affecting customer behavior and the process of customer decision-making are studied. This paper identifies five aspects of customer behavior analysis. The main and typical behaviors are selected from five aspects of customer behavior. On the one hand, for the behavior of customer's normal power consumption, the author chooses the incremental power consumption and the condensed power consumption to carry on the corresponding correlation analysis; The second part is the abnormal electricity consumption behavior of customers, mainly two types of electricity breach and electricity theft, through clustering to find common points and differences between different customers; The third aspect is the data mining of customer payment behavior, mining and clustering the choice of customer payment mode and the rule of payment time; The fourth aspect is the research on the behavior of the customer in arrears, aiming at the trend of the overdue fee, the distribution of the industry and the way of payment. In the fifth aspect, the author studies the important appeal of customer-complaint, excavates the type constitution, regional distribution and time rule of customer complaint, and makes cluster analysis and prediction of complaint. Based on the data mining of customer behavior in five parts, this paper puts forward the corresponding marketing strategy in view of the phenomenon reflected by customer behavior in each part. The customer behavior analysis based on data mining is more quantitative, objective, real, and data speaking, which makes the marketing strategy of power grid enterprises more scientific and effective, and also has a more positive reference significance for other industries.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.13;F426.61;F274
【引证文献】
相关期刊论文 前1条
1 杨凛;李巍;李俊杰;廖谦;张叶贵;;基于数据挖掘的电力负荷预测[J];自动化与仪器仪表;2018年03期
，本文编号：2345577
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