以電力客戶行為數(shù)據(jù)挖掘為基礎(chǔ)的營銷策略研究
發(fā)布時間：2018-11-20 17:53
【摘要】：“十三五”是我國全面深化改革的關(guān)鍵時期,面對改革新形式,電網(wǎng)企業(yè)應(yīng)打破固有的壟斷思維、著眼于未來,更加注重發(fā)展客戶服務(wù)質(zhì)量和效益、更加注重量化管理與精益管理、更加注重以市場為導(dǎo)向、以客戶為中心,工作開展要始于客戶需求、終于客戶滿意,變被動服務(wù)為主動服務(wù)、變粗放服務(wù)為精準(zhǔn)服務(wù),圍繞客戶的特質(zhì)和要求,推行價值營銷,更好地為客戶創(chuàng)造價值、讓渡價值。本文首先對目前國內(nèi)電力行業(yè)在客戶行為方面的數(shù)據(jù)挖掘和營銷策略制定現(xiàn)狀進(jìn)行了研究,對傳統(tǒng)營銷策略的不足進(jìn)行了分析,提出數(shù)據(jù)挖掘?qū)τ谛滦蝿菹麻_展較為精準(zhǔn)的營銷策略制定的優(yōu)勢。然后對客戶行為的基本概念、全壽命周期的客戶行為理論,以及影響客戶行為的主要因素和客戶決策的過程進(jìn)行了研究。本文確定了客戶行為分析的五個方面。從客戶行為的五個方面選取了主要的、典型的行為作為分析對象。第一方面為客戶正常用電的行為,選取了增量用電和縮量用電兩個方向,進(jìn)行相應(yīng)的關(guān)聯(lián)分析;第二個方面為客戶非正常用電行為,主要為違約用電和竊電兩種類型,通過聚類尋找不同客戶間的行為共通點和差異點;第三個方面為客戶繳費行為的數(shù)據(jù)挖掘,對客戶繳費方式上的選擇和繳費時間上的規(guī)律進(jìn)行挖掘和聚類;第四個方面為客戶欠費行為的研究,針對欠費客戶的欠費趨勢、行業(yè)分布和繳費方式進(jìn)行數(shù)據(jù)挖掘;第五方面,研究的是為客戶訴求中重要的訴求——投訴,對客戶投訴的類型構(gòu)成、地區(qū)分布和投訴時間規(guī)律進(jìn)行挖掘,并對投訴進(jìn)行聚類分析和預(yù)測。在對五個部分的客戶行為的開展數(shù)據(jù)挖掘的基礎(chǔ)上,針對各部分客戶行為所反映的現(xiàn)象,提出了相應(yīng)的營銷策略。以數(shù)據(jù)挖掘的為基礎(chǔ)的客戶行為分析更加量化、客觀、真實,以數(shù)據(jù)說話,讓電網(wǎng)企業(yè)制定營銷策略更加科學(xué)、有效,同樣對于其他行業(yè)也有較為積極的借鑒意義。
[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.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP311.13;F426.61;F274
本文編號：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.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP311.13;F426.61;F274
【引證文獻(xiàn)】
相關(guān)期刊論文 前1條
1 楊凜;李巍;李俊杰;廖謙;張葉貴;;基于數(shù)據(jù)挖掘的電力負(fù)荷預(yù)測[J];自動化與儀器儀表;2018年03期
，本文編號：2345577
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