發(fā)布時間：2018-01-09 08:07

  本文關鍵詞：基于大數(shù)據(jù)技術的電信客戶維系挽的分析與研究　出處：《鄭州大學》2017年碩士論文　論文類型：學位論文

  更多相關文章： 電信 網(wǎng)絡爬蟲 大數(shù)據(jù) 客戶 維系挽留

【摘要】：進入21世紀,伴隨著電信市場的不斷開放,中國的電信市場取得了迅猛的發(fā)展,電信企業(yè)之間的競爭也日益加劇。為了爭奪客戶增加自身利潤,電信企業(yè)采取各種營銷手段推廣新業(yè)務和新套餐,但是,這又導致了運營成本的上升,增加了客戶的不穩(wěn)定性�？蛻舻牧魇б阎鸩匠蔀榱擞绊戨娦牌髽I(yè)效益的主要原因,同時在多方面嚴重危及著電信企業(yè)的健康發(fā)展,客戶的維系挽留已經(jīng)成為電信企業(yè)的重中之重。面對客戶對電信企業(yè)服務滿意度低和投訴率高的情況,弄清客戶投訴的根本原因和真正訴求,從事前防備和事中管控去避免和降低投訴,從而減少客戶離網(wǎng)現(xiàn)象的發(fā)生是很有必要的。本文主要針對電信企業(yè)客戶流失現(xiàn)象頻發(fā)的企業(yè)現(xiàn)狀,以國內主流社交媒體為主要研究對象,進行網(wǎng)絡爬蟲策略的研究與實現(xiàn)。通過獲取新浪微博上用戶發(fā)布的大量數(shù)據(jù),基于大數(shù)據(jù)技術對數(shù)據(jù)進行處理和分析,最后對電信客戶維系挽留提出可行性對策與建議。本文的主要研究工作與內容如下:1.對網(wǎng)絡爬蟲技術和大數(shù)據(jù)技術進行了學習與分析,基于Python語言在Linux平臺上以國內主流社交媒體新浪微博為研究對象,進行網(wǎng)絡爬蟲策略的研究與實現(xiàn),爬取新浪微博用戶發(fā)布的大量數(shù)據(jù)。2.為了進行數(shù)據(jù)的分析與研究,弄清客戶的真正訴求與投訴的根本原因,本文搭建了一套HADOOP分布式系統(tǒng)測試環(huán)境,存儲網(wǎng)絡爬蟲爬取的相關數(shù)據(jù)。另外,搭建和部署并行運算框架Spark,依托大數(shù)據(jù)技術對網(wǎng)絡爬蟲爬取的數(shù)據(jù)進行處理,方便下一步研究與分析。3.將Spark平臺處理分析的數(shù)據(jù)存入MONGODB中的Python Matplotlib繪圖庫對數(shù)據(jù)進行了多維度的可視化圖表分析,并依據(jù)分析結果針對電信企業(yè)客戶的維系挽留在多個領域有針對性的提出了可行性對策與建議。本文主要基于大數(shù)據(jù)技術和網(wǎng)絡爬蟲策略對電信客戶的維系挽留進行分析與研究,然后提出有針對性的改進對策,并在文章最后給出了本文研究內容的新的技術展望。
[Abstract]:In 21th century, with the continuous opening of the telecommunications market, China's telecommunications market has made rapid development, the competition between telecom enterprises is also increasingly intensified. In order to compete for customers to increase their own profits. Telecom companies adopt various marketing methods to promote new business and new packages, but this leads to the rise of operating costs. Increasing the instability of customers. The loss of customers has gradually become the main reason of affecting the efficiency of telecom enterprises, and seriously endangers the healthy development of telecom enterprises in many aspects. Customer retention has become the most important part of telecom enterprises. In the face of low customer satisfaction and high complaint rate, we can find out the root cause and real demand of customer complaints. It is necessary to avoid and reduce the complaints before taking precautions and controlling in the incident, so as to reduce the occurrence of the phenomenon of customer disconnection. This paper mainly aims at the current situation of the enterprises where the phenomenon of frequent customer churn occurs in telecom enterprises. Take the mainstream social media as the main research object, carry on the research and implementation of the web crawler strategy. Through obtaining a large number of data released by users on Sina Weibo, processing and analysis of the data based on big data technology. Finally, the paper puts forward the feasible countermeasures and suggestions for the telecom customer retention. The main research work and content of this paper are as follows: 1. Learn and analyze the network crawler technology and big data technology. Based on the Python language on the Linux platform, taking the domestic mainstream social media Sina Weibo as the research object, the research and implementation of the web crawler strategy are carried out. Crawl to Sina Weibo user released a large number of data. 2. In order to carry out data analysis and research, to understand the customer's real demands and complaints of the root cause. In this paper, we build a HADOOP distributed system test environment to store the crawler crawling data. In addition, build and deploy the parallel computing framework Spark. Based on big data technology, the data of crawler crawling are processed. Convenient for the next research and analysis .3.The Spark platform processing and analysis of data stored in the MONGODB Python. The Matplotlib drawing library carries on the multi-dimensional visualization chart analysis to the data. Based on the results of the analysis, this paper puts forward some feasible countermeasures and suggestions for the maintenance and retention of telecom customers in many fields. This paper mainly based on big data technology and network crawler strategy to retain telecom customers. Analysis and research. At last, the paper gives a new technical prospect of the research content.
【學位授予單位】：鄭州大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F626;F274;TP311.13

【參考文獻】

相關期刊論文 前8條

1 詹義;方媛;;基于Spark技術的網(wǎng)絡大數(shù)據(jù)分析平臺搭建與應用[J];互聯(lián)網(wǎng)天地;2016年02期

2 陳湘濤;張超;韓茜;;基于Hadoop的并行共享決策樹挖掘算法研究[J];計算機科學;2013年11期

3 劉師語;周淵平;杜江;;基于HADOOP分布式系統(tǒng)的數(shù)據(jù)處理分析[J];通信技術;2013年09期

4 蔣建洪;;主要分布式搜索引擎技術的研究[J];科學技術與工程;2007年10期

5 嚴浩仁;服務質量對移動電話顧客滿意度影響的實證研究[J];移動通信;2004年Z1期

6 龔益鳴,劉來發(fā);確定電信顧客滿意度及其關鍵因素的模型和方法[J];中國質量;2004年01期

7 胥學躍,傅德月,王惠敏;電信客戶投訴的營銷策略[J];通信與信息技術;2003年01期

8 王永貴;服務質量、顧客滿意與顧客價值的關系剖析——基于電信產(chǎn)業(yè)的整合框架[J];武漢理工大學學報(社會科學版);2002年06期

，

本文編號：1400613