基于改進(jìn)RFM模型的聚類算法在農(nóng)村用戶4G消費(fèi)行為中研究與應(yīng)用
發(fā)布時(shí)間:2018-05-19 16:40
本文選題:客戶消費(fèi)行為 + RFM模型; 參考:《南京郵電大學(xué)》2017年碩士論文
【摘要】:4G(第四代通信技術(shù))通信時(shí)代,三家電信運(yùn)營(yíng)商(移動(dòng)、電信、聯(lián)通)的競(jìng)爭(zhēng)日益激烈,南通如皋地區(qū)的城區(qū)通信市場(chǎng)已逐步趨于飽和,縣城區(qū)域4G用戶已達(dá)到高水位,已很難有更大的突破,而17個(gè)農(nóng)村鄉(xiāng)鎮(zhèn)是一個(gè)函待開(kāi)發(fā)的藍(lán)海,4G普及率低、客戶多,具有巨大的新增客戶挖掘空間。如何有效的開(kāi)展4G營(yíng)銷,實(shí)現(xiàn)保存量促新增,擴(kuò)大如皋的移動(dòng)市場(chǎng)份額,是如皋移動(dòng)公司急需解決的問(wèn)題。而要提升移動(dòng)市場(chǎng)份額,如皋移動(dòng)應(yīng)加大農(nóng)村市場(chǎng)的拓展力度,通過(guò)強(qiáng)有力的營(yíng)銷手段提升市場(chǎng)占有率,擴(kuò)大規(guī)模效應(yīng),從而搶占這一潛在市場(chǎng)!RFM模型是衡量客戶能否給企業(yè)帶來(lái)創(chuàng)收的重要工具,R表示最近一次購(gòu)買行為,F表示購(gòu)買頻次,M則表示購(gòu)買金額,但是該模型不太適用于電信行業(yè)(因?yàn)橛脩魩缀鯐r(shí)時(shí)刻刻在消費(fèi),消費(fèi)頻次也高)。本文針對(duì)RFM模型在電信行業(yè)應(yīng)用中的不足之處,研究了通信用戶的消費(fèi)行為,提出了基于改進(jìn)RFM模型的ATM移動(dòng)通信客戶消費(fèi)行為模型(A表示用戶的個(gè)人屬性,例如性別、網(wǎng)齡、是否家庭成員等,T表示用戶的終端屬性,如機(jī)齡、終端價(jià)格等,M表示用戶的消費(fèi)屬性,如月消費(fèi)金額、流量使用數(shù)等)。通過(guò)實(shí)際應(yīng)用,證明了ATM模型是對(duì)通信企業(yè)客戶進(jìn)行數(shù)據(jù)分析的有效方法。本文的研究成果可作為輔助如皋移動(dòng)提升農(nóng)村移動(dòng)用戶4G覆蓋率的科學(xué)依據(jù)。
[Abstract]:In the era of 4G (fourth generation communication technology) communication, the competition among the three telecom operators (mobile, telecom, and Unicom) is becoming increasingly fierce. The communication market in the urban area of Rugao area of Nantong has gradually become saturated, and 4G users in the county area have reached a high water level. It is difficult to make a bigger breakthrough, and 17 rural villages and towns are a letter to be developed in the blue sea 4G penetration rate is low, the number of customers, with a huge new customers mining space. How to effectively carry out 4G marketing, save quantity to promote the increase, expand Rugao mobile market share, is Rugao mobile company urgently need to solve the problem. In order to increase mobile market share, Rugao Mobile should expand the rural market, increase its market share through powerful marketing means, and expand its scale effect. Thus, the RFM model is an important tool to measure whether customers can bring income to the enterprise. The most recent purchase behavior is indicated by the purchase frequency. M means the purchase amount. But this model is not very suitable for the telecom industry (because users spend almost all the time, consumption frequency is also high. Aiming at the deficiency of RFM model in telecommunication industry, this paper studies the consumer behavior of communication users, and puts forward the ATM mobile communication customer consumption behavior model based on improved RFM model, which represents the personal attributes of users, such as gender, network age, etc. Whether or not family members indicate the terminal attributes of the user, such as machine age, terminal price and so on, means the consumption attribute of the user, such as the monthly consumption amount, the amount of traffic usage and so on. Through practical application, it is proved that ATM model is an effective method for data analysis of communication enterprise customers. The research results of this paper can be used as a scientific basis to assist Rugao mobile to promote 4G coverage of rural mobile users.
【學(xué)位授予單位】:南京郵電大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TP311.13;TN929.5
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 孫章才;車勇波;姚莉;白彪;吳秋玫;;基于改進(jìn)K-means算法在電網(wǎng)企業(yè)網(wǎng)絡(luò)入侵檢測(cè)中的應(yīng)用[J];信息通信;2016年09期
2 彭碩;郭晨;周松;王博;;基于改進(jìn)凝聚層次聚類算法的生態(tài)環(huán)境監(jiān)測(cè)采樣點(diǎn)優(yōu)選技術(shù)研究[J];井岡山大學(xué)學(xué)報(bào)(自然科學(xué)版);2014年06期
3 張靖;段富;;優(yōu)化初始聚類中心的改進(jìn)k-means算法[J];計(jì)算機(jī)工程與設(shè)計(jì);2013年05期
4 王越;王泉;呂奇峰;曾晶;;基于初始聚類中心優(yōu)化和維間加權(quán)的改進(jìn)K-means算法[J];重慶理工大學(xué)學(xué)報(bào)(自然科學(xué));2013年04期
5 余敦輝;何克清;李兵;;基于模型聚類算法的領(lǐng)域問(wèn)題本體構(gòu)建[J];小型微型計(jì)算機(jī)系統(tǒng);2013年01期
6 劉懷愚;朱昌杰;李t,
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