大數(shù)據(jù)環(huán)境下精準(zhǔn)客戶(hù)定位的社交網(wǎng)絡(luò)分析
發(fā)布時(shí)間:2018-05-30 03:17
本文選題:社交網(wǎng)絡(luò)分析 + 精準(zhǔn)營(yíng)銷(xiāo)。 參考:《計(jì)算機(jī)工程與應(yīng)用》2017年15期
【摘要】:大數(shù)據(jù)為企業(yè)進(jìn)行精準(zhǔn)營(yíng)銷(xiāo)提供了重要支撐,精準(zhǔn)營(yíng)銷(xiāo)能提升營(yíng)銷(xiāo)效果,提高客戶(hù)滿(mǎn)意度,精準(zhǔn)營(yíng)銷(xiāo)的前提是客戶(hù)識(shí)別與選擇。通過(guò)分析網(wǎng)絡(luò)個(gè)體與群體特征,社交網(wǎng)絡(luò)分析能夠定位核心價(jià)值客戶(hù)。首先對(duì)社交網(wǎng)絡(luò)的中心性進(jìn)行分析,探討社交網(wǎng)絡(luò)節(jié)點(diǎn)地位與營(yíng)銷(xiāo)效果的關(guān)系,運(yùn)用社群識(shí)別方法,對(duì)社交網(wǎng)絡(luò)進(jìn)行分群,提出并用Map Reduce實(shí)現(xiàn)了針對(duì)大規(guī)模社交網(wǎng)絡(luò)的社群劃分RMCL方法。在此基礎(chǔ)上,構(gòu)建了客戶(hù)影響度與客戶(hù)影響因子等指標(biāo),并結(jié)合中心度指標(biāo),定位社群的核心節(jié)點(diǎn),并采用分類(lèi)回歸樹(shù)方法,研究了社交網(wǎng)絡(luò)結(jié)構(gòu)與客戶(hù)消費(fèi)響應(yīng)關(guān)系,并確定了變量重要性,為企業(yè)采取客戶(hù)差異化營(yíng)銷(xiāo)組合策略提供指導(dǎo)。
[Abstract]:Big data provides the important support for the enterprise to carry on the precision marketing, the precision marketing can enhance the marketing effect, enhances the customer satisfaction, the precision marketing premise is the customer identification and the choice. By analyzing the characteristics of individuals and groups, social network analysis can locate core value customers. Firstly, this paper analyzes the centrality of social network, discusses the relationship between the status of social network node and the effect of marketing, and classifies the social network by using the method of community identification. A community partitioning RMCL method for large scale social networks is proposed and implemented with Map Reduce. On the basis of this, we construct some indexes, such as customer impact degree and customer impact factor, and combine the centrality index to locate the core nodes of the community, and use the classification regression tree method to study the relationship between social network structure and customer consumption response. And determine the importance of variables for enterprises to take customer differentiation marketing mix strategy to provide guidance.
【作者單位】: 長(zhǎng)沙理工大學(xué)經(jīng)濟(jì)與管理學(xué)院;美國(guó)北密歇大學(xué)數(shù)學(xué)與計(jì)算機(jī)科學(xué)系;奇虎360科技有限公司;
【基金】:國(guó)家社會(huì)科學(xué)基金(No.13BGL063)
【分類(lèi)號(hào)】:TP301.6;TP393.09
【參考文獻(xiàn)】
相關(guān)期刊論文 前4條
1 王虹旭;吳斌;劉e,
本文編號(hào):1953679
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