Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company

Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company

碩士 === 世新大學 === 資訊管理學研究所(含碩專班) === 103 === This research is using customers history transation log data to transfer to RFM customer-value-module for customer grouping.Using K-means method to clustering and analyzing in different retailers or customers attributes and cataloging every group, this rese...

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Bibliographic Details
Main Authors: Wen-Lung Tseng, 曾文隆
Other Authors: Yu-Chin Liu
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/62yk8j
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spelling ndltd-TW-103SHU053960602019-05-15T22:08:26Z http://ndltd.ncl.edu.tw/handle/62yk8j Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company 應用資料探勘技術於顧客價值分析與商品推薦之研究-以資訊產品通路商為例 Wen-Lung Tseng 曾文隆 碩士 世新大學 資訊管理學研究所(含碩專班) 103 This research is using customers history transation log data to transfer to RFM customer-value-module for customer grouping.Using K-means method to clustering and analyzing in different retailers or customers attributes and cataloging every group, this research finds out that the most high value contribution comes from less customers and it matchs the 80/20 rule.The heigh value customers from customer clustering analysis can help the company sales in this case to identify and review the VIP customer list and make an efficiency decision for good profits. Using Apriori method to analyzing in commodity trading information to get purchase rules and apply it on the basis of marketing or promote. Yu-Chin Liu 劉育津 2015 學位論文 ; thesis 66 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 世新大學 === 資訊管理學研究所(含碩專班) === 103 === This research is using customers history transation log data to transfer to RFM customer-value-module for customer grouping.Using K-means method to clustering and analyzing in different retailers or customers attributes and cataloging every group, this research finds out that the most high value contribution comes from less customers and it matchs the 80/20 rule.The heigh value customers from customer clustering analysis can help the company sales in this case to identify and review the VIP customer list and make an efficiency decision for good profits. Using Apriori method to analyzing in commodity trading information to get purchase rules and apply it on the basis of marketing or promote.
author2 Yu-Chin Liu
author_facet Yu-Chin Liu
Wen-Lung Tseng
曾文隆
author Wen-Lung Tseng
曾文隆
spellingShingle Wen-Lung Tseng
曾文隆
Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company
author_sort Wen-Lung Tseng
title Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company
title_short Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company
title_full Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company
title_fullStr Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company
title_full_unstemmed Data Mining Analysis on High Value Customers and Products recommendation-A Case Study of An IT Product Channel Company
title_sort data mining analysis on high value customers and products recommendation-a case study of an it product channel company
publishDate 2015
url http://ndltd.ncl.edu.tw/handle/62yk8j
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