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  • 學位論文

客戶價值分析-以婦幼衛生用品製造商為例

Customer Value Analysis for Feminine Care and Baby Diaper Manufacturers

指導教授 : 盧以詮
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摘要


台灣婦幼衛生用品市場高度成熟化、市場逐漸飽和且產品價格競爭度高。有鑑於此,本研究擬以婦幼衛生用品製造商K公司之客戶進行分析,探討客戶之價值。本研究使用RFM模型計算客戶價值及K-means分群演算法建立分群模型,分析婦幼衛生用品製造商K公司客戶分群結果之特性。分析在K公司現行有銷售客戶中具有價值的客戶,並為K公司帶來有價值的客戶資訊,以提供決策判斷之依據使用。研究結果顯示,本研究所建構的分群模型,可分為最佳型、消費型、頻率型、不確定型、潛力型及消失型等六群客戶,其中,最佳型,頻率型與潛力型之客戶為K公司有價值之客戶,此三群客戶即包含約90%之銷售比例。

關鍵字

婦幼衛生用品 客戶價值 RFM K-means

並列摘要


Feminine care and baby diaper supplies market is highly sophisticated, market saturation and price competition high. This study intends to customers of Company K of the feminine care and baby diaper manufacturer for analysis to explore the value of the customer. In this study, using the RFM model to calculate the customer value and K-means clustering algorithm to establish the clustering model, and analyze the characteristics of the feminine care and baby diape supplies manufacturer K customer clustering results. Analysis of Company K of existing customers of the value of sales customers, Company K, valuable customer information to provide a basis for decision making. The results show that the clustering model, this research regarding (A) Best , (B) Spender, (C) Frequent , (D) Uncertain, (E) Potential and (F) Disappearance can be divided into six groups of customers.Among them, the Best , Frequent and Potential types of customer for the valuable customers of Company K, this three groups of customers which includes about 90% the proportion of sales.

並列關鍵字

Feminine Care Customer Value RFM K-means

參考文獻


[11] 吳長興,「應用資料探勘技術建立顧客關係管理之行銷策略」,國立成功大學,碩士論文,2004年。
[13] 羅巧芳、吳信宏、張恩啟、鄭易英,「應用資料探勘於戶外活動用品專賣店之顧客忠誠及價值分析」,品質學報,第十五卷第四期,293-303頁,2008年。
[4] Sung, H. H. and Sang, C.P., "Application of data mining tools to hotel data mart on the Internet for database marketing," Expert Systems With Application, Vol 15, pp 1-31, 1998.
[5] Marcus, C., "A practical yet meaningful approach to customer segmentation," Journal of consumer marketing, Vol 15, pp 494-504, 1998.
[6] Miglautsch, John, "Thoughts on RFM Scoring", Journal of Database Marketing, Vol.8, 2000.

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