以關鍵商品分辨VIP客戶之研究; Discovering Key Products to Identify VIP Customers

NCUIR > School of Management at National Central University > Graduate Institute of Business Administration > Electronic Thesis & Dissertation > Item 987654321/59970

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/59970

Title:	以關鍵商品分辨VIP客戶之研究;Discovering Key Products to Identify VIP Customers
Authors:	鄭承祐;Cheng,Cheng-Yu
Contributors:	企業管理學系
Keywords:	資料探勘;RFM分析;顧客關係管理;Data mining;RFM analysis;customer relationship management
Date:	2013-06-24
Issue Date:	2013-07-10 11:53:31 (UTC+8)
Publisher:	國立中央大學
Abstract:	在現今激烈的商業環境中比競爭對手更快掌握顧客的需求是企業獲利的關鍵。企業為了瞭解客戶的需求以及消費模式，常利用資料探勘(Data mining)中的關聯法則(Association rules)去分析出客戶的購買習慣，也就是俗稱的購物籃分析(Market-basket analysis)。利用購物籃分析我們可以了解該在何時對何種顧客進行何種促銷計畫，進而發展出更周全的客戶關係管理機制(Customer relationship management)。　　以往的購物籃分析方法，或許能準確地分辨客戶的屬性，但是在顧客對於企業的貢獻程度方面則較無著墨。本論文則是藉由分析VIP顧客的購物行為進而發現關鍵商品。藉此關鍵商品預測為來購買此商品的客戶是否為VIP顧客。　　本論文實驗的結果總共找到四項關鍵商品。每項關鍵商品在驗證資料中對VIP顧客的區別比率皆在60%以上，其中兩項關鍵商品更可以高達70%以上。意即購買到關鍵商品的顧客，有60%以上的機率是我們欲開發的VIP顧客。因為本論文研究僅需要可辨識的會員編號，所以對於僅有會員編號的匿名資料探勘方法亦有相當的貢獻。 In today's competitive business environment faster than competitors to grasp the needs of customers is the key to create corporate profits. In order to understand customers’ needs and consumption patterns, enterprises usually using Data Mining and association rules to analyze customers' buying habits, also known as market basket analysis. We can use market basket analysis to understand what the customers' want and carry on propriety promotion plans, furthermore we can develop a customer relationship management strategy. Ordinary thesis about basket analysis may be able to accurately identify the customer's property, but the contribution of the customer for the enterprise is no mention. By using the aforementioned method In this paper, we total find a of four key commodities. Each key products in the testing data for VIP customers distinction ratios are more than 60%, of which two key products but also up to 70% or more. This means that customers buy key products, which are more than 60% probabilities who we want to develop a VIP customer. Because this thesis requires only recognizable membership number, so the only member number anonymous data mining methods are also considerable contributions.
Appears in Collections:	[Graduate Institute of Business Administration] Electronic Thesis & Dissertation

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