以RFM分析和CAI分析建置顧客推薦系統 —以超級市場為例

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Title:	以RFM分析和CAI分析建置顧客推薦系統 —以超級市場為例 Applying RFM and CAI Analyses building Personalized Recommendation System: Supermarket as an Example
Authors:	劉傑滔
Contributors:	國際企業管理學系
Keywords:	RFM 顧客活躍性指標推薦系統 RFM Customer Activity Index Recommended system
Date:	2016-06
Issue Date:	2016-08-02 14:52:20 (UTC+8)
Abstract:	隨著大數據應用的爆發性增長，將產品結合雲端和互聯網等資訊科技，透過消費者消費和使用產品情形所衍生的數據，進行顧客關係管理。大數據時代的來臨，未來的零售業要成功，勢必要掌握顧客資料庫以及進行適當之顧客關係管理。超市流失顧客的原因主要分為，超市環境和形象、超市服務、便利性和商品問題幾個方面，卻沒有明確表白應如何進行管理。回顧先前研究，國內有關超市利用顧客資料庫進行顧客關係管理(Customer Relationship Management, CRM)的相關文獻，均主要著重於探討環境因素對消費者購物準則的影響，而忽略了資料庫行銷數據與消費者購物關係的相互依存關係。為解決此一研究缺口，本研究透過顧客價值分析(Recency Frequency Monetary, RFM)、顧客活躍性分析(Customer Activity Analysis)、購物籃分析(Market Basket Analysis)與邏吉斯迴歸分析(Hierarchical Regression)等方法，分析顧客價值類型、建置顧客推薦系統。 Along with the massive growth of the usage of Big Data, data of customer purchasing habits are collected through the combination of Cloud technology, the Internet of Things and the feedback of the clients. Enterprises analysis their customers with the aid of the data and use it for customer relations management. In the era of the Big Data, enterprises will need to make use of these data to maximize their understanding of their customer for targeted customer relation management and thus establish a successful business. The reasons for supermarkets losing their customers are analyzed as follow, environment, company image, service quality, convenience, and products. These factors are somehow related but there is no clear resolution suggested. After revised the previ-ous studies in the country on the topic "Customer Relationship Management", the ma-jority of them are focusing on how the environment factor affects the purchasing princi-ples of the customers, neglected the relationship of the marketing management data and the customer. To fill the gap in the field, this study will analysis customer values and suggest the establishment of recommended system based on analyzing Recency Frequency Monetary, Customer Activity Analysis, Market Basket Analysis and Hierarchical Re-gression of the supermarket customers.
Appears in Collections:	[Department of Business Administration & Graduate Institute of International Business Administration ] Thesis

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