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題名 | 應用模糊關聯規則建立連鎖咖啡店之顧客價值模型=Applying Fuzzy Association Rules to Establish Customer Values Model for Coffee-Shops |
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作者 | 蔣文育; Chiang, Wen-yu; |
期刊 | 數據分析 |
出版日期 | 20231200 |
卷期 | 18:3 2023.12[民112.12] |
頁次 | 頁59-78 |
分類號 | 991.7 |
語文 | chi |
關鍵詞 | 顧客價值; RFMDT模型; Apriori演算法; Customer values; RFM model; Fuzzy K-Means; RFMDT model; Apriori algorithm; |
中文摘要 | 本研究目的在於建構與改良顧客關係管理中的顧客價值模型(Recency, Frequency and Monetary, RFM model),經由模型的建立可精確的掌握連鎖咖啡店產業市場之顧客價值,進而提升咖啡產業之顧客價值。本文以台北市之連鎖咖啡店消費顧客為研究對象,研究方法採用模糊聚類分析法(Fuzzy K-Means, FKM)對消費顧客進行市場區隔分析,分群結果發現連鎖咖啡店消費之三個硬性市場與其模糊市場:成本考量、方便考量、與專業考量。並以改良式之Recency, Frequency, Monetary, Discount, and Turnover(RFMDT)模型導向監督式Apriori演算法進行分析,建構4項連鎖咖啡店顧客價值關聯規則、與2項模糊關聯規則,此模型建議可套入顧客關係管理軟體之學習功能中,達到對顧客價值之認知品質提升,並可作為連鎖咖啡產業行銷決策之方案基礎。 |
英文摘要 | The objective of this research is to improve and establish customer value (Recency, Frequency, and Monetary, RFM model) of Customer Relationship Management (CRM). Customer value can be handled and promoted precisely by the established model. The research objects are experienced shoppers of chain store within six months in Taipei city. The researcher uses Fuzzy K-Means (FKM) method to process market segmentation to find four clusters. Their features are: convenience consideration, café quality, and cost consideration. The Recency, Frequency, Monetary, Discount, and Turnover (RFMDT) model (revised based on RFM) is applied on the Apriori algorithm to establish four association rules and two fuzzy association rules. This model can be employed in the learning software of CRM system in order to identify and enhance customer value of the café chain store industry. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。