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運用RFM模型分析顧客消費行為與貢獻度之研究及應用實務-以中油會員卡顧客為例

Analysis of Consumers' Consumption Behavior and Degree of Contribution by Using RFM Model and the Practical Applications: A Case Study of CPC Members

摘要


「顧客關係管理」一詞在近年來受到熱烈的討論及研究,而顧客價值分析是顧客關係管理的基礎,在顧客價值分析的方法中,又以Hughes提出的RFM模型最常被提及與運用。藉由RFM模型中的三項衡量指標,便可簡單而清楚地勾勒出顧客消費行為的輪廓,以提供企業進行消費行為分析並研擬顧客關係經營策略。本研究以RFM模型為基礎,考量石油在產品、訂價策略上的特性進行修正,發展出油品零售通路的顧客價值分析模型。透過此模型所尋找出來的高價值流失顧客,採取行銷活動後,有高達49%的顧客挽留率。另外,運用此模型篩選出計程車營業卡金字塔顧客,推薦至加油站附屬的車輛快速保養中心消費,創造了較同期業績成長64%的佳績。證明此模型也相當適合運用在加油站資料庫行銷上,RFM模型不僅協助企業掌握重要顧客,更是幫助企業有效分配行銷資源的一項實用分析工具。

並列摘要


In recent years, ”Customer relationship management (CRM)” has been discussed and studied widely. However customer value analysis is the basis of CRM. In many methods of customer value analysis, RFM model proposed by Hughes has been most often mentioned and utilized. Using the three indicators (Recency, Frequency, Monetary amount) of RFM model, customer consumption behavior can be outlined simply and clearly, and used to provide enterprises to analyze consumption behavior and to plan their own strategies of customer relationship management. This study is based on RFM model, revised by considering the characteristics of oil products and pricing strategies, and developed to a model of customer value analysis of retail channel of oil products. The loss of high value customers can be found by this model and the customer retention rate is 49% after taking promotion campaigns. In addition, the best customers of taxi business card customers were filtered out by the model and recommended to consume in the express service center of gas stations and created the growth of business 64%. The model has been proved that it can be used in the promotion of gas station database properly. RFM model is a practical analysis tool that can not only help enterprises keep their important customers, but also help them distribute promotion resources effectively.

被引用紀錄


陳協慶(2015)。巨量資料運用於流通業商業智慧系統發展佈局之研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2015.00446
陳秀慧(2013)。應用基因演算法於RFM模型權重最佳化之研究〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841/NTUT.2013.00760
吳岱壎(2012)。運用資料採礦技術於零售業之研究—以居家用品專賣店為例〔碩士論文,國立臺北大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0023-2907201223051400
鍾永富(2013)。運用資料探勘技術協助行銷策略制定之研究— 以家庭清潔用品為例〔碩士論文,國立臺北大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0023-2101201301440700

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