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系統識別號 U0026-2812202016284100
論文名稱(中文) 應用數據分析於零售業通路行銷之研究
論文名稱(英文) Applying Data Analysis to Retail Channel Marketing
校院名稱 成功大學
系所名稱(中) 會計學系
系所名稱(英) Department of Accountancy
學年度 109
學期 1
出版年 109
研究生(中文) 劉璦遠
研究生(英文) Ai-Yuan Liu
學號 R16074208
學位類別 碩士
語文別 中文
論文頁數 38頁
口試委員 指導教授-徐立群
口試委員-李明錡
口試委員-高啟洲
中文關鍵字 沉睡顧客  喚醒行銷  商業智慧  RFM  精準行銷 
英文關鍵字 Sleep Customer  Evoking Marketing  BI  RFM  Precision Marketing 
學科別分類
中文摘要 對於任何一家企業來說,有一個重要的營運上之關鍵變數-顧客流失率,當一家公司的顧客流失率越高,也就表示這家公司有許多顧客跑到競爭對手的公司消費,或者存在著許多沉睡顧客。在各行各業中都有顧客流失的問題,通常企業都會試圖找出新顧客來取代流失顧客,但有研究指出更好的策略是喚醒這些沉睡已久的顧客。現今科技變遷迅速,公司內部資料量也越來越大,如何能從諸多資料中取得有效資訊,是目前許多公司都想得到的答案,而商業智慧就可以幫助公司有效的處理資訊並且協助管理階層做決策,像是顧客分群,顧客特徵、個人化推薦等。基於此,本研究提出一個通用喚醒行銷的篩選方法,將其應用到一家零售通路,藉由數據分析,找出該廠商的沉睡顧客。結果顯示,我們可以將一定數量有消費能力的沉睡顧客喚醒,符合廠商的需要。
英文摘要 There is a critical variable that is important to one of each enterprise - customer loss rate. The issue of losing the customer happens to all the industries. In general, the enterprise will try to locate the new customer as the replacement for lost customers. But some of the research indicates that wakes up the deep sleep customer will be considered a better strategy. Therefore, obtaining effective information from the vast database is the answer that all the companies want to achieve. Based on that, the study applied the data provided by a bedding retailer and proceed with the data analysis, and setting up three screening conditions for evoking marketing to locate the sleeping customer for the supplier. The screening conditions are the customer bears no transaction in a year-and-a-half, to dig out the customer with the potential purchasing power and the CAI value in the past must be excessive over zero. And to combine the customer's repurchase rate, the higher the possibility the early the priority to execute the marketing and promotion; the result indicates the screening condition in this study does fit into the supplier's characteristics and found the deep sleep customer with the purchasing power.
論文目次 第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 論文架構 2
第二章 文獻探討 3
2.1 商業智慧(Business Intelligence) 3
2.1.1智慧零售 3
2.2 一般行銷 4
2.2.1 行銷定義 4
2.2.2 行銷理論演變 4
2.3 精準行銷(Precision Marketing) 6
2.3.1 精準行銷定義 6
2.3.2 RFM模型 6
2.4 喚醒行銷 9
2.4.1 顧客價值 10
2.4.2 顧客關係管理(Customer Relationship Management) 11
2.4.3 沉睡顧客 11
第三章 分析方法 14
3.1 流程架構 14
3.2 設計喚醒行銷之考量 15
3.2.1 商品週期 15
3.2.2 顧客消費能力 16
3.2.3 顧客活躍度 (Customer Active Index, CAI)分析 17
3.2.4結合精準行銷回購機率排名 20
3.3 商業智慧分析 21
第四章 實證結果 23
4.1 資料來源與描述型分析 23
4.2 喚醒行銷的條件及人數分布 26
4.3 實際測試結果及成效 28
4.4 顧客RFM分群 31
第五章 結論 33
5.1 結論 33
5.2 研究限制與建議 34
參考文獻 35
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