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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 曹承礎 | |
dc.contributor.author | Chia-Chi Chang | en |
dc.contributor.author | 張家綺 | zh_TW |
dc.date.accessioned | 2021-05-19T17:45:52Z | - |
dc.date.available | 2023-08-02 | |
dc.date.available | 2021-05-19T17:45:52Z | - |
dc.date.copyright | 2018-08-02 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-07-31 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7536 | - |
dc.description.abstract | 隨著零售業快速成長,全台灣零售業營業額光是去年11月已達3,698億元台幣,但現今顧客的喜好越來越多元,企業不可能完全滿足每一個顧客,而這種挑戰在零售業中卻是非常常見的。但隨著資料庫的建立以及演算法的進展,對顧客進行區隔以及分類,能使企業盡力達到滿足每位顧客的目標。顧客區隔可以讓企業了解不同顧客群的行為和喜好,根據顧客的偏好制定行銷策略,更能有效的識別最能帶來收益的關鍵顧客群。
進行顧客區隔時,顧客交易資料是預測未來顧客購買行為的最有力和最可靠的資料,但目前雖然有大量運用顧客交易資料來區隔顧客的研究,卻很少有研究將產品交易數量,也就是產品的銷量考慮在內。因此本研究在進行顧客區隔時,把產品交易數量的概念加進分析,並同時比較無產品交易數量的結果,藉此證明產品交易數量確實能使顧客區隔更加準確、有效率。最後結合加入產品交易數量的分析方式與傳統RFM模型將顧客分群,找出真正具有價值的顧客,作為企業在推行促銷組合的參考依據。 | zh_TW |
dc.description.provenance | Made available in DSpace on 2021-05-19T17:45:52Z (GMT). No. of bitstreams: 1 ntu-107-R05725021-1.pdf: 3182530 bytes, checksum: 8b6ea17211811fc313cd0d2fb2bc217b (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 第1章 研究導論 7
1.1 研究背景 7 1.2 研究目的 9 第2章 文獻回顧 11 2.1 顧客區隔 11 2.2 RFM模型 13 2.3 歐幾里得距離與曼哈頓距離 15 第3章 研究架構及方法 18 3.1 資料集說明 18 3.2 研究架構 21 3.3 資料前處理 23 3.4 研究方法 25 3.4.1 顧客相似度定義與計算 25 3.4.2 RFM變數定義 31 3.4.3 疊圖分析 33 第4章 實驗結果 35 4.1 有數量及無數量比較 35 4.2 疊圖分析結果 36 第5章 結論 43 5.1 管理意涵 43 5.2 研究限制 43 第6章 文獻引用 45 | |
dc.language.iso | zh-TW | |
dc.title | 結合產品交易數量與RFM模型發展行銷策略 | zh_TW |
dc.title | Integrating Product Volume of Transaction Data and RFM Model to Develop Marketing Strategy | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 盧信銘,王貞雅 | |
dc.subject.keyword | 顧客區隔,交易資料,產品數量,RFM分析,促銷組合, | zh_TW |
dc.subject.keyword | Customer segmentation,Transaction data,Product volume,RFM analysis,Promotion,Product set, | en |
dc.relation.page | 47 | |
dc.identifier.doi | 10.6342/NTU201802255 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2018-07-31 | |
dc.contributor.author-college | 管理學院 | zh_TW |
dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
dc.date.embargo-lift | 2023-08-02 | - |
顯示於系所單位: | 資訊管理學系 |
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