Customer Cluster Analysis Using SOM-A Case Study of SMS Company Customer Service以SOM 進行顧客群集分析之研究-以簡訊業者客戶服務為例

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Title:	Customer Cluster Analysis Using SOM-A Case Study of SMS Company Customer Service以SOM 進行顧客群集分析之研究-以簡訊業者客戶服務為例
Authors:	許良僑 Sheu, Liang-Chyau
Contributors:	科技管理學系 Technology Management
Keywords:	顧客分群；行銷策略；自組織映射圖網路；資料探勘 Customer Clustering;Marketing Strategy;Self-Organizing Map;Data Mining
Date:	2010
Issue Date:	2014-06-27 01:15:13 (UTC+8)
Abstract:	本研究以簡訊業者為案例，首先將顧客過去的消費行為，包括購買行為、發送行為、發送對象以及業務拓展，建立特徵擷取與正規化，採用類神經網路中資料分群之方法一自組織映射網路(Self-Organizing Map,SOM)，找到顧客群組樣本類型，再將群組狀態分析，找出顧客類型分類後，再依顧客類型制定行銷手法。第二階段利用SOM回想技術，針對分群結果將近期顧客於群組落點分類判斷，再次以SOM回想技術判別屬何種顧客，易於企業將新顧客分類，再選擇對企業適當的行銷策略，亦即可有助於企業獲取更高的報酬，及提升顧客之保留率。 In this paper, a Self-Organizing Map (SOM) is used to cluster consumers based on customer data of a short message service (SMS) company. First, raw data are quantified and normalized for the learning phase of SOM. The clusters found by the SOM are then us
Appears in Collections:	[Department of Technology Management] Seminar Papers

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