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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/96931


    Title: Combing Customer Profiles for Members' Repurchase Rate Predictions
    Authors: Wang, Yi-Hsin;Chiang, Rui-Dong;Chu, Huan-Chen
    Contributors: 淡江大學資訊工程學系
    Keywords: CRM;Customer profile;Concept drift detection;Repurchase rate prediction
    Date: 2013-06-01
    Issue Date: 2014-03-14 13:00:19 (UTC+8)
    Publisher: Oulu: Academy Publisher
    Abstract: Customer relationship management (CRM) leverages historical users’ behaviors in order to dawn effort of enhancing customer satisfaction and loyalty. Thus, constructing a successful customer profile plays a critical role in CRM. As customers’ preferences may change over time, we take the different types of past behavior patterns of the registered members to capture concept drifts. Then, we combine the repurchase index (RI) and the preference drifts to propose a Behavioral Repurchase Prediction (BRP) model, and to predict the members’ repurchase rates in the specific category of the e-shop. The marketers of the e-shop can target the registered members with high repurchase rates and design corresponding marketing strategies. The experimental results with a real dataset show that our model can effectively predict the registered members’ repurchase rates.
    Relation: Journal of Software 8(6), pp.1316-1326
    DOI: 10.4304/jsw.8.6.1316-1326
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

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