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Optimization of Multiple Campaigns Reflecting Multiple Recommendation Issue  

Kim Yong-Hyuk (서울대학교 기계항공공학부)
Moon Byung-Ro (서울대학교 컴퓨터공학부)
Publication Information
Journal of KIISE:Software and Applications / v.32, no.5, 2005 , pp. 335-345 More about this Journal
Abstract
In personalized marketing, it is important to maximize customer satisfaction and marketing efficiency. As personalized campaigns are frequently performed, several campaigns are frequently run simultaneously. The multiple recommendation problem occurs when we perform several personalized campaigns simultaneously. This implies that some customers may be bombarded with a considerable number of campaigns. We raise this issue and formulate the multi-campaign assignment problem to solve the issue. We propose dynamic programming method and various heuristic algorithms for solving the problem. With field data, we also present experimental results to verify the importance of the problem formulation and the effectiveness of the proposed algorithms.
Keywords
personalized marketing; multi-campaign assignment; response suppression function; dynamic programming; heuristic algorithms;
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