This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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615
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and Marketing
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Abstract - #308167 |
Title:
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Data Augmentation by Updating Long-Term CRM Models with Day-Specific Meteorological Conditions
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Author(s):
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Philippe Baecke* and Dirk Van den Poel+
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Companies:
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Ghent University and Ghent University
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Address:
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Department of Marketing, Gent, International, 9000, Belgium
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Keywords:
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data augmentation ;
CRM ;
customer intelligence ;
meteorological variables ;
predictive performance
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Abstract:
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In the past decades CRM models have become important decision support systems for management. These models can help to predict future sales and rank customers based on their predicted profitability. During recent years, the rise in computational power makes it possible to update long-term CRM models on a daily basis. This enables researchers to include day-specific meteorological conditions, which is of relevance to predictions of consumption levels of products sensitive to climatic conditions. In this study, we present a methodology to include this kind of data in an efficient way and increase the predictive performance of CRM models.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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