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Activity Number:
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268
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and Marketing
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| Abstract - #300456 |
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Title:
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Customer Segmentation: Data Mining Application for the Auto Insurance Industry
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Author(s):
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David S. Dobson*+
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Companies:
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North Carolina State University
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Address:
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2586 East 17th Avenue, Vancouver, BC, , Canada
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Keywords:
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Automobile Insurance ; Cluster Analysis ; Customer Data ; Customer Profiling ; Customer Segmentation ; Data Mining
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Abstract:
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As the auto insurance industry becomes more value-competitive, insurance companies are facing challenges to maintain their market share. To understand their customers better and create effective marketing initiatives, companies can profile their customers using data mining techniques. Using customer profiling, companies can initiate customized marketing messages that reach out to the target group by tailoring products and services to the individual customer's needs. This can lead to increased customer engagement and stronger customer relationships. This paper demonstrates the steps that are taken in the data mining process. Fictitious data are used as input data for this study. The research goal is to segment current customers based on their driver history data using cluster analysis, and then to profile each segment to understand which are high risk customers and which are safe.
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