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Enhanced Rule Induction Algorithm for Customer Relationship Management |
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PP: 1471-1478 |
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Author(s) |
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Prabha Dhandayudam,
Ilango Krishnamurthi,
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Abstract |
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| Customer Relationship Management (CRM) helps businesses to gain insight into the behavior of customers and their value
so that the company can increase their profit by acting according to the customer characteristics. In order to analyze the customer
needs and behavior, data mining is used to extract information from the customer database. For analyzing the customer behavior, the
important attributes in the customer database are first chosen and then they are segmented into groups using clustering algorithm based
on those attribute values. The rules are then generated to describe the customers in each group using LEM2 (Learning from Examples
Module, version 2) algorithm and the proposed algorithm. These rules can be used by the business people to predict the behavior and
to vary their promotional activities like coupon distribution and special discounts. It is observed that the proposed algorithm is better in
terms of time complexity and performance measures. |
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