A Fuzzy Logic Approach for the Assessment of Online Customers

A Fuzzy Logic Approach for the Assessment of Online Customers

Nicolas Werro, Henrik Stormer
Copyright: © 2012 |Pages: 18
DOI: 10.4018/978-1-4666-1598-4.ch022
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A key challenge for companies in the e-business era is to manage customer relationships as an asset. In today’s global economy this task is becoming simultaneously more difficult and more important. In order to retain the potentially good customers and to improve their buying attitude, this chapter proposes a hierarchical fuzzy classification of online customers. A fuzzy classification, which is a combination of relational databases and fuzzy logic, allows customers to be classified into several classes at the same time and can therefore precisely determine the customers’ value for an enterprise. This approach allows companies to improve the customer equity, to launch loyalty programs, to automate mass customization, and to refine marketing campaigns in order to maximize the customers’ value and, this way, the companies’ profit.
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Fuzzy Classification Toolkit

The proposed fuzzy classification toolkit is based on an extension of the Structured Query Language SQL. SQL is the standard for defining and querying relational databases. By adding to the relational database schema a context model with linguistic variables and fuzzy sets, the query language has to be extended. The proposed extension is the fuzzy Classification Query Language fCQL, described by Schindler (cf. Schindler 1998).

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