Automatic Fuzzy Classification Tool for Customer Loyalty Using Gaussian Membership Function

Retaining customers in current era is of utmost importance and crucial for the success of any business enterprise. Identifying potential and loyal customers for any enterprise is of great importance. Customer loyalty is one of the major aspects of Customer Relationship Management (CRM). It is very important for an organization to identify its loyal customers, so that the organization can provide better and special services to these customers in order to enhance their business. In this paper, the construction of fuzzy decision tree has been refined by assigning the weights to each attribute, as all the attributes may not affect the customer loyalty equally.

This paper proposes an application, which makes use of fuzzy decision trees for classifying customers into various categories. Rather than identifying a customer crisply falling near to the end boundaries, soft boundaries (concept of fuzziness) are used which classifies the customer into different predefined classes of loyalty from the information stored about the customers by the organization.

This procedure helps in classifying customers in a better way as compared to crisp classification. The proposed framework is evaluated on a sample dataset that provides encouraging results.