Using Association Rule Mining for Customer Relationship Management in Insurance Sector

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Today, the development of information technology, increased competition, change in customer profile have affected firms’ relationship with customers. CRM (Customer Relationship Management) is required to be in continuous contact with customers to increase customer loyalty and satisfactions and it aims to identify customer’s needs and requests to meet the expectations. Customer relationship management is primarily based on the collection of data about customers as much as possible. Therefore, data warehouses in companies are combined together and analyses are performed to determine the characteristics of customers. With this data, it is possible to find which types of products customers prefer to buy and this information will help and give directions of communication with the customers. DM (Data Mining) provides benefits at this stage which is the process of extraction of meaningful information and patterns through the analysis of data. In this study, a leading insurance company’s customer data that is operating in Turkey is used. Apriori algorithm which is the most widely used association rule mining algorithm is applied to this dataset. This analysis reveals combinations of product groups that customers prefer to buy. Taking advantage of this association rule analysis results in terms of customer relationship management, it is possible to make more effective sales campaign and to develop marketing strategies.

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Customer Relationship Management , Association Rule Mining , Apriori Algorithm

International journal of advances in engineering and pure sciences

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International journal of advances in engineering and pure sciences