Title: Analytical customer relationship management in insurance industry using data mining: a case study of Indian insurance company

Authors: Vishal Bhatnagar; Jayanthi Ranjan; Raghuvir Singh

Addresses: Ambedkar Institute of Technology, Geeta Colony, Delhi – 110031, India. ' Institute of Management Technology, Raj Nagar, Ghaziabad – 201001, India ' Shobhit University, NH-58, Modipuram, Meerut – 250110, India.

Abstract: The insurance organisations have strong customer base with vast amount of data which is very difficult to manage in terms of finding unknown and hidden patterns from it. The growing demand of information which will provide assistance to decision makers in building a strong customer base and good image in customers mind is guiding a path towards extensive usage of analytical tools for revealing hidden information|s. The data mining (DM) has emerged as such tool that provide hidden information|s and patterns from customer data, and thus helps in organisation|s achieve an information|s which will provide customer satisfaction and increase customer base. The stiff competitions in insurance sector also demand that organisations should have cutting edge over their competitors. These requires the in depth analysis of the customer data using DM tools. We authors through this paper highlighted the importance and significance of DM techniques and tools in managing customer relationship management (CRM) by finding the hidden and unknown information from the real case data of insurance company. We had analysed through our research customer|s satisfaction level, churners and non-churners and much other information|s which will increase the profitability of the organisation and will provide customer satisfaction.

Keywords: customer relationship management; analytical CRM; aCRM; data mining; information technology; TPAs; third party administrators; insurance industry; India; customer satisfaction.

DOI: 10.1504/IJNVO.2011.043803

International Journal of Networking and Virtual Organisations, 2011 Vol.9 No.4, pp.331 - 366

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 21 Nov 2011 *

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