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Information Journal Paper

Title

Life Insurance Market Segmentation Using Neural Network

Pages

  74-88

Abstract

 In the marketing process, one of the strategic tools that influences all market mix decisions is the process of Market Segmentation, market selection and market positioning. Proper implementation of this process will enable marketers to gain a better view and understanding of customers and, as a result, better meet their needs. Different criteria have been proposed for Market Segmentation and various analytical tools are used. In this study, an attempt was made to identify the sectors of this market, considering the importance of Life Insurance in the insurance industry from the perspective of income generation and investment, as well as its share of the total industry portfolio. The present research is of applied type and its method is quantitative and the scope of the present research is libraries and databases. The variables that are considered as the basics of Market Segmentation in this study are: monthly income, marital status, ratio of insurer to insured, gender, age, province of birth. The statistical population of this study was the individual Life Insurance customers of Parsian Insurance Company in 2018, which includes 58181 items of insurance policies, of which 711 insurers were selected as a sample randomly from parsian insurance Life Insurance data warehouse. SOM Neural Networks was used and six market segments were identified.

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  • Cite

    APA: Copy

    Haghighinasab, Manijeh, & NIAKAN LAHIJI, NAZILA. (2020). Life Insurance Market Segmentation Using Neural Network. CONSUMER BEHAVIOR STUDIES, 7(2 ), 74-88. SID. https://sid.ir/paper/965891/en

    Vancouver: Copy

    Haghighinasab Manijeh, NIAKAN LAHIJI NAZILA. Life Insurance Market Segmentation Using Neural Network. CONSUMER BEHAVIOR STUDIES[Internet]. 2020;7(2 ):74-88. Available from: https://sid.ir/paper/965891/en

    IEEE: Copy

    Manijeh Haghighinasab, and NAZILA NIAKAN LAHIJI, “Life Insurance Market Segmentation Using Neural Network,” CONSUMER BEHAVIOR STUDIES, vol. 7, no. 2 , pp. 74–88, 2020, [Online]. Available: https://sid.ir/paper/965891/en

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