An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning
Given the competitive market of the insurance industry, customer retention is one of the most important goals of insurance brokers. As a matter of fact, attracting a new customer as well as establishing a relationship with the insurer and gaining his trust requires a lot of money. However, the cost...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | fas |
| Published: |
University of Qom
2024-03-01
|
| Series: | مدیریت مهندسی و رایانش نرم |
| Subjects: | |
| Online Access: | https://jemsc.qom.ac.ir/article_2792_8988dcf61b883f1423baf90dd9fd98c1.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832577540234936320 |
|---|---|
| author | Kamran Balani Hossein Sadr Ahmad Edalatpanah Mahnaz Manteghipour Mojdeh Nazari |
| author_facet | Kamran Balani Hossein Sadr Ahmad Edalatpanah Mahnaz Manteghipour Mojdeh Nazari |
| author_sort | Kamran Balani |
| collection | DOAJ |
| description | Given the competitive market of the insurance industry, customer retention is one of the most important goals of insurance brokers. As a matter of fact, attracting a new customer as well as establishing a relationship with the insurer and gaining his trust requires a lot of money. However, the cost of attracting new customers is much more than retaining existing customers. Accordingly, marketing strategies have shifted from product-oriented and many companies have turned to customer relationship management.Companies and organizations have found that retaining their current customers as their most valuable asset is highly important. Therefore, the strategy of insurance companies is to first retain existing customers and then attract new customers. In this regard, identifying the effective factors in customer turnover is essential. In this paper, data mining methods are used to predict the factors affecting customer dissatisfaction. Based on the empirical results, it has been determined that the customer attraction channel, purchase history and place of insurer are important factors affecting customers dissatisfaction in the insurance industry, respectively. |
| format | Article |
| id | doaj-art-7f20627472dd4665973d77872836e0b4 |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2024-03-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-7f20627472dd4665973d77872836e0b42025-01-30T20:19:06ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752024-03-01929110510.22091/jemsc.2024.9138.11702792An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble LearningKamran Balani0Hossein Sadr1Ahmad Edalatpanah2Mahnaz Manteghipour3Mojdeh Nazari4Department of Computer Engineering, Ayandegan Institute of Higher Education, Tonekabon, IranDepartment of Computer Engineering, Rasht branch, Islamic Azad University, Guilan, IranDepartment of Mathematics, Ayandegan Institute of Higher Education, Tonekabon, IranData mining desk leader, Insurance Research Center, Tehran, Iranshahid beheshti tehranGiven the competitive market of the insurance industry, customer retention is one of the most important goals of insurance brokers. As a matter of fact, attracting a new customer as well as establishing a relationship with the insurer and gaining his trust requires a lot of money. However, the cost of attracting new customers is much more than retaining existing customers. Accordingly, marketing strategies have shifted from product-oriented and many companies have turned to customer relationship management.Companies and organizations have found that retaining their current customers as their most valuable asset is highly important. Therefore, the strategy of insurance companies is to first retain existing customers and then attract new customers. In this regard, identifying the effective factors in customer turnover is essential. In this paper, data mining methods are used to predict the factors affecting customer dissatisfaction. Based on the empirical results, it has been determined that the customer attraction channel, purchase history and place of insurer are important factors affecting customers dissatisfaction in the insurance industry, respectively.https://jemsc.qom.ac.ir/article_2792_8988dcf61b883f1423baf90dd9fd98c1.pdfinsurance industrymarketing strategiescustomer dissatisfactiondata miningmachine learning |
| spellingShingle | Kamran Balani Hossein Sadr Ahmad Edalatpanah Mahnaz Manteghipour Mojdeh Nazari An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning مدیریت مهندسی و رایانش نرم insurance industry marketing strategies customer dissatisfaction data mining machine learning |
| title | An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning |
| title_full | An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning |
| title_fullStr | An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning |
| title_full_unstemmed | An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning |
| title_short | An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning |
| title_sort | intelligent method to identify effective factors in customers dissatisfaction in the insurance industry using ensemble learning |
| topic | insurance industry marketing strategies customer dissatisfaction data mining machine learning |
| url | https://jemsc.qom.ac.ir/article_2792_8988dcf61b883f1423baf90dd9fd98c1.pdf |
| work_keys_str_mv | AT kamranbalani anintelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT hosseinsadr anintelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT ahmadedalatpanah anintelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT mahnazmanteghipour anintelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT mojdehnazari anintelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT kamranbalani intelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT hosseinsadr intelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT ahmadedalatpanah intelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT mahnazmanteghipour intelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning AT mojdehnazari intelligentmethodtoidentifyeffectivefactorsincustomersdissatisfactionintheinsuranceindustryusingensemblelearning |