عنوان مقاله [English]
Objective: Insurance companies must use new methods to increase public attention, attract new customers and retain former customers, due to the low penetration of insurance in Iran. In insurance industry, the analysis of customers’ buying behavior is very important, and today new technologies are used in this field.
Methodology: One of the features of new customer relationship management softwares is the possibility of gamification, which has the ability to implement attractive and diverse solutions such as scoring, rewards, sharing, etc. Data mining techniques can use the information in insurance companies’ databases, to classify customers from different perspectives (loyalty, profitability, etc.) and suggest solutions for categorizing customers into different groups according to the characteristics of each group. Today, there are various tools for implementing data mining algorithms, and it is easy to master these tools, present useful projects and use them in companies.
Results: In this article, we have tried to classify insured and help experts using Python programming language and data mining algorithms.
Conclusion: In order to implement the proposed method, the data related to the real insured of Alborz Insurance Company in the last three years have been used while maintaining the security and confidentiality of the data. The insured are divided into 4 categories of special, superior, middle and weak insured. Appropriate gamification methods tailored to each group of clients according to their gender, age, etc. can be used.
JEL Classification: G22, C38, C53