Research On Purchasing Behavior and Marketing Strategy Optimization of Commercial Medical Insurance Based on Unsupervised Learning Algorithms

Tianyi Ren

doi:10.62051/ijcsit.v4n1.14

Authors

Tianyi Ren

DOI:

https://doi.org/10.62051/ijcsit.v4n1.14

Keywords:

Unsupervised learning methods, Machine learning, Policies and suggestions, Insurance companies and sellers

Abstract

Being a marketer in today's world is not an easy job, especially in the insurance industry, where many factors affect whether customers buy insurance and how much they buy. This field also has many research topics and areas worth exploring. In this article, the data used is real insurance sales data and used unsupervised learning methods in machine learning to clean, mine and analyze the data. First, using clustering methods to divide people who buy insurance into three categories based on weight and insurance expenses. Then using association rule learning methods to analyze the recurring features among people who buy insurance. Finally, based on these results, many policies and suggestions can be given from the perspective of insurance companies and sellers.

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