Market Segmentation in Insurance

Objective :

This case requires to develop a customer segmentation to give recommendations like saving plans, loans, wealth management, etc. on target customer groups.

Data Description :

The sample Dataset summarizes the usage behavior of about 9000 active credit card holders during the last 6 months. The file is at a customer level with 18 behavioral variables.

Data :

Use the below link to download the Data Set:here

Algorithms used :

In this dataset i've used five clustering algorithm to perform segmentation.These algorithms are given below.

• K-Means Clustering
• Agglomerative Clustering
• Spectral Clustering
• DBSCAN Clustering
• GaussianMixture Model based clustering

Final Model :

We have created a Streamlit Application based on this clustering technique, where we are taking the customer details & identifying which cluster the custoemr belongs to.