sidharth178 / Market-Segmentation-in-SBI-life-Insurance

A machine learning clustering model for customer segmentation to define marketing strategy.

Market Segmentation in SBI life 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

Dependency Libraries :

• Python 3.x
• scikit-learn
• scipy
• pandas
• numpy
• matplotlib
• seaborn
• jupyter notebook

Installation Commands :

If using pip ->

• Pandas: - pip install pandas
• numpy: - pip install numpy
• scipy: - pip install scipy
• scikit-learn: - pip install scikit-learn
• matplotlib: - pip install matplotlib
• seaborn: - pip install seaborn
• jupyter notebook: - pip install jupyter

If using anaconda ->

• Pandas: - pip install pandas
• numpy: - pip install numpy
• scipy: - pip install scipy
• scikit-learn: - pip install scikit-learn
• matplotlib: - pip install matplotlib
• seaborn: - pip install seaborn
• jupyter notebook: - pip install jupyter

Troubleshoot

Any issues??? Feel free to ask.Linkedin

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Thanks! ❤️