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Performed Data Cleaning and Data Augmentation on customer data. Calculated RFM score for each customers and grouped customers based on their RFM score. And finally performed K-Means Clustering and used PCA to visualize the clusters in 2D and 3D.

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Data-Analysis-and-Customer-Segmentaion

I used dataset from a KPMG Virtual Internship program at Insidesherpa to do the following things. Performed Data Cleaning and Data Augmentation on customer data. Calculated RFM score for each customers and grouped customers based on their RFM score. And finally performed K-Means Clustering and used PCA to visualize the clusters in 2D and 3D.

1. (EDA) and Data Cleaning; Customer Demographic

2. (EDA) and Data Cleaning; Transactions

3. (EDA) and Data Cleaning; Customer Address

4. (EDA) and Data Cleaning New Customers

5. Merging different datasets

6. RFM Segmentation on existing customers.

7. Adding the RFM segments to customers data

8. Performing K-Means Clustering and Visualizing the clusters using PCA

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Performed Data Cleaning and Data Augmentation on customer data. Calculated RFM score for each customers and grouped customers based on their RFM score. And finally performed K-Means Clustering and used PCA to visualize the clusters in 2D and 3D.

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