This repository uses Python and Scikit-Learn to perform K-Means clustering on 8,950 customer records with 17 features. The project aims to segment customers by behavior to enable targeted marketing strategies.
From the README
🎯🛍️ Customer Segmentation for Targeted Marketing 🛍️🎯 An unsupervised machine learning project that segments customers by behavior so marketing can target each group differently, instead of treating every customer the same. 📌 Project Overview This project analyzes customer behavioral data using Python and Scikit-Learn to uncover distinct spending segments through K-Means clustering. The project contains 8,950 customer records across 17 behavioral features, including balance, purchases, cash advances, and credit limit. The analysis focuses on preprocessing, choosing the right number of clusters rigorously (not arbitrarily), fixing a reproducibility issue, and making the resulting...
Skills
- Jupyter Notebook
