Customer Segmentation Web App Using ML Clustering

I developed a customer segmentation tool using machine learning techniques to help businesses better understand and target their audiences. The app analyzes customer data — such as income, age, and spending score — and applies clustering algorithms like K-Means and DBSCAN to group users based on behavior patterns. The project was built in Python using pandas and scikit-learn, and deployed using Streamlit for an interactive experience. The resulting clusters allow businesses to personalize marketing efforts and improve decision-making. The visuals below show the clustering results, user interface, and a sample of how customer segments are separated in 2D space.