Mall Customer Segmentation

This project uses KMeans clustering via Jupyter Notebook with Python to segment customers based on their age, annual income, and spending score. It helps mall management understand customer behavior and optimize marketing strategies.

Dataset

Source: Mall_Customers.csv

Columns:

Gender

Age

Annual Income (k$)

Spending Score (1–100)

Project Workflow

Data Cleaning

Exploratory Data Analysis (EDA)

KMeans Clustering

Cluster Profiling

Business Recommendations

Highlights

Identified 5 customer segments using KMeans.

Used Elbow Method to find optimal clusters.

Cluster visualizations (scatter plots, radar charts).

? Business insights for targeted marketing.

Libraries Used

pandas

seaborn

matplotlib

sklearn