Name : NALLA DEEPIKA

Company : CODTECH IT SOLUTIONS

ID: CT08DS7222

Domain : Data Analytics

Duration : August 2024 to September 2024

This project focuses on customer segmentation using a dataset that includes customer demographics, annual income, and spending scores. The main objective is to segment customers into distinct groups based on their behavior using clustering techniques such as K-Means. This segmentation helps businesses target specific customer groups with more personalized marketing strategies.

Data Preprocessing: The dataset was cleaned and preprocessed by handling missing values, dropping unnecessary columns, and ensuring correct data types.

Exploratory Data Analysis (EDA): Used seaborn and matplotlib to visualize distributions and relationships in the data, including age, income, and spending scores.

Customer Segmentation: Applied the K-Means algorithm to segment customers into clusters based on their spending score and age. Visualization of Clusters: 2D and 3D visualizations were created to illustrate customer segments and their characteristics.

Python (pandas, seaborn, matplotlib)

Machine Learning (K-Means Clustering using scikit-learn)

Visualizations: Distribution plots for customer age, annual income, and spending scores. Violin plots and bar plots showcasing customer distribution based on gender, income, and age groups. Cluster visualization using 3D plots of customer spending, income, and age.

The project successfully demonstrates customer segmentation through data visualization and clustering techniques, providing insights into customer behavior that can guide targeted marketing strategies.