Mall Customer Segmentation
This project utilizes clustering algorithms to segment mall customers based on their purchasing behavior. The goal is to create targeted marketing strategies and provide personalized shopping experiences, thereby increasing customer satisfaction and business revenue.
Project Overview
Mall Customer Segmentation uses machine learning techniques to analyze customer data and categorize them into different segments based on their purchasing patterns. By leveraging these segments, retailers can deliver personalized marketing campaigns and enhance customer engagement.
Key Features
- Segmentation of mall customers based on shopping behavior
- Data visualization to showcase customer groups
- Targeted marketing strategy for each segment
- Improved customer retention and business revenue
Technologies Used
- Python
- Machine Learning (KMeans Clustering)
- Data Visualization (Matplotlib, Seaborn)
- Data Analysis and Segmentation