Customer-Clustering-for-Smartphone-Brands-using-Machine-Learning-

🔗 PROJECT LINKS

• 💻 Notebook - Explore the project

Note

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Introduction

This project uses K-Means and Agglomerative Clustering techniques to segment smartphone users based on their preferences and usage patterns.

Goal

The primary goal is to identify distinct customer segments using clustering techniques, providing insights for improving customer engagement and marketing strategies.

Key Highlights

• Applied clustering techniques like K-Means and Agglomerative Clustering to segment customers based on usage patterns and preferences.
• Conducted EDA and feature engineering to identify key customer groups, providing actionable insights for targeted marketing strategies.
• Built clusters to help optimize customer segmentation and improve business decision-making.