Customer Analytics | AI in Marketing
AI-Driven Consumer Segmentation Studio — Behavioral & RFM Analytics
This project demonstrates how machine learning (K-Means clustering) can be combined with behavioral metrics to analyze shopping patterns — transforming raw transactional data into actionable insights through feature engineering, clustering, and visualization.
My Role
Data & Research Analyst
Duration
2 months
Tools
SQL, Python, Streamlit, Pandas, Scikit-learn, Plotly
Link
Overview
Businesses struggle to translate large volumes of transactional data into meaningful customer insights. Manual segmentation is slow, error-prone, and fails to uncover behavioral patterns needed for personalization and retention campaigns.
Developed an AI-driven web app that automates customer segmentation through K-Means clustering on RFM and behavioral features. The app provides an interactive dashboard to visualize clusters in 2D and 3D, understand spending behavior, and export segmented customer data for targeted marketing use.
Research
Explored e-commerce datasets to study how purchase frequency, recency, and monetary value correlate with loyalty. Behavioral analysis revealed that:
Customers with high frequency and monetary scores drive repeat purchases.
High discount dependency leads to low retention.
Broader category diversity correlates with stronger brand loyalty.
These findings informed feature selection for the ML model.
Design
Built using Streamlit for its interactive UI and ease of deployment.
Integrated Plotly visualizations for 2D/3D scatter plots, radar charts, and behavioral KPIs.
Added modular navigation: Overview, Clusters, Recommendations, and Downloads.
Results
Delivered four actionable customer segments from raw retail data.
Reduced segmentation time from hours to minutes via automation.
Simplified marketing strategy creation with built-in recommendations.
Deployed on Streamlit Cloud for live demo access and recruiter interactivity.
🌟 Takeaway
Bridging machine learning with marketing analytics — transforming raw customer data into intelligent, visual, and actionable insights that drive smarter engagement decisions.
