Personalised Marketing Campaign

• Tech Stack: Python, Streamlit, Scikit-Learn, Google Gemini API
• Github URL: Project Link

Developed a web-based application to classify customers into 13 distinct clusters and generate personalized marketing strategies and email campaigns. The clustering was achieved using K-Means, yielding a silhouette score of 0.415, which indicates a well-structured grouping of customers based on their demographic and behavioral data.

The application preprocesses customer data, predicts customer segments, and provides personalized email drafts or campaign strategies to maximize ROI.