• Manila Gupta
• Sidra Amjad Ali Shaikh
• Sagarika Shekhar Srivastava
• Sidra Sameer Solkar
• Ansari Bushra Zahiruddin

Customer segmentation is a fundamental strategy in contemporary marketing that enables organizations to classify customers into distinct groups for targeted engagement and improved decision-making. This research presents an AI-driven customer segmentation framework that integrates machine learning with intelligent automation to analyze behavioral patterns and generate actionable business insights. The proposed system employs the K-Means clustering algorithm to identify meaningful customer segments based on behavioral and transactional attributes, while the Elbow Method and Silhouette Coefficient are used to determine the optimal number of clusters. An AI module powered by gpt-4o-mini is integrated to automatically interpret cluster results, generate natural-language insights, and produce downloadable summary reports for businesses. The combination of clustering, visualization, and AI interpretation produces a comprehensive analytical system that supports personalized marketing, customer retention, and overall business growth.

Customer Segmentation, Artificial Intelligence, K-Means, Clustering, Machine Learning, Marketing Analytics, GPT-based Analysis.

"AI-Driven Customer Segmentation Using Clustering Techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 10, page no.d5-d7, October-2025, Available :http://www.jetir.org/papers/JETIR2510302.pdf

"AI-Driven Customer Segmentation Using Clustering Techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 10, page no. ppd5-d7, October-2025, Available at : http://www.jetir.org/papers/JETIR2510302.pdf