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@article{193830,
        author = {Pradeep Kumar S and Aadhithya K and Solomon Samuel},
        title = {SMARTSEG: AN INTELLIGENT CUSTOMER SEGMENTATION SYSTEM USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {5290-5294},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193830},
        abstract = {Customer segmentation is an important process in modern marketing analytics, which is used by businesses to understand customer behavior and to create targeted marketing strategies. Traditional segmentation methods also tend to rely on manual analysis and basic segmentation based on demographic characteristics, which might not be able to identify complex behavioral patterns. This research proposes SmartSeg, which is a web-based intelligent customer segmentation system that uses machine learning clustering techniques to automatically analyze customer datasets and generate meaningful customer groups.
The system enables the user to upload customer datasets and performs automated preprocessing, feature engineering, clustering and visualization. Multiple clustering algorithms like K-Means, DBSCAN and Hierarchical Clustering are implemented and analyzed using several parameters like Silhouette Score, WCSS to find the best segmentation strategy. The platform also does provide explainable insights using cluster centroid analysis and natural language explanations.
The system architecture is based on the 3-tier architecture, which includes React frontend, FastAPI backend, and machine learning engine using Scikit-Learn. Interactive visualizations are created from Plotly and segmentation reports can be exported to CSV or PDF format.
The solution proposed here helps businesses to discover meaningful customer segments easily i.e., champions, loyal customers, and at-risk customers for data-driven marketing strategies.},
        keywords = {},
        month = {March},
        }