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@article{176215,
        author = {Varenya Gupta and Vikas Sani and Shobhit Tiwari and Priyansh Gaur and Sudhir Dawra},
        title = {Customer Segmentation using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {6215-6218},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176215},
        abstract = {Customer segmentation has become an essential strategy for businesses to enhance customer engagement, improve retention, and maximize profitability. This research delves into grouping customers from diverse organizations by analyzing behavioral traits, such as their spending habits and income levels. Behavioral segmentation proves to be a more effective method compared to other approaches, as it allows for a deeper understanding of customer preferences. Utilizing the K-means clustering algorithm, this study categorizes customers into clusters based on shared characteristics. These clusters enable organizations to craft personalized marketing strategies and targeted social media campaigns that align with individual customer interests, ultimately fostering greater engagement and driving revenue growth.},
        keywords = {Big Data, Classification, Clustering, Model},
        month = {April},
        }