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@article{200345,
        author = {Varun Balar and Satish Gujar},
        title = {Customer Segmentation Using Data Mining Techniques for Retail Analytics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {1097-1104},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200345},
        abstract = {Customers of businesses have always provided businesses with various information, but with the rapid growth of online shopping, there is more customer-related information available. However, much of this data is not being utilized by businesses to make accurate decisions because companies are choosing to look only at total sales numbers and other relatively general metrics.
The primary focus of this paper is to utilize multiple methods of data mining to group customers according to how they purchase, and how often and what stores they visit. Each method of data mining will be evaluated in terms of its ability to successfully identify meaningful groups of customers. The outcome of this research will produce a structured methodology that will give retailers the ability to better understand their customers and design appropriate marketing plans.},
        keywords = {Customer Segmentation, Retail Analytics, Data Mining, Clustering, RFM Model, Customer Behavior},
        month = {May},
        }