Tripti Tiwari

Papers

Total Citations

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About

Tripti Tiwari is a researcher at the forefront of applying data mining and machine learning techniques to e-commerce and customer analytics. Her work focuses on developing intelligent systems for product comparison and customer data classification, addressing the critical challenge of extracting actionable insights from vast commercial datasets. In her most-cited paper, "E-Commerce product comparison portal for classification of customer data based on data mining" (2021), Tiwari introduces a framework that leverages data mining algorithms to categorize user behavior and product attributes, enabling more personalized and efficient online shopping experiences. This foundational study has garnered 12 citations, reflecting its relevance to both academia and industry practitioners seeking to bridge the gap between raw transactional data and strategic decision-making. Tiwari’s contributions are particularly notable for their practical orientation, offering scalable solutions for real-world e-commerce platforms. Her work not only advances the theoretical understanding of customer segmentation but also provides a blueprint for building smarter, user-centric digital marketplaces. As the e-commerce sector continues to grow, Tiwari’s research remains a valuable resource for students and professionals aiming to harness data-driven approaches for competitive advantage.