Optimization of Product Placement on E-commerce Platforms with K-Means Clustering to Improve User Experience
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Abstract
This study delves into product placement strategies on E-commerce platforms using K-Means Clustering analysis. Employing an experimental methodology, data about products and user preferences were gathered to delineate product and user clusters. The K-Means Clustering analysis yielded three primary product clusters and four user preference clusters. These findings hold significant practical implications, empowering E-commerce platforms to refine user experience personalization, streamline sales efficiency, and bolster overall business performance. Platforms can positively influence sales conversion rates and user satisfaction by implementing targeted and adaptable product placement strategies. This research contributes not only to the theoretical comprehension of product placement in E-commerce but also furnishes actionable insights for stakeholders to optimize platform operations and deliver an enriched online shopping experience.
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