Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering
Abstract
Technological developments have transformed traditional buying and selling practices into online transactions. Amazon, as one of the largest e-commerce platforms, continues to innovate to maintain its competitive advantage, offering a variety of products and services. This research uses the K-Means Clustering method to identify Amazon's customer segmentation and devise more effective marketing strategies. The analysis results show three main clusters: Price-Sensitive Browsers, Review-Driven Shoppers, and Quality Seekers. Cluster 2, which accounts for 47.49% of the total sample, is the most potential. Consumers in this cluster shop weekly, want better prices, pay attention to product reviews, and care about eco-friendly packaging. The right target segment for Amazon is women aged 24-26 who regularly shop weekly and care about environmental sustainability. By understanding consumer needs and preferences, Amazon can develop more effective marketing strategies, increase customer satisfaction and loyalty, and maintain its competitive advantage.
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