Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Rizki Agung Ramadani, Tiyanda Hanti Arum Kusuma, Rinta Agustiani Dwiputri, Jerry Heikal
Format: Article
Language:English
Published: Universitas KH Abdul Chalim, Prodi Ekonomi Syariah 2025-07-01
Series:Indonesian Interdisciplinary Journal of Sharia Economics
Subjects:
Online Access:https://e-journal.uac.ac.id/index.php/iijse/article/view/6176
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2621-606X