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...
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| Format: | Article |
| Language: | English |
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Universitas KH Abdul Chalim, Prodi Ekonomi Syariah
2025-07-01
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| Series: | Indonesian Interdisciplinary Journal of Sharia Economics |
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| Online Access: | https://e-journal.uac.ac.id/index.php/iijse/article/view/6176 |
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| author | Rizki Agung Ramadani Tiyanda Hanti Arum Kusuma Rinta Agustiani Dwiputri Jerry Heikal |
| author_facet | Rizki Agung Ramadani Tiyanda Hanti Arum Kusuma Rinta Agustiani Dwiputri Jerry Heikal |
| author_sort | Rizki Agung Ramadani |
| collection | DOAJ |
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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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| format | Article |
| id | doaj-art-9665ba1205f54b33bc8e1ebff0a0bc51 |
| institution | Kabale University |
| issn | 2621-606X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Universitas KH Abdul Chalim, Prodi Ekonomi Syariah |
| record_format | Article |
| series | Indonesian Interdisciplinary Journal of Sharia Economics |
| spelling | doaj-art-9665ba1205f54b33bc8e1ebff0a0bc512025-08-20T03:31:48ZengUniversitas KH Abdul Chalim, Prodi Ekonomi SyariahIndonesian Interdisciplinary Journal of Sharia Economics2621-606X2025-07-017310.31538/iijse.v7i3.6176Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means ClusteringRizki Agung Ramadani0Tiyanda Hanti Arum Kusuma1Rinta Agustiani Dwiputri2Jerry Heikal3Universitas Bakrie, Jakarta, IndonesiaUniversitas Bakrie, Jakarta, IndonesiaUniversitas Bakrie, Jakarta, IndonesiaUniversitas Bakrie, Jakarta, Indonesia 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. https://e-journal.uac.ac.id/index.php/iijse/article/view/6176AmazonE-commerceK-meansClusteringSegmentation |
| spellingShingle | Rizki Agung Ramadani Tiyanda Hanti Arum Kusuma Rinta Agustiani Dwiputri Jerry Heikal Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering Indonesian Interdisciplinary Journal of Sharia Economics Amazon E-commerce K-means Clustering Segmentation |
| title | Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering |
| title_full | Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering |
| title_fullStr | Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering |
| title_full_unstemmed | Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering |
| title_short | Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering |
| title_sort | identifying customer segmentation and persona of amazon customer an approach using k means clustering |
| topic | Amazon E-commerce K-means Clustering Segmentation |
| url | https://e-journal.uac.ac.id/index.php/iijse/article/view/6176 |
| work_keys_str_mv | AT rizkiagungramadani identifyingcustomersegmentationandpersonaofamazoncustomeranapproachusingkmeansclustering AT tiyandahantiarumkusuma identifyingcustomersegmentationandpersonaofamazoncustomeranapproachusingkmeansclustering AT rintaagustianidwiputri identifyingcustomersegmentationandpersonaofamazoncustomeranapproachusingkmeansclustering AT jerryheikal identifyingcustomersegmentationandpersonaofamazoncustomeranapproachusingkmeansclustering |