User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering
As a large company, Amazon operates an online marketplace with a diverse user base exhibiting varied purchasing habits. This diversity challenges Amazon to provide tailored services and marketing strategies for each user with distinct characteristics. Therefore, this research aims to assist Amazon i...
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Universitas Teknologi Akba Makassar, Lembaga Penelitian dan Pengabdian Masyarakat
2023-12-01
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| Series: | Inspiration |
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| Online Access: | https://ojs.unitama.ac.id/index.php/inspiration/article/view/63 |
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| author | Al Isra Denk Rimakka Rezty Amalia Aras |
| author_facet | Al Isra Denk Rimakka Rezty Amalia Aras |
| author_sort | Al Isra Denk Rimakka |
| collection | DOAJ |
| description | As a large company, Amazon operates an online marketplace with a diverse user base exhibiting varied purchasing habits. This diversity challenges Amazon to provide tailored services and marketing strategies for each user with distinct characteristics. Therefore, this research aims to assist Amazon in segmenting its users based on their characteristics, enabling the implementation of targeted marketing strategies and service provision for each user. The study employs the K-Means Clustering method to segment Amazon platform users based on their purchasing behavior, site feature interactions, and preferences. The research process involves Knowledge Data Discovery (KDD) stages, including data processing, attribute selection, and applying the K-Means Clustering algorithm. The analysis results reveal five distinct user clusters, each with unique characteristics reflecting user behavior and preferences. These clusters depict variations in purchasing frequency, interactions with site features, and responses to product recommendations. This user segmentation provides valuable insights for Amazon to develop more focused marketing strategies, enhance personalized services, and improve overall customer satisfaction. |
| format | Article |
| id | doaj-art-5eef4f9f898a4404af6de6799ceacf1d |
| institution | Kabale University |
| issn | 2088-6705 2621-5608 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Universitas Teknologi Akba Makassar, Lembaga Penelitian dan Pengabdian Masyarakat |
| record_format | Article |
| series | Inspiration |
| spelling | doaj-art-5eef4f9f898a4404af6de6799ceacf1d2025-01-28T05:41:12ZengUniversitas Teknologi Akba Makassar, Lembaga Penelitian dan Pengabdian MasyarakatInspiration2088-67052621-56082023-12-0113210310910.35585/inspir.v13i2.6363User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means ClusteringAl Isra Denk Rimakka0Rezty Amalia Aras1Institut Teknologi dan Bisnis KallaInstitut Teknologi dan Bisnis KallaAs a large company, Amazon operates an online marketplace with a diverse user base exhibiting varied purchasing habits. This diversity challenges Amazon to provide tailored services and marketing strategies for each user with distinct characteristics. Therefore, this research aims to assist Amazon in segmenting its users based on their characteristics, enabling the implementation of targeted marketing strategies and service provision for each user. The study employs the K-Means Clustering method to segment Amazon platform users based on their purchasing behavior, site feature interactions, and preferences. The research process involves Knowledge Data Discovery (KDD) stages, including data processing, attribute selection, and applying the K-Means Clustering algorithm. The analysis results reveal five distinct user clusters, each with unique characteristics reflecting user behavior and preferences. These clusters depict variations in purchasing frequency, interactions with site features, and responses to product recommendations. This user segmentation provides valuable insights for Amazon to develop more focused marketing strategies, enhance personalized services, and improve overall customer satisfaction.https://ojs.unitama.ac.id/index.php/inspiration/article/view/63amazonk-means clusteringuser segmentationpurchasing habits |
| spellingShingle | Al Isra Denk Rimakka Rezty Amalia Aras User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering Inspiration amazon k-means clustering user segmentation purchasing habits |
| title | User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering |
| title_full | User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering |
| title_fullStr | User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering |
| title_full_unstemmed | User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering |
| title_short | User Segmentation Based on Purchasing Habits and Preferences on the Amazon Platform Using K-Means Clustering |
| title_sort | user segmentation based on purchasing habits and preferences on the amazon platform using k means clustering |
| topic | amazon k-means clustering user segmentation purchasing habits |
| url | https://ojs.unitama.ac.id/index.php/inspiration/article/view/63 |
| work_keys_str_mv | AT alisradenkrimakka usersegmentationbasedonpurchasinghabitsandpreferencesontheamazonplatformusingkmeansclustering AT reztyamaliaaras usersegmentationbasedonpurchasinghabitsandpreferencesontheamazonplatformusingkmeansclustering |