Market segmentation analysis to find out products and services that suit customer needs using the python KMEANS clustering method  (Case study: Superindo Tambun Area, Bekasi)

Rizqy Gumilar  Praditya; Giri  Sembodo; Jerry  Heikal

doi:10.31004/jutin.v7i4.35889

Authors

Rizqy Gumilar Praditya Unversitas Bakrie
Giri Sembodo Universitas Bakrie
Jerry Heikal Universitas Bakrie

DOI:

https://doi.org/10.31004/jutin.v7i4.35889

Keywords:

market segmentation, k-mean clustering, phyton, superindo, online value proposition

Abstract

This study analyzes market segmentation of 1000 Superindo consumers in Tambun, Bekasi, using K-Means Clustering with Python 3.10. Variables included age, gender, occupation, purchase amount, product type, and discounts. Three main segments were identified: "Business Women" (average age 40, focus on staple goods, 16% discount), "Women Government Career" (age 39, staple goods, 16% discount), and "Professional Women" (age 38, staple goods, 15% discount). Superindo should target "Women Government Career" with the highest purchasing power. To increase sales, an online value proposition is recommended offering bundled packages of staple goods with meat and fruit.

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