International Journal of Engineering Continuity
Vol. 3 No. 2 (2024): ijec

Revealing Consumer Preferences in the Fashion Industry Using K-Means Clustering

Feri Sulianta (Universitas Widyatama)
Khaerani Ulfah (Universitas Widyatama)
Endang Amalia (Universitas Widyatama)

Article Info

Publish Date
15 Aug 2024

Abstract

The fashion industry, driven by rapidly shifting e-commerce trends and consumer preferences, demands precise data analysis to optimize marketing strategies and enhance customer satisfaction. This study utilizes data mining techniques, specifically K-Means Clustering and the Elbow Method, to reveal consumer preferences within a dataset of 1,000 fashion product sales records, which include attributes such as product ID, name, brand, category, price, rating, color, and size. By grouping data into distinct clusters based on price and rating preferences, the analysis uncovers four key consumer segments. The optimal number of clusters is confirmed using the WCSS (Within-Cluster Sum of Square) method. These insights offer valuable guidance for refining marketing strategies in the fashion industry. Future research should consider additional variables and employ advanced tools for deeper analysis.

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Journal Info
International Journal of Engineering Continuity
Website

Abbrev

ijec

Publisher

Sultan Publisher

Subject

Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering

Description

The International Journal of Engineering Continuity is peer-reviewed, open access, and published twice a year online with coverage covering engineering and technology. It aims to promote novelty and contribution followed by the theory and practice of technology and engineering. The expansion of ...