K-MEANS CLUSTERING IMPLEMENTATION FOR XYZ MALL CUSTOMER SEGMENTATION AND MARKETING STRATEGY USING THE MARKETING MIX THEORY

Abstract

In today's competitive business environment, businesses require effective marketing strategies to achieve success. This research aims to determine an effective 8P marketing strategy based on clustering using the K-means algorithm. This method groups consumers into homogeneous segments based on their preferences, behaviors, and purchase characteristics. Consumer data is used as input for the K-means algorithm. The clustering results identify market segments with unique characteristics. The 8P marketing strategy is tailored to meet the needs and preferences of each segment. Product, price, placement, and promotion are adjusted according to segment preferences. Attention is also given to employees, the purchasing process, physical evidence, and packaging. The objective of this research is to develop a more targeted and effective 8P marketing strategy based on K-means clustering. It is expected that this approach will help companies optimize their marketing resources and efforts by considering differences among market segments.