Maximizing Strategy Improvement in Mall Customer Segmentation using K-means Clustering

The application of customer segmentation is very vital in the world marketing, a manager determining marketing strategy, knowing target must, otherwise it will potentially waste resources to pursue wrong target. Customer aims create relationship with most profitable customers by designing appropriate strategy. Many statistical techniques have been applied segment market but large data are influential reducing their effectiveness. aim clustering optimize experimental similarity within cluster and maximize dissimilarity between clusters. In this study, we use K-means as basis for that be carried out, course, there additional models used support research results. As result, succeeded dividing into 5 clusters based on annual income spending score, has concluded who high-income levels & high score also targets implementing strategies.