Implementation of K-Means Clustering for Classification of Total Transaction and Seasonal Correlation on Online Retail Shop

Abstract

E-commerce growth has been increasing rapidly for the past few years, and it’s already become an important part for customers or retailers to sell and buy products with no bound of distances. With e-commerce having a lot of transaction data, it will be hard to make the most effective selling strategy by only using bare eyes. Thus, in this study, we adopt k-means clustering technique for clustering analysis to gain useful patterns and insights about total transaction and seasonal correlation on online retail shop dataset with the aim of giving these retail shops a more strategic sales plan. The result shows that different countries had its peak sales in different seasons, these insights can be applied for many e-commerce stores to give a deeper sales strategy to various target market.