Applying data mining to analyze sales patterns of goods using the k-means algorithm method at the Erremy Shop. Availability of goods, stock of goods and completeness of goods in a shop is a very important element. So that the management process to regulate the availability of inventory is needed to avoid the accumulation of the same goods and is less desirable to customers. This research aims to determine buyer interest in a product so that we can ensure the supply and availability of products that are selling well or not selling well. The benefit of this research is to prevent product stockouts and accumulation of unsold products. The method used in product grouping uses the K-Means Clustering method so that the best-selling and less-selling products can be identified. Product data is grouped based on the similarity of the data so that data with the same value will be in one cluster. With the existence of product stock clusters with each level of stock movement owned, this allows it to be used as a reference in predicting the supply of products according to their needs. The tests carried out in this study were using black box testing.