This report uses unsupervised learning to identify order experience clusters in the Olist marketplace. The clusters are created from delivery, freight, order complexity, payment, and customer geography variables. Review outcomes are deliberately excluded from clustering and are used only after clustering to understand how each experience profile relates to customer satisfaction. The analysis answers a practical customer satisfaction question: which types of order experiences look risky or positive even when customers do not leave a review?