In recent years, e-commerce platforms offering consumers a wide range of products and various price options have become widely used due to the convenience they provide. The widespread use of e-commerce platforms has positioned logistics companies as significant stakeholders in e-commerce, leading to the emergence of new approaches in logistics services. Both sectors, focusing on customer satisfaction, strive to develop various strategies to enhance service quality, acquire new customers, and encourage repeat purchases. A fast, reliable, and seamless delivery process directly impacts customer satisfaction and loyalty, while delivery issues can lead to customer dissatisfaction and decreased trust in the brand. In this context, consumer experiences shared on various platforms regarding the delivery process emerge as a valuable source of feedback for logistics companies to enhance customer satisfaction. On the other hand, analyzing these reviews through data-driven methods such as text mining and sentiment analysis provides crucial insights for improving the operational processes of logistics companies. In this context, the study aims to analyze customers' views regarding individual cargo companies, focusing on the shortcomings and demands in the delivery process. To this end, user reviews from a widely used online platform containing real user feedback were analyzed using sentiment analysis and machine learning methods. The findings indicate that 82% of user reviews related to cargo companies are negative, with 66% of these reviews focusing on delivery issues such as failed deliveries, delayed deliveries, and not delivered in hand. The study's findings reveal that cargo companies have not been sufficiently successful in their delivery processes and communication with customers.