Enhancing Sales Success in B2B Negotiations Using the C4.5 Decision Tree Algorithm

Sales performance is a critical determinant of a company’s profitability and overall success, especially in competitive industries where data analysis is crucial for optimizing sales strategies. PT XYZ, operating in the medical equipment industry under a business-to-business model, relies heavily on negotiations involving price, shipping costs, project completion time, and product quantity. However, more research is needed to identify systematic patterns in the negotiation process and their impact on sales outcomes in this sector. To address this gap, this study leverages the power of the C4.5 Data Mining classification algorithm to analyze negotiation processes at PT XYZ, focusing on generating and evaluating rules from decision trees. Data from 1604 sales records between 2021 and 2022 were used, with $75 \%$ allocated for training and $25 \%$ for testing. The C4.5 Decision Tree classification model identified price as the most significant factor in the negotiation process, with the model achieving an accuracy score of $74 \%$, as evaluated by the Confusion Matrix. This robust algorithm gives us a high confidence level in our findings. The potential for significant improvement in sales performance through optimizing price strategies should be a source of hope for PT XYZ.