A strong seller’s market in 2017 and 2018 led to dramatically increased costs in transportation due to demand surpassing supply, government regulations, and a shortage of truck drivers. As a result, the carrier rejection rate by primary carriers in the routing guide increased. This research examines the performance of routing guides to segment freight to help shippers identify and characterize where and how budget overruns occur. Using data characterization and regression modeling, we examine the plan data (carrier/lane/volume) and analyze how the transactions performed against it. We analyze one year’s worth of shipper data from March 2019, when the plan was made, to March 2020 for three shipper sizes. We classify how lanes perform relative to the planned budget to determine the underlying factors that contribute to budget overruns by creating a freight categorization framework. A linear regression model was built to quantify the impact of independent variables such as distance, lane volume, origin/destination, and lane freight types (dry/refrigerated/frozen) on spend, volume, and total cost contribution to deviations from planned budget. The research found that frozen lane freight loads contribute to higher budget deviations, while dry van loads tend to contribute to lower budget deviations. Furthermore, specific origins and destinations impact budget deviations depending on the shipper. While volume deviations contribute to budget overruns more than price deviations. Finally, we provide insights to determine better segmentation strategies for procurement and management of transportation bids in the future.