| Mode-Specific Weighted Rejection Index | |
| We’ve enhanced our existing Weighted Rejection Index (WRI) with a more precise, mode-specific view powered by our updated tender dataset. The SONAR Weighted Rejection Index (SWRI) measures weekly changes in tender rejection rates, weighted by market share, helping you quickly identify where capacity is tightening or loosening in the markets that matter most.
Why it matters
SWRI helps you cut through the noise and act faster by showing where market changes actually matter most. | |
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| Load Balance Index (LBI) | |
| Understanding freight imbalance is critical to anticipating pricing power and capacity risk. LBI transforms traditional headhaul analysis into a normalized, percentage-based metric, allowing you to compare markets directly without adjusting for size. By scaling outbound versus inbound activity against total market volume, LBI provides a clearer, more strategic view of directional pressure and helps quickly identify where pricing power or coverage risk may be building:
The Load Balance Index adds a sharper layer of network intelligence helping you move beyond volume tracking and into actionable market positioning. It is currently available in the below granularities:
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| Average Tender Market Share | |
We are expanding market visibility with the launch of Average Tender Market Share (ATMS) and its mode-specific companions:
Average Tender Market Share measures how much of the total network’s tender activity is concentrated within a specific market. This helps you move beyond volume tracking and highlights meaningful directional movement, making it easier to:
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| Truckload Intermodal Spot Rate Spread (TLIMS) | |
| The Truckload Intermodal Spot Rate Spread (TLIMS) helps users quickly understand the cost relationship between truckload and intermodal freight. It measures the difference between SONAR National Truckload Spot Rates (NTI.USA) and National Intermodal Spot Rates (INTRM.USA), providing a simple indicator of which mode holds the pricing advantage at the national level. By tracking the spread between these two rates, TLIMS makes it easier to identify when intermodal becomes a more cost-effective option compared to truckload, helping shippers evaluate modal conversion opportunities, brokers adjust pricing strategies, and carriers monitor shifts in competitive dynamics. This new dataset provides a clear signal of modal cost competitiveness, allowing SONAR users to quickly gauge how changing market conditions may influence freight routing and transportation strategy. | |
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| Estimated Diesel Cost Per Mile (MPG) | |
| This new dataset converts national and market-level diesel fuel prices into a cost-per-mile metric, giving you a clearer picture of how fuel costs directly impact trucking operations. Calculated as Diesel Truck Stop Price (DTS) ÷ 7 MPG, this dataset eliminates the manual work of translating per-gallon prices into operational costs. With MPG, you can:
This dataset is relevant for carriers, brokers, shippers, market analysts, and financial teams. | |
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| Ocean Supply/Demand Enhancements | |
| We have enhanced the Lead Days metric on the Ocean Supply/Demand dashboard to provide deeper visibility into future booking trends as well as adding Seasonality mode to the charts. Previously, the TEU Booking Index displayed activity at fixed intervals of 0, 7, 14, 21, and 28 days relative to departure or arrival dates. With this update, the metric now extends visibility into the future up to 28 days, allowing users to better track how booking volumes are developing ahead of vessel movements. This improvement provides earlier signals of shifts in ocean demand, helping users anticipate capacity pressure, demand surges, or softening volumes before they materialize in the market. | |
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Together, these enhancements offer a more powerful and intuitive way to visualize market dynamics, identify opportunities, and plan with confidence.To learn more visit our Knowledge Center or contact customer success at [email protected]. |