• ITVI.USA
    13,924.900
    3.330
    0%
  • OTRI.USA
    22.080
    -0.170
    -0.8%
  • OTVI.USA
    13,904.220
    5.970
    0%
  • TLT.USA
    2.650
    0.000
    0%
  • TSTOPVRPM.ATLPHL
    2.480
    0.060
    2.5%
  • TSTOPVRPM.CHIATL
    2.190
    0.050
    2.3%
  • TSTOPVRPM.DALLAX
    1.400
    0.180
    14.8%
  • TSTOPVRPM.LAXDAL
    2.730
    0.160
    6.2%
  • TSTOPVRPM.PHLCHI
    1.440
    0.040
    2.9%
  • TSTOPVRPM.LAXSEA
    2.870
    -0.010
    -0.3%
  • WAIT.USA
    108.000
    5.000
    4.9%
  • ITVI.USA
    13,924.900
    3.330
    0%
  • OTRI.USA
    22.080
    -0.170
    -0.8%
  • OTVI.USA
    13,904.220
    5.970
    0%
  • TLT.USA
    2.650
    0.000
    0%
  • TSTOPVRPM.ATLPHL
    2.480
    0.060
    2.5%
  • TSTOPVRPM.CHIATL
    2.190
    0.050
    2.3%
  • TSTOPVRPM.DALLAX
    1.400
    0.180
    14.8%
  • TSTOPVRPM.LAXDAL
    2.730
    0.160
    6.2%
  • TSTOPVRPM.PHLCHI
    1.440
    0.040
    2.9%
  • TSTOPVRPM.LAXSEA
    2.870
    -0.010
    -0.3%
  • WAIT.USA
    108.000
    5.000
    4.9%
Inside SONARInsightsNews

This week in SONAR: API upgrade allows subscribers to digest rates into their own workflows

In FreightWaves’ ongoing effort to bring more transparency and clarity to domestic and global freight markets, the FreightWaves SONAR platform is adding an API upgrade allowing subscribers to digest rates directly into their own unique workflows.

SONAR is the only product that combines near-time tender data from 85% of the contract market with historical spot market data to provide forecasted trucking spot rates.

API rates

For the first time, API subscribers have the ability to extract rate data through the existing API portal. Daily dry van rates are available from zip3 to zip3 regions (zip3 is the first 3 numbers in a zip code). These rates are determined by machine learning, historic trends, and real-time tender data.

What are FreightWaves SONAR predictive rates? 

One of the biggest challenges facing carriers is pricing optimization for any given load or lane to ensure profitability. Rather than relying on intuition or tribal knowledge, FreightWaves’ data science team has just released the 2.0 version of its API for predictive rates. This updated API builds on the prior release by incorporating more real-world variables and enhanced functionality to improve precision.

At its core, an API allows a user or a device to send a request to a database, and then based on relevant scientific variables, to receive an intelligent, helpful response to the query. In this case, with FreightWaves’ new predictive rate tool, the basic idea is to take a given lane (with defined origin and destination) and use algorithms that incorporate many relevant fundamental variables to estimate the cost of hauling that load, before ultimately arriving at what rate per mile to charge to ensure a profit. After all input variables are considered and calculated, the API then arrives at a band of optimal rates per mile for a carrier to charge a shipper to make sure the load is both profitable (over and above operating cost per mile) and within reasonable range of the operating ratio target.

Input variables into the new API designed to improve precision include national operating ratio (OR) and volume/rejection trends; normalized haul scores, relative rejection rates and “freight potential” scores based on the specific origin and destination; expenses, distance/duration and toll mileage at the lane level; and, lastly, even the particular day of week is considered for price optimization.

The base or target operating ratio for the particular lane in question is based on monthly anonymized benchmark data and interpolated to a daily frequency. The origin and destination variables take into account headhaul and backhaul market pricing considerations. In addition, the origin rejection rates are overweighted in the model because if rejections out of the origin are higher than the three-month average, then it is logical to assume that carriers will expect more profitable loads and vice versa. “Freight potential” indicates the probability of picking up a load in all surrounding markets within 7 hours of the stated market, with the idea being a load is more attractive when surrounded by more attractive freight potential. 

Without going into too much depth or technical detail, these are just a few relevant examples of the type of data now being incorporated into the new SONAR predictive rates tool.

The end goal is that, after inputting origin and destination data and taking into account the adjusted operating ratio target, lane expenses and other fundamental variables, the API then returns a range of plausible rates for a given lane. 

FreightWaves believes that this tool will help carriers become significantly more efficient and profitable in their pricing decisions and we believe our new predictive rates API is a cutting edge, unique tool that can potentially help carriers achieve this objective.

Parameters required:

  • OD Pair: 374-704
  • Start Date: 2020-03-31
  • End Date: 2020-04-06

Returned parameters:

  • Time Stamp
  • OD Pair
  • High Rate
  • Medium Rate
  • Low Rate
  • Lane Confidence
  • Region
  • Cities
  • Mode

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One Comment

  1. Are these rates better than DAT rate view and Truckstop rate mate rates? We use both for our rating. Although it’s interesting that DAT and Truckstop rates are so different for almost every lane. Why???? If their rates are meant to be as accurate as they say wouldn’t they be within pennies of each other??? Weird.

    THe sonar software is just way to expensive for us tho. i’m sure Swift and JB Hunt can afford thousands a month but we can’t lol. We pay less than $100 for DAT and Truckstop rates COMBINED. I just wish I was confident that one of them was accurate.

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