Overview
To get you the most accurate and precise predictions possible, the Triumph Rates team needs to train a machine learning model using historical data from your brokerage. This is how we make sure the rates you see are tailored to your particular brokerage's buying power.
What Data to Send
We'll need a .csv or .xls file with your historical data. The easiest way to send it is by emailing the file to your customer success manager or business analyst. The more historical loads you include, the better. Two years or more of load data is ideal. The minimum number of loads we need listed is 544, with at least 32 being from the last two weeks.
Your .csv or .xls file should have the following fields:
Pick up city*
Pick up state*
Pick up zip
Drop off city*
Drop off state*
Drop off zip
Mileage
Equipment type*
Actual buy rate (Linehaul + Fuel)*
Weight
Booked date + time*
Pickup date + time*
Covered date + time*
Commodity description
*- mandatory field
How to Send Data
Historical Data
You can send your historical data to Triumph in a number of different ways:
Email it to your customer success manager or business analyst.
Send it using STFP file transfer
Through your API
Through your Customer Success Manager via manual upload
By custom integration
Continuous Data
Once Triumph has your initial historical data, you can transfer future data through an API, SFTP, or TMS integration.
Maintaining an accurate model requires a steady flow of data, so if the above options are not available, you'll need to send regular updates through email. Make sure your business analyst knows the email address that you're using to send files so they can lock in the automatic upload process. Send an update once a week at minimum, ahead of a 30-day rolling look-back, to import_load@greenscreens.ai
Data Flow
