AI \ Case Study \ AI-Powered Price Predictions in Transportation Logistics

Client Summary

The client is a Fortune 500 transportation and logistics company with a vast fleet of tens of thousands of trailers and containers that facilitate millions of annual deliveries. The client approached us to help them predict accurate market prices using AI and ML solutions that would allow them to negotiate better in the spot market broking business, resulting in optimal margins and increased profitability.

Challenges Faced by the Client:

The client often encountered challenges such as over-paying carriers or losing business from shippers due to inaccurate predictions of the market price. The client's existing market price prediction model suffered from high error rates, which affected their bid-win rate and margins. Therefore, the client sought to predict the optimal market price that paid the carriers the right cost and won the load from the shipper with an optimal margin.


Our objective was to develop an AI/ML solution that could predict the market price with an accuracy rate of over 90%, helping the client arrive at the best carrier cost and shipper price, leading to optimal margins. The client also aimed to increase the bid-win rate from 1% and to procure better carrier costs, considering lane and load attributes, while offering better shipping prices to boost gross margins per employee.


Futurism developed a novel dynamic pricing model powered by AI/ML to help predict the market price that gave maximum margin using cognition and hyper-automation. We utilized an advanced ensemble-based machine learning approach with multiple models implemented across lanes and considered relevant features. We leveraged the power of AI to reduce manual effort and time consumed in determining the market price. The solution was hosted on cloud, and the entire pipeline was automated, from extracting data from legacy systems, data quality, transformation and loading, feature engineering, modeling, to integrating with the consuming systems.


Futurism's solution predicted the carrier cost with an accuracy greater than 90%, leading to the following benefits:

  • $19M annual savings with a 12% increase in prediction accuracy
  • Bid-win rate increased from 1% to 3%
  • Increased Gross Margin per Employee per Day (GMED) from $200 to $900 using cognition and hyper-automation


By using AI/ML-driven price prediction, the transportation and logistics leader could negotiate better in the spot market broking business, leading to optimal margins, and increased profitability. The accuracy of market price prediction, bid-win rate, and GMED improved significantly, leading to millions of dollars in annual savings.


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