Introducing dexRate V1.0 — Machine Learning Powered Shipment Rate Estimation and Forecasting Tool for Brokers and Carriers
By the Data Science Team at dexFreight Inc.
Summary
In this blog post, we present dexRate, a novel tool developed by dexFreight for brokers and carriers to estimate and forecast full truckload freight rates in the spot market. The tool uses multiple data sources and machine learning algorithms (e.g., clustering, time series analysis) to estimate and forecast rates for a given origin, destination, and equipment type. Using dexRate, brokers and carriers can discover freight rates in new lanes, understand rate fluctuations, compare rates with peers in the market. We analyzed the rates suggested by the tool to the rates used by two freight brokers. As described below, we estimated return on investment (ROI) would have been 50% and 165% for two freight brokers if they had used dexRate.
Estimating Freight Rates is Tricky
For brokers/carriers, accurately pricing freight rate of shipments in the spot market involves knowledge of the lane they are moving, market trends, rate details, company’s target margin etc. Knowing all these variables and putting them together to make sense of shipment’s freight rate is not easy. Owner-operators, dispatchers, and the sales team, who typically work on those, use multiple systems, emails, and phones to estimate the right freight rate for a particular load and lane.
Introducing dexRate V1.0
dexRate is a Machine Learning-powered tool that makes it easy for the users to instantly discover the freight rate of shipments for a given lane, equipment type, weight, and other factors. The dexRate engine is neutral in the sense that it is not designed to favor one side of the supply and demand. The underlying data may at times be biased depending on where and how much data the engine receives.
dexRate determines suggested rates based on market indicators that consist of offered and invoice data provided by our users as well as third-party data providers. If the shipments are a few days out, then it provides forecasted rates. We do not forecast the rates beyond 5 days out because the spot rates are so volatile that the models cannot accurately capture such volatility beyond 5 days ahead. dexRate allows users to measure the short and long term performance of their pricing strategies.
Benefits and Value Propositions
There are obvious benefits to faster rate discovery. Some benefits are subjective and others are quantitative. We analyzed two freight brokers and compared their past shipment rates and revenue. We compared their rate to carriers with dexRate suggested rate. We are performing similar tests with carriers. These benefits are described below:
Benefit- 1: Eliminate Shipments with Negative Margins
Freight Broker A (<$100 Million per year top-line revenue) that operates largely in the spot truckload market was chosen for this study. They provided us with individual revenue from shipper and carrier rates for over 7000 shipments. The broker typically negotiates the shipment rates with the shippers and then goes on and hires carriers. There are obvious pros and cons to this practice. Nonetheless, we found that they had 4.6% of shipments with negative margins. After we ran our rate forecasting model on their shipments, we found that the overall profit margin would have increased from 14.0% to 14.9% by reducing negative margin shipments. With $200/month/seat licensing cost (may vary) and 3 licenses per month, their return on investment for the year would have been 165%.
Benefit — 2: Reduce Negative Portfolio Returns
We also analyzed the broker’s annual return using the Sortino Ratio, a common indicator used in algorithmic trading and hedge funds to assess the performance of various portfolios and investment strategies. The higher the ratio, the better it indicates risk-adjusted return in the portfolio. Obviously, we are not trying to compare broker operations with algorithmic trading. However, Sortino Ratio is sensitive to the impact of negative profit and the standard deviation of those returns. Using 10% as a desirable profit margin, we estimated the Sortino Ratio before and after (theoretic) using dexRate. The Sortino ratio jumped by over 30% from negative to positive territory indicating positive overall returns by using dexRate.
Benefit — 4: Reduce Lead Times to Quote Customers
We also worked with Broker B, a small freight broker (< $10 Million per year top-line revenue.) Their practice is different from the first broker. Broker B will receive shipment orders from customers, obtain bids from multiple carriers for those orders, and choose bids that best fit their rate as well as carrier’s reputation and performance. An obvious downside to this practice is that they have to wait for carriers to respond to their bids. By that time, if shippers are in a hurry then they may assign loads to another broker. dexRate provides users with an opportunity to quickly quote a rate to their customers without waiting to receive bids from carriers (a lot of those bids happen over the phone) and confidently hedge against rate risks.
Benefit — 4: Find Rates in New Markets
If you are entering a new market or bidding on new lanes, then dexRate is a perfect tool for users. One of the difficulties of entering a new market is quoting the rate with high confidence in the absence of adequate historic information. With dexRate , users can look at historic trends of rates in those markets, and then quote a rate. dexRate provides an algorithmic confidence level in the form of relative market position of the rate compared to the peers.
Benefit — 5: Use Rates with Confidence
Brokers and carriers can either use the rates suggested by dexFreight or modify it according to their individual needs. When modified, the algorithm compares the modified rates with rates currently available in the market. This allows the users to be lower or increase their rates to be aggressive or conservative against the market trends.
Customize Rates for Carriers
For carriers, total rates can be customized on a per shipment basis before sending bids to a shipment. Users can disaggregate the rate into a number of variables such as fuel, wages, benefits, insurance, tolls, profit margin, etc.
Integration with TMS and FMS
Transportation Management Systems (TMS) and Fleet Management Systems (FMS) can request suggested and forecast rates via our open API. The request can be a single o-d or batch thousands of o-d lanes and equipment types. For recurring API pulls, we will charge on the basis number of API pulls.
In Conclusion
dexRate is unique among other rate discovery tools in the market because of the fact that it can estimate the probability of rate acceptance by comparing it with market sentiment and also perform short term price forecasting using machine learning algorithms that constantly learn as new data enters the model. The blog post clearly demonstrated ROI for brokers. We will continue to analyze the ROI for carriers of different sizes. dexRate is also a strategic tool within the platform, as it is a building block to future tools we are building including revenue-based optimization algorithms for carriers.
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Please click here for a free demo. Feel free to send us your thoughts and comments at info@dexfreight.io.
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