One of the largest obstacles procurement teams face is spot freight. With tender rejection rates increasing in an unpredictable market, spot freight is more frequent - and certainly more costly - than ever before. All too often, procurement teams are left with little time to secure spot capacity and are reliant on antiquated bid systems to cover freight and meet transportation schedules. This leaves little time for rate negotiation and generally results in inflated spot freight spend.
Machine learning and behavioral-science technologies are paving the way to a better, more efficient path to spot rate procurement. This technology delivers a robust carrier profiling system to match available spot freight to the best-suited carriers, at the best rate, based on historical data and engagement metrics. This article explores how carrier profiling works and how it improves spot freight tender acceptance rates and builds a more engaged carrier network.
What is Carrier Profiling?
Carrier profiling involves understanding how a carrier’s interests intersect with available loads, with the goal of predicting the likelihood of a carrier accepting a particular load at a certain rate. This is accomplished through an application of behavioral and data-science to determine the needs and decision-making patterns of each carrier.
Consider the way consumer applications operate. They rely on algorithms that learn through users’ behaviors, the frequency of searches, clicks, and visits to a page, and amount of time spent in evaluating a product before purchase. Over time, these applications create a profile of each user based on their likes and preferences, and personalize the user experience with suggestions that drive engagement. The platforms are designed to present a relevant and attractive experience for each individual user, streamlined for decision-making.
TNX’s carrier profiling utilizes machine learning in a similar way to drive attractive offers to carriers with capacity for available loads. Profiling is based on a combination of historical data and real-time behavioral inputs to determine what loads are relevant for each carrier at a given time. This results in increased engagement from carriers, and faster, and more effective spot pricing and tendering for the buyer.
Limitations of Traditional Spot Freight Negotiation
Traditional spot freight negotiations take place between two parties – procurement teams and their sources of capacity. Procurement teams may consist of either a planner at a large shipper or a brokerage representative. Planners handle any freight that falls out of contract while attempting to secure carrier capacity at the lowest possible rate. Brokerage reps are responsible for covering committed loads while preserving a certain margin to keep the brokerage profitable. Both planners and brokers rely on historical rate data and their current market knowledge to dictate rate negotiations with carriers, but these are often subjective and prone to bias, therefore not reliable tools for successful negotiation.
The negotiation model itself is rooted in traditional, human elements. People skills, interpersonal relationships, and negotiation tactics all factor into the end result, which creates high variability and little predictability in the outcome. This is further exacerbated by the time constraints of spot freight - procurement teams often have little time to source capacity and often take shortcuts to keep freight moving.
Modern toolsets evolved in an attempt to bridge the gap between planner and capacity sources, but unfortunately, these also fall short. These solutions largely focus on the collection of spot freights bids, which allows procurement teams to receive bids from a wider range of carriers in a short time window. This is certainly helpful for time-management, but loses the human element of playing against another party and negotiating for better rates.
In short, planners and freight brokers have two options. Either rely on humans for more sophisticated negotiations, at the expense of speed and cost analysis, or default to automated auction tools for speed and scale, without the ability to negotiate and optimize. Carrier profiling, however, combines automation and negotiation to create smart tendering and provides the benefits of speed, scale, and cost management.
Beyond Negotiation: Carrier Profiling & Smart Tendering
Carrier profiling is critical to smart tendering, which determines if and when to notify carriers about new loads and what price to offer. While all the data relevant for carrier profiling and smart tendering is available to procurement teams, most don’t have the structures in place to collect and organize it. Additionally, planners likely lack the time or ability to extract and analyze it at a meaningful level. Advanced analytics is the crucial component for turning raw data into actionable insights and automating the tendering process.
TNX Logistics’ software approaches carrier profiling using two AI methodologies. The first is Statistical AI, or machine learning, which is based on a large volume of historical and current data, as well as future predictions, to identify patterns of importance. These patterns are used to predict key outcomes - in the case of spot freight, the outcome of a carrier accepting a load at a given rate. The more data Statistical AI has, the more accurate the predictions. The second methodology is Symbolic AI, which attempts to analyze and describe the current state of the world and the available actions to act as a rational agent to achieve a given goal, like spot freight tender acceptance. These AI methods work in tandem to power a smart, AI-driven negotiator that can secure the best possible spot freight rate at speed.
Carrier profiling helps to ensure the best spot freight outcomes for procurement teams, but it is advantageous for carriers as well. Customized offers and notification schedules minimize the need for carriers to scroll endlessly on load boards for potential matches. It also takes the guesswork out of pricing and eliminates the uncertainty and waiting time of bid systems. In a market context where teams are seeing carrier participation rates dropping, a more concise and streamlined experience is crucial to engagement.
Improving Spot Freight Tender Acceptance Rates through Carrier Profiling
Carrier profiles built by advanced machine learning and behavioral science-based technology will dramatically transform spot rate procurement. Shippers that make the shift to automated profiling and smart tendering are assured the best possible outcome for spot freight, and can opt out of traditional negotiation and biased decision-making. Procurement teams can take back the time spent on manual tendering and improve productivity, while achieving consistent transportation cost savings. Carrier networks will become more robust and engaged through customized offers, speeding up tender acceptance rates and streamlining efficiencies.
Carrier profiling is the cornerstone of the TNX platform. Our software learns how carriers make pricing decisions and automates smart tendering driven by AI data insights, creating a straightforward solution for spot procurement. Schedule a demo today to learn more.