Dynamic Pricing for Carriers. How Trucking Companies Can Remain Competitive with Smart Pricing Algorithms

Dynamic Pricing for Carriers. How Trucking Companies Can Remain Competitive with Smart Pricing Algorithms

Dorota Owczarek - October 28, 2022

As a transportation company, you face stiff competition from other trucking firms. You need to find ways to remain competitive, and dynamic pricing can help. With dynamic pricing algorithms, you can set flexible prices that adapt to the current market conditions. This will help you stay ahead of the competition and increase your profits.

In this article, we will discuss how dynamic pricing algorithms help carriers by optimizing prices, reducing customer churn, and making it easier to compete within the transportation services sector.

Dynamic Pricing Model - What Is It?

A dynamic pricing model is a tool that helps companies set prices based on real-time market conditions. It takes into account supply and demand, competitor prices, customer churn, and other factors to determine the optimal price for a product or service.

Static pricing (with single price point) vs. dynamic pricing (with multiple price points)

Static pricing (with single price point) vs. dynamic pricing (with multiple price points)

Dynamically Adjust Pricing Based on Market Demand

Dynamic pricing enables you to adjust your prices in real time based on current market demands. If demand is high, you can raise your prices to maximize profits. If demand is low, you can lower your rates to increase sales.

By constantly monitoring market conditions, you can ensure that you are always charging the optimal price for your services. This will help you stay ahead of the competition and increase your profits.

How Can Fleet Owners Apply Dynamic Pricing Models?

FTL and LTL carriers can use dynamic pricing models to optimize their prices and stay competitive. Here are a couple of angles that mature pricing models take into account:

Advanced Lane Analytics

One way to dynamic pricing is to use advanced lane analytics. This technology uses real-time network monitoring (from TMS and the system for tracking orders) and predictive analytics to track traffic patterns. By analyzing historical data, predictive analytics can identify trends and patterns that will help you forecast future demand. Machine learning models can estimate the probability of loading in a given location and therefore adjust the pricing for shipping quotes that end in that zip code. On the other hand, if you know that a lane is underutilized, you can lower your prices to attract more business. This information can be used to optimize your prices and ensure that you are always charging the optimal rate.

Shippers Segmentation

Not every shipper is willing to pay the same. You need to segment your customers based on their willingness to pay and price accordingly. Negotiation trends are also something to look at. Some transportation companies use dynamic pricing models to segment their customers and charge different prices based on their willingness to pay. For example, a carrier might charge a higher rate for a shipper that is always willing to negotiate and a lower price for a shipper that accepts the initial quote. Have you noticed which shippers or brokers will always negotiate on your offer while others take it without bidding? You need to be aware of this when preparing your dynamic pricing strategy, and machine learning models can automatically segment your customers at scale.

Dynamic LTL Pricing and Shipment Consolidation

If you’re in the LTL spot market, you need to constantly monitor market conditions and the state of your network to utilize options for shipment consolidation. Suppose you already have an order for a shipment that takes up half the truck’s space. In that case, you can immediately offer an attractive price if somebody asks for the same lane that would fit within the remaining truck capacity. Easy to execute when you’re managing a small fleet, but to approach the same problem at scale is a real challenge for LTL carriers, that’s where AI-based models for shipments consolidation that power a dynamic LTL pricing strategy come in. By automatically monitoring your network state and identifying opportunities for freight consolidation, you can utilize your assets and excess capacity more efficiently and make additional profit.

Features of a dynamic pricing model for LTL transportation

Features of a dynamic pricing model for LTL transportation

Related case study: Delivering a dedicated IT system to manage and sell freight deals and plan transportation

A major logistics company approached us to create a dedicated IT system to handle their core business process – managing and selling logistics deals.

Our challenge? The key challenge in the freight forwarding sector is cutting the time of concluding deals to an absolute minimum. The tool has to be very responsive and help in the smart matching of carriers and freight, fleet management, and other logistics operations. The platform helps shipping agents minimize fuel consumption, maximize operational efficiency, and optimize fleet performance by matching multiple loadings on a similar route with a single carrier. Read more about this case study.

Offer Competitive Prices to Reduce Empty Miles

Similarly, it would be best if you offered competitive rates to shippers to fill your trucks and reduce empty miles on unpopular lanes. Again, dynamic pricing can help you can automatically adjust your prices to reduce deadhead miles and running empty. By harnessing machine learning, businesses can locate possibilities for headhaul optimization and get suggestions on load matching and shipment routing. If predictive analytics models are employed for actual supply chain data, they can forecast the probability of finding the next load within an allocated location and timeframe. Based on this, the dynamic pricing model would readjust the pricing.

Benefits of Dynamic Pricing Models for Carriers

Dynamic pricing models offer several benefits for carriers, including:

Dynamically React to Changing Market Demand

By dynamic pricing, businesses can increase their profits by optimizing their prices based on real-time data and demand. Artificial intelligence models can help identify patterns and trends, allowing transportation businesses to forecast future demand and optimize their shipping rates accordingly.

Time Savings by Automating Shipping Quotes and Improved Customer Service

Dynamic pricing models can automate the quoting process and provide real-time quotes to shippers. This can save a lot of time for carriers, as they no longer need to prepare quotes for each shipment manually. In addition, dynamic pricing can improve customer service levels, as shippers can get instant quotes without waiting hours to get their rates.

Reduce Empty Miles and Deadheads

By offering competitive rates, carriers can fill their trucks and reduce empty miles. Similarly, dynamic pricing can help you minimize deadhead miles by automatically adjusting your prices to match market conditions.

Dynamic pricing models in logistics - solid base for automated freight qoute and three key pillars of logistics optizmization and supply / demand forecasting

Improved Asset Utilization and Increased Sustainability

Dynamic pricing engines powered by artificial intelligence technology can improve asset utilization by limiting excess capacity and helping carriers make more money. With dynamic pricing, carriers can automatically consolidate shipments, identify profitable and unprofitable lanes, and offer competitive rates to fill up their available capacity. As a result, dynamic pricing can help carriers become more sustainable and reduce CO2 emissions.

Target Specific Customers with Flexibly Pricing through Shipper Segmentation

Carriers can use dynamic pricing to target specific customers with flexible pricing. By segmenting shippers into different groups, carriers can offer different prices to different groups of shippers.

Gain Insights into Lane Imbalances and Identify Opportunities

With dynamic pricing, carriers can gain insights into lane imbalances and identify opportunities for optimization. You can more efficiently utilize your assets and capacity by automatically monitoring your network state and identifying opportunities for freight consolidation.

Ease of Training for New Pricing Managers

Becoming a pricing manager requires long training and experience. But with a dynamic pricing engine, the pricing is automated, and therefore it is easy to train new pricing managers. With dynamic pricing, all you need to do is input freight details, and the dynamic pricing algorithm will take care of the rest.

Proactively Test and Adjust Rates with Data-Driven Pricing

It is hard to alter the pricing strategy and evaluate its outcomes if everything is manual. But with dynamic pricing, all you need to do is input different price points into the dynamic pricing algorithm, and it will automatically test and evaluate the results. Based on the data, you can then decide how to adjust your rates.

Getting Started with Dynamic Pricing Models

If you’re looking for a dynamic pricing engine that can help your business react to changing market conditions, save time on the quoting process, and reduce CO2 emissions, contact nexocode. Our team of AI experts is ready and waiting to partner with you to create a stellar pricing engine that drives sales and enables you to grow. Contact us today to learn more about how dynamic pricing can benefit your business!

References

Getting the price right in logistics - McKinsey & Company

What really matters in B2B dynamic pricing - McKinsey & Company

About the author

Dorota Owczarek

Dorota Owczarek

AI Product Lead & Design Thinking Facilitator

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With over ten years of professional experience in designing and developing software, Dorota is quick to recognize the best ways to serve users and stakeholders by shaping strategies and ensuring their execution by working closely with engineering and design teams.
She acts as a Product Leader, covering the ongoing AI agile development processes and operationalizing AI throughout the business.

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This article is a part of

AI in Logistics
25 articles

AI in Logistics

Artificial Intelligence is becoming an essential element of Logistics and Supply Chain Management, where it offers many benefits to companies willing to adopt emerging technologies. AI can change how companies operate by providing applications that streamline planning, procurement, manufacturing, warehousing, distribution, transportation, and sales.

Follow our article series to find out the applications of AI in logistics and how this tech benefits the whole supply chain operations.

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