Dynamic Pricing in Logistics. How to Build an AI-Based Pricing Strategy?

Dynamic Pricing in Logistics. How to Build an AI-Based Pricing Strategy?

Dorota Owczarek - February 27, 2022

In a business as fast-paced as transportation and logistics, it is crucial that companies are able to price their products and services quickly and smartly. Dynamic pricing, also referred to as surge pricing, demand pricing, or time-based pricing, is a strategy that allows businesses to do just that. By setting flexible prices based on current market demands, companies can maximize profits by adjusting prices according to algorithms that take into account competitor pricing, supply and demand, and other external factors in the market. In this article, we will discuss why dynamic pricing is so important for companies in the transportation and logistics industry and how artificial intelligence can be used to create a successful dynamic pricing strategy.

Why Should Logistics Companies Look Into Novel Pricing Strategies?

In the logistics industry, competition is high, and margins are low. To remain competitive in their market, companies must be able to adjust their pricing quickly according to changes in supply and demand for their goods or services.

COVID-19 pandemic has exacerbated the need to enhance pricing tactics, noticeably raising the stakes. As a result of the pandemic, some companies have seen revenue decline, while others have experienced an increase in demand for their products and services. All these events affected global supply chains, which, in turn, affected how logistics companies price their services. To adapt to these rapidly changing business needs, logistics businesses must be able to alter their pricing strategies accordingly.

Pricing is the lever with highest impact on profit.

Dynamic Pricing Strategy - How Does It Work?

Any dynamic pricing strategy aims to find the right price for a product or service that will result in tremendous profits for the business. This is done by considering current market conditions, competitor prices, and other factors that may influence demand.

There are many ways to implement a pricing strategy with dynamic pricing software, and they may all be used together to fit any business plan:

  • cost-plus pricing
  • competitor-based pricing
  • value-based pricing
  • time-based pricing
  • price discrimination
  • key value items (KVI) based pricing
  • predatory pricing

Most of these methods are common in the transportation and logistics industry. Still, with the help of artificial intelligence (AI), businesses can tailor their dynamic pricing strategy to fit their specific needs. There are several different ways companies can implement a dynamic pricing strategy. One way is to use artificial intelligence to create complex deep learning algorithms that automatically adjust prices based on changing market demand, conditions, and company targets. AI can be used to monitor competitor prices and track supply and demand for products or services to make informed decisions about when and how much to adjust prices.

What Is AI, and How Does It Help?

AI is short for artificial intelligence, a type of software that allows computers to learn from data and make decisions on their own. This makes it the perfect tool for implementing a dynamic pricing model, as it can analyze large amounts of data quickly and make changes to prices accordingly.

Businesses that use AI-based dynamic pricing algorithms will be able to respond more quickly to changes in the market and maximize profits by adjusting prices at the right time. Not only that, but AI can also help businesses to be more strategic in their pricing by taking into account factors such as customer psychology and perceived value.

The most common ML algorithms for dynamic pricing engines are based on:

  • Bayesian models,
  • Reinforcement Learning (RL),
  • Thompson sampling,
  • Decision tree models.

The most effective pricing engine is a two-stage machine learning system. The first stage assesses the impact of price changes on sales and profits. The second step is the price optimization model, which involves using the findings from the first stage to suggest prices for the entire services or products portfolio.

dynamic pricing model how it works

How dynamic pricing strategy works? How changing variables impact price optimization.

Dynamic Pricing Strategy in Logistics and Supply Chains - Examples

Dynamic Freight Pricing for Ocean Freight Carriers

One of the most important examples is dynamic freight pricing for ocean freight carriers. To remain competitive in a constantly changing market, many ocean freight carriers are turning to dynamic pricing models to price their services. This sector is currently experiencing a significant increase in prices, and dynamic pricing allows carriers to adapt to these changes quickly.

Freight spot rates and contract rates are two distinct value propositions for shippers, with contracts providing price and capacity year-long security. In contrast, the spot market is available to assist shippers when their contract carriers aren’t enough, or there’s a need to transport freight on a lane where a contract rate hasn’t been agreed.

Spot Rates for Container Shipping

Spot rates for container shipping are constantly fluctuating, and it can be difficult for carriers and clients to keep up with the changes. This is where dynamic pricing comes in, allowing them to adjust prices based on current market conditions quickly.

Dynamic pricing mechanisms could enable ocean freight buyers and sellers to agree on binding forward commitments, eliminating inefficiencies in the existing spot market. The dynamic pricing engine aims to develop a simulation model that can price freight transport contracts between a buyer and seller in a way that reflects their mutual interests.

Large customers often contract capacity on ships, generally with no penalties for no-shows. Large clients frequently engage in volume purchasing and are typically given lower rates than smaller clients. A tailored pricing approach that pushes large-volume consumers away from these practices could restore balance to the market.

Dynamic Pricing in Air Cargo

Airlines have been using dynamic pricing models for years to maximize profits on specific routes for pricing passenger flight fares, which is probably the most well-known and visible example of dynamic pricing. For instance, they will often increase ticket prices during busy travel times (such as holidays) or when there is a lot of competition from other airlines on a particular route. Airlines also use dynamic pricing to sell premium seats at a higher price than regular seats.

Airfreight cargo carriers are also using dynamic pricing models to price their services of transporting commodities. The rates that airlines offer will depend on several factors, including but not limited to: the type of commodity being shipped (perishable goods need expedited delivery), size/weight limitations imposed by the airline’s aircraft, and how much space is available in their cargo hold(s). Airfreight carriers can create AI-based algorithms that additionally take into account competition pricing (including transport of goods by other means), supply and demand, and external variables to optimize profits.

Time-based Pricing Strategies for Freight Forwarders

Freight forwarders are in the unique position of offering both contract and spot pricing for their services. They often have long-term contracts with customers, which gives them a certain degree of stability regarding price. At the same time, freight forwarders also offer their services on the spot market, which allows them to take advantage of changing market conditions.

A good pricing strategy for freight forwarders offers stability for their contracted shippers while also taking advantage of changes in the market. This can be done using AI-based dynamic pricing algorithms that quickly adjust prices based on current conditions.

The goal should always be to find a balance between what you need to charge to stay afloat, and dynamic pricing should not only consider market conditions but individual clients’ spending power and willingness to pay.

LTL Freight Management with Dynamic Pricing Model

An LTL freight management company can take advantage of dynamic pricing in its operations by utilizing an AI-based algorithm that considers co-loading opportunities. This means that they can find shipments with similar route characteristics (concerning required timings, space, and mass to be matched as partial loading) and offer them at a discounted rate to increase volume. The AI-based algorithm used should be explicitly designed for the purpose of finding opportunities like this one which would not normally be visible by looking through data manually.

LTL freight companies should also consider direction as part of the pricing strategy. Moving freight to directions where it is hard to find further loading opportunities should have higher prices than moving freight in directions with many options to co-load.

It is crucial that FTL businesses set flexible prices that are smart enough to consider current market conditions and external variables such as weather or traffic congestion. This allows them to be competitive on the market by adjusting prices accordingly, which helps reduce costs while maximizing profits.

Surge Pricing in FTL Trucking

Truckload carriers are also using dynamic pricing to remain competitive. In fact, about 60% of truckload carriers are currently using some form of it. This is because the truckload transportation market has become much more complex in recent years, with a more significant number of players and increased regulation. This means that there is more competition for contracts, which leads to price fluctuation.

In addition, there has been an increase in demand for trucking services as the economy continues to grow, so companies in this sector must be able to adjust prices quickly to take advantage of these changes. Just as it is in other transportation modes, surge pricing is becoming more common within trucking companies. The practice of offering lower prices for shipping goods when there is less demand and raising the price when there is higher demand can be very profitable for truckers.

To use surge pricing effectively in FTL trucking, a trucker needs access to real-time data that shows current market conditions (highs and lows) and supply/demand ratios. This information will allow them to make quick decisions on whether or not to raise their prices.

Dynamic Pricing for Parcel Shipping in Logistics

Parcel shipping is also an excellent sector to consider demand-based pricing. This is because the market for parcel shipping is much more volatile than that of truckload or LTL transportation. The reason for this is twofold: first, there are many more players in the market, and secondly, customers are much more price-sensitive when it comes to small shipments.

Many parcel shipping companies are looking at dynamic pricing as a way to increase their margins while still offering competitive prices on services like overnight delivery or two-day service options with guaranteed arrival times within 24 hours or less than 48 hours, respectively. An excellent example of this is online retailers and Amazon’s Prime Now program, which offers free two-day shipping on many items. Parcel shippers should also focus on bundling their products together to increase volume and get better rates from carriers. This is another area where dynamic pricing can be very beneficial because it allows companies to bundle products together and sell them at a discounted rate.

Dynamic pricing should be tailored to each segment of customers, depending on the needs and willingness to pay for this service. A parcel shipper may want to use AI algorithms that consider all relevant information, including but not limited to competitive rates. This means that companies need to be able to change prices rapidly to take advantage of changes in the market. In addition, they need an AI-based algorithm that can accurately predict demand so that they don’t overprice or underprice their services.

Dynamic Pricing for Railways

Rail transportation is another sector where dynamic pricing is becoming increasingly important. Rail companies are facing increased competition from other modes of transport, such as trucks and ships, so they need to react quickly to changes in demand if they want to remain competitive. Price elasticity allows rail companies to adjust prices according to current traffic conditions, which helps them move more cargo and make more money.

The Benefits of Dynamic Pricing in Logistics

There are several benefits that come with implementing a dynamic pricing system for logistics companies:

Increased Profits

Dynamic pricing can help businesses increase profits by charging more for products or services when demand is high and less when demand is low. This allows logistics and transportation companies to take advantage of changes in the market, which can result in increased revenue.

More Accurate Forecasts

By using algorithms that consider current market conditions, businesses can develop more accurate forecasts for future sales. This helps them better plan for future needs and avoid stockouts or overages.

Improved Customer Service

Offering different prices for the same product or service can confuse customers. A good time-based pricing algorithm can help businesses provide better customer service by ensuring that customers are charged appropriately based on their individual needs.

Improved Efficiency

By using algorithms to adjust prices, businesses can save time and money because they don’t have to manually change item prices or negotiate with suppliers daily. This also means less paperwork and fewer lost sales.

Reduced Costs

By using dynamic pricing, businesses can reduce their overhead costs because they don’t have to hire additional employees or pay for office space. They also won’t need as much inventory since prices will be adjusted based on demand instead of having fixed price points like traditional retailers do.

Increased Sales Volume

A good pricing strategy can increase sales volume by enticing customers to buy more products or services.

Optimized Fleet Utilization

By adjusting prices, businesses can also optimize their fleet utilization by ensuring that their trucks are only going to the places where they can make the most money or by co-loading similar shipments. This reduces fuel costs and emissions from unnecessary truck trips.

Conclusions

It’s not enough just to know what your competitors are charging for freight services; you also need to adjust your own prices based on supply and demand. The goal is simple: maximize profits by charging what people are willing to pay. This can only be achieved if carriers understand their customers’ needs, which includes understanding how much they would spend on shipping costs at any given time of day or week during peak season when rates go up because there’s more traffic than usual (surge pricing). A dynamic pricing strategy enables businesses that offer transportation services to do this by monitoring changes in real-time data - using algorithms explicitly designed with those variables in mind, so they’re constantly adjusting accordingly.

Dynamic pricing is crucial for a company’s success in the transportation and logistics business. By using AI, businesses can create algorithms that take into account competitor pricing, supply and demand, and other external factors in order to set prices that will maximize profits. Applying dynamic pricing models can help companies stay competitive in a constantly changing market.

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
8 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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