Dynamic Pricing In The Bus Coach Industry

By Stanislaw Schmal, Director Data Analytics & AI at Lufthansa Industry Solutions US; and Mauro Garcia, Marketing Manager for Lufthansa Industry Solutions US.

Pricing in the bus coach industry has gone through different developments. During pre-pandemic times, cost and competitive pricing were the main drivers of bus fares. Both charters and intercity connectors would reflect fare decreases by competitors. This would continue as long as the region size of bus operators would decrease to a minimum.

After the pandemic, many bus coach operators have seen a steady rise in bus fares. Both charters and intercity connectors steadily increased their prices throughout 2022. This increase was mainly driven by catching up demand and decreased inventory of buses and/or drivers. However, due to rising labor and fuel costs, margin has not followed the same trend.

Some bus operators leveraged that time to implement technology innovation on the revenue management side. One example is the implementation of “dynamic pricing” tools and strategies. Dynamic pricing is a popular pricing strategy that has been used in the travel industry for years. The goal of dynamic pricing is to enhance prices based on demand, competition, and other external factors to maximize profits. There are many benefits of dynamic pricing for businesses, like increasing revenue, improving customer satisfaction, and better utilizing unused inventory.

Dynamic Pricing Reacts On The Spot

The dynamic pricing algorithm uses tactics that involve regulating prices for products or services based on real-time market opportunities. The approach is to charge different prices for the same product depending on days to travel, demand, willingness to pay, and other parameters. The same charter or bus fare from city A to B can have different prices on different days depending on current and estimated demand, competitor pricing, and other criteria.

Dynamic pricing optimizes bus operators’ total revenue. It takes into account all of the factors that can affect your business’s bottom line. This allows revenue managers to set prices that maximize profits while still providing value to customers. Dynamic pricing can help to respond quickly to drastic changes in the market. For example, if there is a sudden rise in demand for your services, the dynamic pricing tool recognizes the trend and adjusts the prices automatically. Conversely, if demand decreases or competition increases, the dynamic pricing tool lowers prices to be ahead of the market.

This approach can help bus operators to quickly react to shifts in demand and increase their profits.

Additionally, dynamic pricing ensures that you are not selling at a loss and helps you to make decisions about which route to cover depending on the seasonality and how to improve your operational processes.

Dynamic Pricing Strategies

Dynamic pricing in the bus couch industry comes in different sizes and benefits. The approaches differ in their implementation complexity and technological know-how. The more complex the approach the more granular the pricing and the higher the benefit uplift.

The rule-based pricing approach is the simplest technique to adjust pricing to market situations. This approach is mainly based on historical demand information. If demand for charters or a particular intercity route is higher on Tuesday afternoons, the rule-based approach would recommend a price increase for trips starting at that time. The rule-based approach is easy to implement and does not require any technology tool. On the other hand, this approach is limited to historical information and does not take into account any future demand or market changes.

The category-based approach is a medium-sized technique to leverage demand in the pricing strategy. The category-based approach considers seats or vehicles already sold in the price decision. In this case, the price changes with the amount of already booked trips. For example, an intercity operator can sell the first 10 seats on a trip for $5 less than all other seats. A charter operator can sell the last seven buses for a particular weekend in August with a premium of 15%. This approach ensures that costs are covered on each trip and optimizes revenue management with the booking over expected demand.

The prediction-based approach is the most complex technique in adjusting prices to market situations. This approach requires a supervised training method to predict future demand and adjust the prices accordingly. The method uses historical data to train a price-demand model. This model is applied to predict future demand with a particular price.  This technique is mainly implemented with external providers and additional software. As this approach is the most complex it also provides the highest expected benefit lift. Due to their anticipation of demand on a particular date, bus operators avoid selling charters and trips at a lower price than they could have.

By constantly monitoring market conditions and reacting quickly to changes, bus operators can stay one step ahead of the competition and keep their prices in line with customer demand and as a result, keep their margins healthy. This approach enables companies to take advantage of special circumstances such as promotions or seasonal trends.

Going forward, price competition in the bus coach industry will be determined by the best service and experience. Attracting and retaining passengers will become a capability of technology. Bus operators who prepare today for the changing travel world of tomorrow will outperform the competition in the market and take full advantage of digital transformation and data analytics. More than ever, it is important for bus operators to keep a finger on technology trends and set the course for dynamic pricing, either by themselves or with an IT support partner.

About Lufthansa Industry Solutions

Lufthansa Industry Solutions (LHIND) is a service company for IT consulting and system integration with a long-standing business relationship in the cruise industry. The Lufthansa subsidiary supports its customers in digital transformation and data analytics. The customer base includes companies within the Lufthansa Group as well as more than 300 companies in different industries. Headquartered in Norderstedt, Germany, the company employs more than 2,500 people at several offices in Germany, Albania, Switzerland, and the United States. Visit lufthansa-industry-solutions.com/de-en/.

About the Authors

Stan Schmal is with Lufthansa Industry Solutions US, a service company for IT consulting and system integration in Miami, FL. Stan and his team have introduced AI products and Data Analytics platforms for marketing and sales, revenue management, and operations departments in the cruise industry. The team focuses on enabling Data Analytics applications for daily business operations and covers projects in NLP, predictive modeling, business intelligence, and data management. Stan previously held various data scientist and business roles with airlines, cruise lines, and the financial industry.

Mauro Garcia is a global marketer with 15+ years of experience in the advertising industry. Acknowledged for the ability to build strategic marketing plans and collaborate across different divisions within LHIND, among which can find Data Analytics. Produces omnichannel campaigns that generate sales lift, brand/product awareness, and consumer engagement. Passionate for driving communications toward the promotion of digital solutions & innovations in the market. Currently leading the global branding plan, advertising strategy, performance marketing, analytics, and content development for LHIND Americas.