The Close-to-real-time Dynamic Pricing Model

The Close-to-real-time Dynamic Pricing Model

Revenue management has been commonly practised in the airline industry since the late 1970s to help airlines increase their revenues by managing price and seat availability. The perceived goal of Revenue Management and Pricing is to attempt to sell each seat at the highest possible price.

Many complex factors are involved in achieving the goal and affecting the price. Most of them can be grouped into 3C definitions:

Capacity – theoretically and on a short-term basis, a route is operated with an aircraft with a fixed capacity. However, in the mid-term, the capacity can be managed by changing the proportion of cabin seats, and in the long-term by changing the aircraft or frequency of scheduling. Different availability of different products affects the proposition and the price of that product.

Customer – theoretically the general customer segmentation based on the business/leisure character of travelers is much more complex. Airline Revenue Managers take into consideration where the traveller starts their journey (Point of Sale), where they fly to (prices depend on markets, not mileage flown), and how flexible they are in terms of travel time and connections (shortest travel time tends to be more valuable to travellers), how flexible they may be to travel on specific days (price restrictions that can discount emptier flights), for how long they travel for, how confident they are to travel (are they ready to book & pay with no refund or change option), when do they make the decision to purchase (last minute purchases tend to be more determined), how price sensitive they are (ratio between % price change to % change in demand driven by that price change), which cabin they are willing to travel, what additional products they are interested to purchase etc.

Competition – aside from Capacity and Customer considerations, one of the most important factors in price decisions is what the competition is doing. Comparing products, schedules and prices is a daily duty of Revenue Management and pricing teams. As so for the Traveller who can use multiple metasearch sites and OTAs available on the Internet offering price and product comparisons for them to make the most valuable purchase decision.

This last factor becomes more & more important to airline Revenue Management as Low-Cost Carriers evolve, new routes and lower prices generate new demands and post covid recovery pushes even more demand to travel. As supply and demand grow, the competitiveness escalates and so does the need for the constant (real-time) ability for the airline to adapt to market conditions and prices.

Traditionally airlines used capacity controls/quantity decisions as a default pricing tactic. This is due to the complexity of factors involved in decision-making and optimization of demand (the right price for the right customer at the right time).  

However, in the last two post-covid years, the revenue management field in the airline industry has witnessed increased adoption of dynamic pricing policies. Dynamic pricing policies are a fundamental component of the competitiveness of an airline.

The graph below is a visualization of all prices available on the LPA-VCE route (Las Palmas – Venice) from today and every next day for the next 60 days. It considers all airlines that have connections between the two cities. Within the grey box, there are 69% of all prices. The end of the lines above and below the box is the maximum and minimum price.

You can see how dynamic the airline prices are. They start somewhere below 230 € and reach above 1900 €. But most of them are between the 230-600 € range. This is a Competition factor to be taken into consideration, only then Capacity and Customer factors can play a role. 

In highly competitive markets, traditional capacity and customer-driven price dynamics should be applied to competition dynamics.

“Close to real-time price dynamics” as we call it, are very difficult to achieve. They require full-price automization and heavy computing power that can process ML-based algorithms.

Fare simplification is required to manage the price and dynamics. Implications on forecasting and optimization methods also need to be taken into consideration.

The impact of a successful “close to real-time dynamic pricing strategy” can be significant. According to McKinsey, on average, it can help businesses achieve a 5-10% increase in profit margins. Customer-choice modelling, continuous pricing, and differentiated retailing all come together to maximize the per-seat profit and broaden the appeal to your customers.

What is the future?

The “close to real-time dynamic pricing model”  is causing excitement and driving change in the airline sector. Many face the prospect with some trepidation, as it means transitioning away from decades-old pricing systems that are deeply entrenched. As a result, many experts see dynamic pricing potentially becoming an add-on, as a price mark up or mark down. This would bring the benefits of the strategy but also mitigate the complexity of changing systems. Dynamic pricing will become widely adopted for simpler products where it is easier to change systems.

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