Real-Time Pricing Engine

As yields on many O&D's continue to be driven down by excess capacity, aggressive competition from no-frills carriers and a customer base demanding less restrictive, simplified fare structures, traditional network carriers need more than ever to bank on their strengths and price their fare products according to their real market value. In a highly competitive, volatile and dynamic environment such as today's air travel industry, this means understanding and quantifying their customers' purchase behavior, identifying their market advantage and optimizing their fare schedules to match each customer profile's willingness to pay.

These are by no means easy goals, but ExPretio can help airlines achieve them. Its technology, based on years of high-level academic research, allows for the optimization of fare schedules while explicitly considering customer purchase behavior, pricing actions of competitors as well as network structure, and in particular the interactions between itineraries sharing common flight legs. ExPretio's unique Real-Time Pricing Engine can handle gigabytes of raw data and provide invaluable insight into the market strengths of an airline, thus helping it to optimally position itself against its competitors.

The Engine is based on bilevel optimization methods, a powerful modeling paradigm that is ideally suited for complex pricing problems. It allows an airline to optimize its fares by taking into account current market conditions (fares offered by competitors), network structure (flight schedules), latest booking reports and booking limits, and integrate the rational reaction of various customer profiles who seek to minimize travel disutility by considering all products and itineraries offered on the market. In that sense, the bilevel model incorporates a discrete choice model that recreates the current situation on each market, computes choice probabilities for each alternative and optimizes the airline's fares as to maximize revenue. Choice models are driven by parameters that numerically describe observed customer behavior and sensitivity to various product and itinerary attributes. In order to evaluate those parameters, ExPretio has developed data-mining procedures that are regularly launched on recent sales data, so that the optimized fares computed by the Engine based on these parameters always reflect the latest observed trends in customer behavior.

ExPretio's Pricing Engine fills an important void in airline Revenue Optimization (RO). Whereas overbooking and seat allocation have been given a lot of attention over the last two decades in the airline industry, pricing remains, at several carriers, a fundamentally manual task performed by human analysts, lacking decision-support tools and isolated from other RO functions. By empowering them with cutting-edge analytical capabilities and sound optimization logic, the Engine helps pricing analysts in maintaining their carrier's fare schedule in the best possible state, given current conditions. With ExPretio's Pricing Engine, analysts know, in real-time, how fares should be set and why.

Pricing Engine's main benefits

ExPretio's Real-Time Pricing Engine can help you and your airline

• Quantify and analyze the observed purchase behavior of your customers.
• Identify the strengths of your own fare products with respect to those of your competitors.
• Optimally price each fare product so as to maximize short-term revenue.
• Provide pricing analysts with powerful tools giving them precious insight into the current commercial dynamics of each market.

For further information on ExPretio's Real-Time Pricing Engine, please contact an ExPretio representative.

Dynamic Capacity Management Framework

The allocation of seats to separate and sequentially closed booking classes, usually called Yield or Revenue Management (RM), has become a central commercial process at virtually all airlines, from small regional carriers to long-established national flag-carriers. However, classical and still largely-used RM methods are based on rather strong assumptions that have, in recent years, been challenged by the rise of Low-Cost Carriers and the wide-spread use of Internet.

As traditional RM approaches are rendered less appropriate by the new commercial reality of the Airline Industry, many experts in both academic and industrial circles have been suggesting the accounting of customer behavior and the incorporation of choice models into the RM framework. Such a modeling approach is indeed more suitable in a highly competitive and volatile environment with a knowledgeable customer base (having access to virtually complete and real-time information through the Web) and simplified fare structures.

ExPretio's technology, which is based on years of academic research in optimization and behavioral modeling, incorporates several choice models into a series of software solutions for Airline Revenue Optimization. In particular, ExPretio has developed a powerful Dynamic Capacity Management Framework (DCMF) for airline seat allocation that can be used either as a stand-alone tool or in conjunction with the Pricing Engine in a Joint Revenue Optimization context. The DCMF allows an airline to dynamically optimize seat allocations by taking into account observed customer behavior, current market conditions (its own and its competitors' fares) as well as network structure. As with the Pricing Engine, the Capacity Management Framework uses numerical descriptions of recently observed customer behavior that are computed from sales records using data mining procedures. The incorporation of choice modeling allows the Framework to operate in simplified or fenceless fare environments without relying on traditional Revenue Management assumptions such as product differentiation between booking classes or the independence of demand for each type of fare.

For further information on ExPretio's Dynamic Capacity Management Framework, please contact an ExPretio representative.

Joint Revenue Optimization: Optimal Pricing and Seat Allocation (Revenue Management)

Although pricing and seat allocation have traditionally been, for theoretical, technical and organizational reasons, treated separately by a majority of airlines, there is growing interest toward the adoption of Joint Revenue Optimization (JRO) approaches that would simultaneously resolve these two aspects of the Revenue Optimization problem for a maximum impact on airline revenue. From a commercial point of view, it is clear that revenue depends directly on both price and quantity of seats being offered, and that synchronizing these elements within a single, coherent business process, backed by powerful and integrated decision-support tools, can only lead to further revenue gains.

While it remains a challenging endeavor whose success has, in the past, been hampered by the lack of appropriate tools, ExPretio strongly believes that the future of airline Revenue Optimization lies with JRO. Towards that end, ExPretio has developed a unified decision-support tool that combines the power of its Real-Time Pricing Engine with the flexibility of its Dynamic Capacity Management Framework. The resulting tool allows for the joint, simultaneous and coherent resolution of the pricing and seat allocation problems faced by a typical network carrier.
For further information on ExPretio's Joint Revenue Optimization solution, please contact an ExPretio representative.