Prime-Class Seat Remapping for Revenue Forecasting
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Solution Overview
Problem
Airlines face revenue loss due to passengers booking seats at lower prices than they are willing to pay, leading to inaccurate demand forecasting and repeated cycles of fare deterioration, as existing systems fail to account for the interdependence of demand between fare classes.
Innovation Solution
A method and system that remaps prime class seat bookings into their target class, considering the interrelationships among fare classes, using statistical analysis and optimization techniques to improve demand forecasting and revenue management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If passengers are allowed to book seats at lower fare classes, then booking availability increases and more passengers can be accommodated, but revenue is lost because passengers pay less than their maximum willingness to pay
Solution Approach 1:
The patent implements dynamic fare class availability management where the system automatically opens or closes specific fare classes based on real-time demand forecasting and revenue optimization algorithms. This dynamic control allows the airline to restrict bookings to higher fare classes when demand is strong, and selectively open lower fare classes when appropriate, thereby maximizing revenue while maintaining booking availability.
Solution Approach 2:
The system changes the parameter of fare class availability status (open/closed) based on forecasted demand and current booking patterns. By adjusting which fare classes are open for booking, the system can guide passengers toward higher fare classes without completely restricting access to lower classes, thus optimizing the balance between booking availability and revenue capture.
2Device complexity
If demand forecasting assumes independence between fare classes, then forecasting complexity is reduced, but forecasting accuracy deteriorates due to ignoring interdependence of demand
Solution Approach 1:
The patent segments the demand forecasting process into distinct fare class components, analyzing each fare class's demand patterns separately while simultaneously modeling the interdependencies between classes. This segmentation allows the system to capture the nuanced relationships between fare classes (such as substitution effects and price sensitivity variations) without creating an impossibly complex monolithic model.
Solution Approach 2:
The system introduces intermediary variables and models that capture the interdependence relationships between fare classes. These intermediaries (such as substitution parameters and cross-elasticity factors) mediate the interactions between different fare class demands, allowing accurate representation of interdependence while maintaining a structured and manageable forecasting framework.
3Ease of operation
If airlines use traditional pricing strategies without considering interclass demand relationships, then pricing simplicity is maintained, but revenue optimization is reduced due to fare deterioration cycles
Solution Approach 1:
The patent implements a feedback-driven pricing system where demand forecasting results from interdependent fare class models feed into automated fare class opening/closing decisions. The system continuously monitors booking patterns, forecasted demand, and revenue performance, then automatically adjusts fare class availability to prevent fare deterioration cycles. This feedback loop enables sophisticated revenue optimization while maintaining operational simplicity through automation.
Data Source
AI summary
A computer based system for remapping prime class seat bookings is disclosed. The system remaps prime class bookings a floor class, or if the floor class is closed, into a higher, displacement class. Via remapping, airline systems, such as inventory management systems, revenue management systems, and the like, may better account for the true value of prime class bookings.