How Airlines Are Evolving Revenue Management to Understand Price Elasticity

Adapting Revenue Management with Elasticity Forecasting

Airlines are under more pressure than ever to price with precision. Traditional revenue management systems, built around fare classes and historical bookings, can’t keep up with the complexity of modern demand patterns. Enter PROS Elasticity Forecasting and Optimization, formerly known as Willingness-to-Pay. This game-changing approach helps airlines estimate elastic demand to capture bookings across both competitive and underserved markets by focusing on the value of passengers rather than estimating demand in fare buckets.

At a recent industry panel, airline revenue management leaders from Aeromexico, Air Europa, Avianca, and Azul revealed how PROS Elasticity Forecasting is transforming their revenue management and pricing strategies. Their insights reveal that Elasticity Forecasting isn’t just a technology upgrade, it’s a strategic shift that requires new thinking, better data, and cross-functional alignment.

The Reality of Traditional Revenue Management

Legacy revenue management (RM) systems were built for a different era in airline retailing. They rely on historical booking patterns and a static class-based approach that worked well for a while. However, today’s volatile markets require greater pricing flexibility, and these systems can’t adapt quickly to changing purchasing patterns or market conditions.

This rigidity creates significant problems:

• Limited responsiveness to real-time demand shifts
• Inability to capture demand at lower price points
• Missed revenue opportunities in both high-competition and low-competition markets

Airlines need a more dynamic approach that considers price elasticity rather than relying solely on historical data and the assumption that demand for each fare is static and independent. As Esteban Rubio, RM Innovation Specialist from Avianca said,

The Case for Elasticity Forecasting

PROS Elasticity Forecasting and Optimization uses AI and machine learning to predict elastic demand for each flight taking into consideration the buy-down effect. Instead of offering the same fare to everyone, airlines can optimize pricing based on demand elasticity and aggregated customer behavior insights.

This approach allows airlines to:

• Compete more surgically on price in high-competition environments and be price-relevant in low-competition or exclusive markets
• Capture more bookings from price-sensitive travelers without undercutting revenue
• Lay the groundwork for future innovations like continuous pricing and the Offer and Order transformation

What makes this approach versatile is its ability to support a wide range of airline business models—from intricate O&D networks to point-to-point operations. This flexibility comes from how the RM system is configured to reflect each airline’s commercial strategy, rather than requiring changes to the core science behind it.

Strategic Use Cases: Where Elasticity Forecasting Works Best

Airlines are taking different approaches to Elasticity Forecasting implementation based on their network characteristics. competition levels, and market position.

Low-Competition Markets

Airlines like Azul use Elasticity Forecasting in markets where they face little competition. These environments provide a safe testing ground for price elasticity without the risk of losing customers to competitors. The goal is to better understand and respond to demand without the immediate threat of losing bookings to rivals.

High-Competition Markets

Air Europa takes the opposite approach, deploying Elasticity Forecasting in highly competitive markets.

The key insight? There’s no one-size-fits-all approach. Network characteristics, competition levels, and business strategy all influence where Elasticity Forecasting delivers the greatest impact. Airlines must tailor their deployment to where this solution can deliver the most strategic value.

Organizational Readiness: The Human Side of Change

Technology alone doesn’t drive successful implementation of the price elasticity principles. Airlines must prepare their organizations for a fundamental shift in how they think about RM and pricing.

Change Management: Cross-Functional Alignment and Economic Literacy

Elasticity Forecasting touches multiple parts of the airline organization. Successful adoption requires coordination across multiple departments:

• Revenue management must embrace new economic models and elasticity-based thinking
• Sales teams must understand margin and be able to communicate dynamic pricing strategies
• Distribution teams need systems that can handle real-time fare changes
• IT teams must ensure data integrity and system integration

Teams must become comfortable with economic terminology and concepts.

This isn’t just about training, it’s about how teams interpret demand and make pricing decisions, moving away from class-based mindset and approaches.

The learning curve is real. Airlines need dedicated change management programs to help teams adapt to new processes and tools. As Ricardo Jakabi notes, “The change management team [and] the implementation team helped us at the beginning of this journey.”

Data: The Foundation of Elasticity Forecasting Success

Clean, reliable data is the backbone of any successful implementation. Without it, model accuracy falters and people lose trust in the system.

Data Quality Requirements

Key data requirements include:

• Accurate historical bookings data
• Clean fare and inventory information
• Quality PNR data

System Integration

Airlines must ensure their pricing and distribution systems can support dynamic price elasticity outputs without delays or errors. This often requires significant IT assessment and careful integration planning to avoid disruptions and ensure seamless execution.

Implementation Best Practices

Based on PROS real-world airline experience with over twenty carriers globally, several best practices emerge for successful price elasticity implementation.

Getting Started with Elasticity Forecasting

For airlines considering Elasticity Forecasting implementation, the journey begins with honest assessment:

1. Evaluate your data quality. Ensure you have clean, reliable data foundations.
2. Assess organizational readiness. Identify training and change management needs.
3. Define strategic priorities. Determine which markets offer your organization the greatest opportunity.
4. Build cross-functional alignment. Ensure all stakeholders understand the vision and their role.
5. Start small and scale. Begin with pilot programs before full deployment.

Start Strategic, Test, and Learn

Don’t try to deploy elasticity pricing everywhere at once. “It’s very important to try to figure out which markets are the ones that you want to have on the [Elasticity Forecasting] system,” advises Javier Subirats. Consider network effects and start with markets where you can measure impact clearly. Approach implementation as an iterative process. Start with pilot markets, measure results, and expand gradually based on what you learn.

Strengthen Competitive Advantages

Price elasticity isn’t just about reacting to market pressure; it’s a tool to reinforce what you already do well. “My recommendation would be to focus on strengthening your competitive advantages,” suggests Ricardo Jakabi. Deploy Elasticity Forecasting where it can amplify your strengths, whether that’s pricing power in low-competition markets or agility in competitive ones.

Invest in People

Technology is only as good as the people using it. “From my perspective, the best advice is to invest in your RM analysts, invest in training, reskilling, because the change in the mindset from the traditional class-based revenue management to [price elasticity] requires a new understanding,” emphasizes Diego Parra, RM Operations Research Manager at Aeromexico.

Equip your teams with the knowledge and confidence to interpret elasticity curves, trust the models, and make informed decisions.

Measuring Success

To ensure price elasticity delivers long-term value, airlines must define clear metrics and monitor performance consistently. Key indicators include:

• Revenue per available seat mile/km (RASM/RASK) to track overall revenue efficiency
• Forecast accuracy and model performance to validate forecast reliability and elasticity assumptions
• Demand shifting and buy-up behavior validation to see if RM decisions are influencing purchase choices

Regular monitoring and adjustment ensure the elasticity model delivers sustainable results over time.

The Path to Dynamic Pricing

Price elasticity isn’t the destination; it’s a steppingstone to class-free revenue management and pricing. When implemented properly, it makes the transition to continuous pricing smoother and more impactful.

The goal is adaptive, real-time pricing that balances yield optimization with customer experience. Achieving this requires real-time data processing capabilities, adoption of advanced AI and machine learning models, integrated distribution systems, and organizational agility.

The Future of Airline Pricing

Price elasticity represents a fundamental shift in how airlines think about RM and pricing. It empowers airlines to respond dynamically to customer demand and market conditions, shifting from class-based to dynamic pricing models.

Success requires more than just technology, it demands strategic thinking, organizational commitment, and a willingness to embrace change. Airlines that invest in Elasticity Forecasting implementation today will be better positioned to capture demand and compete effectively in an increasingly complex marketplace.

The airlines leading this transformation understand price elasticity isn’t just about capturing more revenue, it’s about building more responsive dynamic pricing capabilities that will drive long-term competitive advantage on the path to Offers and Orders.

Frequently Asked Questions