In this guide:
- Unpack the key components of Airfare Data
- Explore how Airfare Data is sourced and used
- Discover practical strategies for using it effectively
What is Airfare Data?
Airfare Data (like airline schedules data) is structured, coded, and governed by industry standards, but its behaviour is far more volatile. Fares can change hundreds of times a day, based on market demand for a single route, making it one of the most dynamic datasets in the aviation industry.
- The insights from Airfare Data provide a rich lens into the economics of modern air travel from public fares distributed through Global Distribution Systems (GDSs) to private offers shared via New Distribution Capability (NDC) channels.
Airfare Data is not only at the heart of an airline’s pricing strategy, but also a key component of traveller decision-making.
At its core, Airfare Data refers to the complex and dynamic information that determines how much a passenger pays for a flight, from the base fare to taxes, fees, surcharges and ancillary services like baggage and extra leg room.
Beneath the surface of the price a passenger sees displayed online, lies a dynamic pricing engine shaped by:
- Competitive influence
- Historical trends
- Market demand
- Artificial intelligence
What Makes Up Airfare Data?
Behind the Fares: How the Airline Industry Uses Airfare Data
The quality of Airfare Data is critical to the accuracy and reliability of any analysis. OAG’s Airfares are sourced directly from airline.com channels, providing the most current and authoritative view of publicly available fares. Through a unique 'give-to-get' model, airline partners participate in a mutually beneficial exchange. By sharing their own detailed, high-quality data, they gain access to valuable aggregated competitor insights.
This collaborative approach ensures data is collected transparently and efficiently, with sources specified and verified by participating airlines. It also supports a shared marketplace of information that enhances reliability, reduces duplication, and upholds data integrity across the network.
On average, OAG achieves 98.1% data completeness and timeliness, giving analysts and industry stakeholders confidence that the data they work with is both comprehensive and current.
Competitive Analysis
In a competitive market, airline pricing and revenue management teams must stay constantly attuned to their competitors’ strategies. Airfare Data enables airlines to monitor rival pricing, capacity fluctuations, customer segmentation, and market positioning to inform more competitive and agile decision-making.
This type of intelligence is equally valuable for online travel agencies (OTAs), who rely on price comparisons to assess their positioning in the marketplace. By understanding how their prices compare to those on other platforms, OTAs can fine-tune pricing, optimize promotions, and manage inventory in response to shifting market dynamics.
In both cases, Airfare Data provides the foundation for sharper competitive analysis and smarter commercial strategy.
Airfare Forecasting
Thanks to the vast amount of historical airfare data available, analysts can forecast future prices using a combination of historical trend analysis, machine learning, and real-time market signal monitoring.
Airfares often follow predictable patterns, such as seasonal trends (e.g., summer travel peaks) and booking window dynamics. Prices can also surge around major global events. Recognising these cycles over time enables forecasters to anticipate when prices are likely to rise or fall based on the time of year and how far in advance a ticket is booked.
Historical data analysis helps predict future airfares by identifying and modelling these recurring patterns and using them to forecast what may happen next. Additionally, analysing route or carrier-specific historical pricing can reveal how and when airfares tend to change.
For example, if historical data shows that fares from LAX to JFK typically drop 45–60 days before departure, and current prices are unusually high within that window, a predictive model might anticipate an imminent price decrease.
Market Analysis
Airfare Data can be a powerful ingredient for market analysis, providing insight into demand, consumer behaviour, competitive strategy, and macroeconomic trends. Rising prices often indicate heightened demand, while frequent fare spikes or the unavailability of low-priced buckets may signal increasing route popularity. By tracking how airfares evolve over time and across markets, analysts can uncover patterns in travel behaviour, identify emerging destinations, and detect shifts in price sensitivities amongst travellers.
Airfare Data offers a real-time lens into consumer confidence, tourism flows, and regional connectivity.
Whether used to benchmark competitors, monitor market saturation, or forecast prices, Airfare Data is an increasingly valuable resource in understanding the dynamics of the travel ecosystem.
The Challenge: Airfare Volatilities
Airfare Data may look simple on the surface, a price displayed on a website, but beneath the figure shown lies a complex ecosystem of variables, systems, and strategies that make it one of the most challenging datasets to manage and analyze due to the sheer scale of data available.
Volatility is one of the reasons Airfare Data is so rich and dynamic. Prices can fluctuate hundreds of times per day for a single route, depending on changes in demand, competitive moves, availability shifts or pricing algorithms and fare buckets.
Myth Buster: Inflating Airfares Based on Searches
A common misconception among travellers is that airlines or OTAs track individual searches and raise fares when the same route is checked repeatedly. In reality, there is no evidence that this practice occurs, and it would in fact violate data protection and consumer laws such as GDPR.
As noted by Time magazine, fare fluctuations that appear to respond to repeated searches are more likely the result of legitimate market factors such as inventory changes, competitor adjustments, or dynamic pricing algorithms. These systems continuously update fares in response to supply and demand, not personal browsing behaviour.
While it can seem as though prices rise the more often you look, the reality is that airfare volatility and real-time market recalibration create that perception, rather than deliberate manipulation.
Not only are there the real-time quantities of data to consider, but there are also historical airfares that are collected over time up to the departure date. At OAG, we have 4 trillion historical airfares on our database, dating back more than 10 years, which is growing by 4 billion airfares daily from over 700 airlines!
A Unique Market View: Supply, Demand, Pricing
Airfare Data is a powerful dataset for analysis and forecasting on its own, but when combined with other OAG datasets such as Schedules and Passenger Booking Data, it unlocks a complete 360-degree view of the global aviation landscape. By bringing together multiple data sources, stakeholders can understand not only when and where airlines are operating, but also how passengers are responding to that capacity and at what price points.
Together, these datasets represent the three core dimensions of the aviation market: Supply, Demand, and Pricing.
- Supply Data shows the availability, attributes, and operational status of global flights.
- Demand Data captures how travellers search and book, providing insight into evolving behaviour and market interest.
- Pricing Data connects the two, illustrating how airlines translate capacity and demand into fares.
Understanding this balance allows stakeholders to explore the true economics of air travel and see how shifts in supply and traveller intent influence price movements and, ultimately, airline performance. This integrated perspective forms the foundation of OAG’s approach to aviation intelligence, helping the industry move beyond isolated datasets toward a more connected and meaningful understanding of market dynamics.
Airfare Strategies – Dynamic + Continuous Pricing
In our blog that looked at Emerging Revenue Management Trends, we explored the similarities and differences between Dynamic and Continuous Pricing strategies. Both are modern strategies aimed at maximising revenue by aligning fares more closely with market conditions and customer behaviour, but they differ in scope, flexibility, and technological maturity.
- Dynamic pricing involves adjusting fares based on real-time data such as booking patterns, competitor pricing, and demand drivers like weather or events. It’s a significant improvement over static pricing models, but it is often constrained by legacy systems and rigid fare rules and structures (like RBDs), which limit the number of price points and the frequency of updates.
- In contrast, continuous pricing, also known as total dynamic pricing, goes a step further. It enables airlines to generate an almost infinite range of personalised price points in real-time, based on contextual signals and a deeper understanding of each customer's willingness to pay. Unlike traditional methods, continuous pricing aims to unify base fares and ancillary services (like baggage or seat selection) into a single, personalised offer, increasing both conversion rates and customer satisfaction.
While dynamic pricing optimizes within a predefined fare framework, continuous pricing redefines the offer itself, moving toward a more seamless, customer-centric, and intelligent retailing model powered by AI and aligned with industry standards like NDC and One Order.
The Evolution of Airfares and What’s Next?
Over the past five decades, airline pricing strategies have undergone significant evolution, transitioning from static models, based on a restricted number of fare classes, to more dynamic and personalised approaches.
Traditional systems restricted flexibility in revenue management strategies, but dynamic pricing introduced real-time adjustments driven by market demand and customer behaviour. Now, continuous pricing is emerging as the next frontier, enabling airlines to offer highly personalised fares and bundled services using AI and machine learning.
This shift promises greater revenue optimisation and a more tailored customer experience, marking a new era in airline retailing.
As the industry continues to embrace these innovations, and with the rise of NDC and One Order, the future of airline pricing lies in creating a true retail experience, powered by holistic, fully personalised, customer-centric models that respond swiftly to market dynamics and individual preferences.
