Scraping the Skies: Get Insights from Flight Data
Types of air travel data and use cases we can get from the web
The travel industry is one of the first to be digitalized. Booking.com was founded in 1996, and Edreams in 2000, in the early days of the internet's mass adoption.
One of the causes of this digital transformation is probably that, more than most sectors, it has a highly dynamic nature and global reach. Airlines, travel agencies, and booking platforms manage millions of transactions daily in real-time. Travelers rely heavily on online platforms to plan and book their journeys, so the travel industry has become a fertile ground for data generation and digital innovation.
Digitalization in this sector is driven by consumer demand for convenience, competitive pricing, and personalized travel experiences. Today, airlines employ complex algorithms for dynamic pricing, while travelers expect to be able to make online bookings, check-in, and receive real-time flight updates.
This means building systems capable of interconnecting the industry's different actors so that they can obtain and share the data needed to run all operations smoothly, from ticket purchases to flight updates.
The different actors in the flight industry
But who are the actors in the flight industry, and what kind of data do they share with others?
Here are some of them:
Airline Websites: These websites provide direct flight schedules, ticket prices, seat availability, and real-time updates. Scraping airline websites allows access to primary data straight from the source, including promotional fares, flight durations, and loyalty program offers.
Online Travel Agencies (OTAs): Platforms like Expedia, Kayak, and Skyscanner aggregate flights from multiple airlines, offering price comparisons, flight durations, and customer reviews. Scraping OTAs can provide insights into competitive pricing, traveler preferences, and market trends.
Flight Tracking Websites: Services like FlightRadar24 and FlightAware offer live flight tracking, historical flight data, and airport activity. Scraping these sites can yield data on flight paths, aircraft types, delays, and cancellations.
Airport Websites: These websites publish real-time flight statuses, terminal information, passenger services, and even weather conditions. Scraping airport data helps understand airport traffic, operational efficiency, and passenger flow.
An alternative to scraping for OTAs and flight tracking services is to use their APIs, which they provide but, in some cases, reserve for travel industry operators.
We can summarize the data we can gather in these categories:
Routes data: we can map the routes established by airlines in the world with standard airport codes, frequency of flights, and aircraft models. This kind of data is quite static and can be refreshed once a week for each airport since we know in advance the scheduling of the flights for the next weeks or months.
Flight data: This category includes what happens to a single flight on a route, including delays, departure and arrival times, flight numbers, airline names, and cancellations.
Booking data: This category includes seat availability, booking status, ticket prices, and fare classes.
How to use data about flights
Flight data can be utilized in numerous ways across various industries. Some key applications include:
Dynamic Pricing Algorithms: Airlines and travel agencies use scraped data to adjust ticket prices based on demand, competition, and seasonality. By analyzing competitor pricing in real time, they can implement pricing strategies that maximize revenue.
Market Analysis: Analysts and investors assess travel trends, popular routes, and airline performance by studying historical and current flight data. This helps identify emerging markets, popular destinations, and consumer behavior trends.
Operational Efficiency: Airlines monitor their schedules, delays, and cancellations to improve services. Scraped data can be used to identify bottlenecks, optimize flight schedules, and improve customer experience.
Consumer Insights: Travel platforms analyze booking behaviors to tailor their offerings. They can personalize their marketing efforts by understanding peak booking times, preferred destinations, and pricing sensitivity.
Use Case 1: Estimating Fill Rate of Flights
An interesting use case is to create a statistical model to estimate the occupancy rate of a flight.
While airline companies have the occupancy rate of their own flights, I don’t know if they can obtain data from other companies by buying data from a provider. In any case, airline companies are not the only subjects that could be interested in this kind of data: most of the airlines are listed on the market, so being able to approximately estimate the fill rate of every flight of a company can tell a lot about its revenues and efficiency.
This can be done by using booking data more often. Ideally, booking websites should be scraped a few hours before a particular flight takes off (and this should be repeated for every company flight). Scraping the results of an inquiry about the maximum number of tickets the website allows you to book per seating class gives a good hint about how many tickets are left available.
The information shown varies from website to website. For example, Booking.com shows this alert only if nine tickets or fewer are available on a flight for a specific seating class. If you don’t see the advice, you know that there are at least 10 seats available, which is not good, especially on short-distance flights, where the margins can be lower since there could be more pressure on prices by other transport means, like high-velocity trains.
Use Case 2: Measuring Flights Cancelled and Late to Understand the Airline Operativity
Another use case is gathering flight data to measure the efficiency of an airport, route, or company by simply measuring flight cancellations and delays. This data provides insights into airline reliability, customer satisfaction, and potential financial losses due to strikes or adverse climate conditions. In addition, we can imagine that airlines with frequent delays and cancelations make their customer unhappy, and in the long run, they could see their revenue drop.
Frequent delays or cancellations might indicate internal challenges such as staffing shortages, maintenance issues, or poor planning. Conversely, consistent on-time performance enhances an airline's reputation and customer loyalty. Regulatory bodies can also use this data to enforce industry standards and protect consumer rights.
For all these use cases, a daily scan of the flight data from all the airports in the world is enough if the source keeps the history of the flight data.
Use Case 3: Measuring the World Economy and Trends to See Where People Are Flying the Most
Flight data serves as a proxy for economic activity. High volumes of flights to business hubs can signal economic growth, while increased travel to tourist destinations may reflect rising disposable incomes and consumer confidence.
Tracking flight trends over time helps analysts gauge economic health, identify emerging markets, and understand global travel patterns. For example, a surge in flights to a particular region may indicate business investments, new trade routes, or geopolitical stability. Similarly, a decline in flight activity could signal economic downturns, travel restrictions, or shifts in consumer behavior.
These are soft signals, but if collected for long enough, they can give investors and analysts a picture of how the world’s economy is shifting. If more flights depart from an emerging market, it could mean more people are in the condition to spend money on travel.
For this type of analysis, scraping route data maybe once a week is more than enough since flights are planned months ahead.
Final remarks
Scraping flight data has several facets, and depending on your interest, we have seen that there could be several approaches and data sources that can be used.
If you’re an investor, an operator in the industry, or a market analyst, the web in 2025 offers a massive amount of data to support your own thesis on the flight industry.
Do you use any of this type of data in your company? If so, how does it help you? Feel free to write it in the comment section.