Understanding Booking Curves and Passenger Behavior

Passenger behavior is predictable—until it isn’t. That’s why the booking curve is our guide.

Introduction

How far in advance do passengers book their flights? What does a "normal" sales pattern look like for a route? These questions are central to airline Revenue Management (RM), and the answer lies in one of RM’s most important tools: the booking curve.

A booking curve maps out how bookings typically accumulate in the days and weeks before departure. When understood and applied well, it helps airlines forecast demand, control availability, and identify when something is going wrong—or surprisingly right.

What Is a Booking Curve?

A booking curve is a visual or data representation of how a flight sells over time. It shows the number of bookings (or seats sold) as a function of the number of days remaining until departure (known as DCP: Days to Departure).

Example:

• Day 60: 10% of seats sold
• Day 30: 45% of seats sold
• Day 7: 80% of seats sold
• Day 1: 95% of seats sold

Each route, flight type, and season will have a different curve—but they often follow a similar shape, depending on the type of customer.

Why Booking Curves Matter

Booking curves help Revenue Management teams to:

• Forecast how many passengers will likely book in the coming days
• Evaluate whether a flight is selling “on pace” or underperforming
• Adjust fare availability to optimize revenue
• Detect unusual booking behavior (e.g., sudden drop-off in sales)

They’re also useful for pricing teams to measure the impact of fare changes or competitor actions on sales velocity.

Passenger Segments and Booking Behavior

Understanding the curve means understanding the passenger. Different traveler types behave differently:

Leisure Travelers

• Book far in advance—often 30 to 90 days before departure
• Highly price-sensitive
• Responsive to promotions and fare sales

Business Travelers

• Book closer to departure—often within 7 to 14 days
• Less price-sensitive, more schedule- and flexibility-focused
• Often pay higher fares for flexibility or timing

Airlines structure fare ladders and availability rules to reflect this behavior—lower fare classes are open early for leisure demand, while higher-yield fare classes are protected for business travelers booking late.

Typical Curve Shapes

• Leisure-heavy routes (e.g., holiday destinations): Long, slow build-up, steep curve in early days
• Business-heavy routes (e.g., hub-to-hub corridors): Flatter early, steeper increase closer to departure
• Low-cost carrier curves: Often earlier booking due to stronger price incentives and fewer last-minute business travelers

Seasonality, day-of-week effects, and special events can all distort these baseline curves.

Using Booking Curves in RM Systems

Revenue Management systems track the expected booking curve based on historical data, and compare it to the actual sales curve for each flight.

If bookings are ahead or behind forecast, the system may:

• Open or close fare classes
• Adjust overbooking levels
• Trigger alerts for analyst review

This process helps airlines stay responsive without overreacting to daily fluctuations.

What Booking Curves Don’t Show

While powerful, booking curves only show how much is booked—not why.

This is where tools like PriceEye complement RM systems by providing competitive context:

• Has a competitor dropped fares on the same route?
• Did they change refund rules or add new restrictions?
• Has a new carrier entered the market?

Without this data, a sudden slowdown in bookings might seem unexplained—even though the answer is visible in the market.

Example: Booking Curve in Action

Let’s say you’re managing a flight from JFK to LAX 30 days before departure. The expected curve says you should have sold 40% of seats. But actual bookings are only at 25%.

You dig into PriceEye and discover:

• A competitor dropped their lowest fare by $30 two days ago
• They’ve also removed change fees for their mid-tier fare

Armed with this, you can now respond—either with pricing adjustments, promotional messaging, or RM availability tweaks.

Conclusion

The booking curve is one of the most valuable tools in an airline’s arsenal. It helps predict demand, optimize availability, and track whether your strategy is working in real time.

But no booking curve exists in isolation. Real-world passenger behavior is influenced by the competitive environment—and understanding that environment is where PriceEye delivers the insights that RM and pricing teams rely on to stay ahead.

Next, we could explore how airlines manage overbooking and no-shows—and how forecasts, booking curves, and fare rules all play a role in balancing risk and revenue.