Load factor is widely used within the commercial airline industry to measure the percentage of available seats that are occupied by passengers. It is a simple principle that you would want to sell most or all of your available seats on the plane. Hence a high load factor is the desired outcome by airlines.
But do not be fooled by this metric on it's own. Airlines can achieve a high load factor by dropping prices to fill planes which are seasonally showing week demand or due to competition. Load factor plus price/yield of the tickets are two of the important factors governing the total profitability of the flight.
Lets look at load factors and yields in this example:
Air Ribero and Air Busto are two identical airlines flying from Seattle to Denver on identical 100 seater all economy class aircraft.
Air Ribero - sold 90% of the seats hence has a load factor of 90%
The average price of the 90 tickets sold by Air Ribero was $200 each
The total revenue generated by the 90 Air Ribero seats @ $200 per ticket = $18,000
Air Busto - only sold 80% of the seats on their aircraft giving them a load factor of 80%
The average price of an Air Busto ticket was slightly higher than Air Ribero.
The average price of the 80 tickets sold by Air Busto was $250 each
The total revenue generated by the 80 seats @ $250 per ticket = $20,000
So Air Busto generated more revenue by selling fewer seats than Air Ribero. This example plays out daily in highly competitive markets between airlines.
Air Busto was selling seats at $250 each, Air Ribero decided to undercut that price by $50, thus attracting more customers which yielded them a higher (90%) Load factor than Air Busto which achieved only 80% Load Factor. However even with a lower load factor of 80%, Air Busto generated $2000 more for that one flight. This was an over simplified example of how airlines revenue manage flights, routes etc. The reality is that competing airlines dynamically adjust prices based on competitor activities in the market.
When Air Ribero dropped its price to $200 per ticket, it would be highly likely and probable that Air Busto would drop it's fare to match or even slightly undercut it's competitor. There would be situations where carriers do not price match if they have a superior product or service that they know customers are willing to pay for, even down to the flight departure time of 10-15 minutes during peaks hours can determine who has the product advantage that can be milked.
Controlling capacity also is a vital component that Network planners have to manage at airlines. Putting too many aircraft on a single route and flooding the market with lots of available seats can negatively impact the airlines profitability and produce low load factors. Simple supply and demand logic applies. High supply of a product traditionally drives down prices, which is extremely good for consumers but could degrade the airlines profitability. Conversely too few seats in a market coupled with high demand could drive up ticket prices and higher load factors. Revenue managers and network planners have to get that balance right. Airlines use mountains of different data points to create the magical formula that nets high load factors and high yields which gives them the edge over the competition. Technology such as ML/AI based tools is also going to provide a distinct advantage to airlines who can finesse that elusive algorithm that ingests and processes billions of data points, processes it and provides realtime capacity and pricing outputs allowing airlines to adjust prices, capacity and schedules dynamically. We are not quite there yet, but "Alexa optimize my Seattle to Denver Air Ribero flight 001 on 17th October 2023" might not be too far away.
Now you have a basic understanding of Load Factor. Let's look at actual data published by the US Department of Transport comparing the Load factors for all US carriers between Jan-Jun 2023 v 2019 baseline. (pre COVID baseline).
Headlines :
Load factors overall in 2023 so far are lower than back in 2019. This is true of domestic as well as International flights.
However International load factors picked up in the summer of 2023 which is a positive trend as International flights typically generate higher yielding customers specially from premium cabins. Historically, over the last 10 years, US airlines have mostly generated load factors greater than 80% for domestic and international flights. Hence the 2023 load factor data seems to indicate we are over the COVID impact relative to this metric.
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