FAQ - FREQUENTLY ASKED QUESTIONS
INTL AIRPORT OVERVIEW REPORT
2) I DON'T UNDERSTAND THE DATES?
4) HOW DOES REVENUE SORT WORK?
5) WHAT IS THE TRAFFIC DATA SOURCE?
1) I CAN'T SEE THE DATA?
This data is available to INTL TIER and above. If no traffic is reported during the period that qualify the report will be blank. This city is shown as an airport with international traffic history and is on the report calendar, but there may be periods with no data.
2) I DON'T UNDERSTAND THE DATES?
Demand data reporting lags about 5-9 months. This reports takes the most recent quarter of demand data (as well as showing the same quarter a year earlier) and removes any market served in the same upcoming quarter. For example, if 4th Quarter 2020 is the newest quarter of demand, this report shows largest unserved markets for 4th Quarter 2021 based on schedule from 4Q2021 and demand from 4Q2020.
3) WHAT IS THE FORMAT?
#RANK=Ranking by either Traffic Size or Forecast Revenue Adjusted for Distance. Gray is Served, Black is Unserved.
MARKET=Alphabetical of the IATA airport codes of the origin and destination airports of the market. Gray is Served, Black is Unserved.
PDEW=Per Day Each Way projected passenger traffic for the Year and Quarter listed
FARE GRADE=Explained HERE
ROUNDTRIPS=Number of roundtrip departures/day in the same upcoming quarter
4) HOW DOES REVENUE SORT WORK?
Market revenue is stage adjusted using an industry standard formula for comparing fares over distance. Such a formula is necessary because fares and costs do not scale with distance. There is a fixed cost to depart and reach cruising altitude related to airport costs, maintenance cost related to one operating cycle, taxi time, and increased fuel burn to reach cruising altitude (as well as the same costs for a landing). These costs do not change by distance, so a fare of $1000 for 1000 miles is much more profitable than a fare of $500 for 500 miles.
5) WHAT IS THE TRAFFIC DATA SOURCE?
There are legal restrictions imposed by the DOT that makes release of international DB1B demand data on a website like this infeasible. There are also release restrictions on most other international demand sources, so I made a new source. At its essense I purchase booking site search data and compare booking attempts for Airport A to Airport B (domestic) to Airport C (international). I then retrieve domestic O&D demand for A to B and create C using the ratio of booking site searches between A to B and A to C. There are also correcting mechanisms which are as follows: a QSI for world schedules that can also approximate demand based on the number of connecting opportunities between two points, use of DOT P1 and DOT T1 and DOT T100 which are not restricted to adjust by airline demand by international region level, and finally correction of the QSI traffic estimate using T100 from past dates that are public released and adjusted forward using CBP passenger throughput by hour and by terminal for each arrival airport. All of these together make a pretty robust estimate and while I cannot provide DB1B international data, from observing both data sources they are usually within 15% of the U.S. carrier demand. Foreign carrier demand is largely based on the same metrics with DOT P1 and T1 data applied to all carriers (not just U.S. carriers) on the aggregate by region to adjust foreign carrier demand and fares.
6) WHAT IS THE SOURCE FOR FARES?
This data is less reliable than the traffic data. It is based largely on low volume screen scraping of fare data from booking sites and using differentials between airlines and destinations (e.g. if Amsterdam was stage adjusted cheaper than Paris in the sample scraped markets by -13% that differential would be part of the fare calculation), coupled with use of P1 and T1 which average fare by region for U.S. carriers without legal restriction, and finally other hints are obtained by using domestic fare data (e.g. fares are higher in ATL for domestic flights than MCO would carry forward for intl, if CLT has a higher stage adjusted average fare than the national average that also goes into the calculation), and finally fares are adjusted based on load factors on international routes from our load factor reports with lower load factor routes typically seeing a negative fare adjustment. Foreign carrier fares are heavily dependent on minimal screen-scraping and may be dramatically overstated for a carrier like Volaris, Norse, or Eurowings that have below average fares.
7) ISN'T THERE NEWER DATA?
Because we use year earlier demand data for a quarter to compare unserved markets in that same future quarter, there can be problems with airlines that do not publish their schedule far enough ahead to appear in the proper upcoming quarter. For example, as of September 2nd, 2021, Southwest did not have a schedule published beyond the first few days of January 2022. So, while 1Q2021 demand data has been available for quite a few weeks, this report cannot roll forward to checking unserved markets for 1Q2022 because all Southwest monopoly markets would qualify as unserved.
8) WHAT IS THE MAP?
The map shows non-stop routes planned for the future quarter noted. Only the top 50 largest domestic markets are shown in the data above. A market may be served non-stop and be on the map, but not appear in the data because it is not in the top 50 largest markets. Conversely, an unserved market may appear in the data, but not appear in the map because it does not have scheduled non-stop during the period.
9) WHAT ARE THE FARE GRADES?
FARE GRADES are a rating based on the stage adjusted fare for the routing compared to all international fares to/from the United States. Fares 30+% below the stage adjusted average are rated POOR, 15-30% below average are rated WEAK, 15% below average to 15% above average are rated FAIR, 15-30% above average are rated GOOD, and more than 30% above average are rated GREAT.
10) WHY WERE EXACT FARES REPLACED WITH FARE GRADES?
This was changed for two main reasons. User feedback was that fares were too high relative to fares on other domestic reports creating the impression that international was much more profitable than domestic which was exaggerated relative to reality because of calculation differences. Domestic data taken from DOT DB1B includes zero fare frequent flier redemption tickets which lower overall fares. Thus, comparison to international fares vs domestic fares gathered mostly from screen scraping created inconsistencies. Additionally, screen scraping an exact fare requires a lot more successful scraping than a relative fare level. Increasing difficulty successfully screen scraping fares also lead to the change. A general level of fare accuracy is much easier to achieve than an exact value.