Expedia, the travel technology giant, has analyzed its trove of data to identify key trends in air travel.
The data was consolidated primarily from the Airlines Reporting Corporation, with additional source data from IATA (the airline group), Diio Mi (an airport market intelligence company) and ATPCO (the fare filing operation).
With the rise of the whiny traveler, it’s essential to understand how this “new premium” travel experience affects traveler expectations and overall satisfaction.
Here are three things that Expedia has learned from its airfare data analysis -- including 8 billion searched across more than 300,000 unique routes.
CORRECTION: 15th of Dec 2015. Some of the figures in the original article were taken from a previous year's edition of the report. We've corrected the numbers below. Sorry.
Timing continues to be greatest indicator of fare
Suppliers and startups are always angling to tell consumers the best day to book flights to snag the more affordable fares. This information is always useful to those in the industry looking to understand the ebbs and flows of airline fare pricing.
Expedia challenges the age-old maxim that earlier purchasers save more money, confirming that a 2 months advance purchase is generally the cheapest. This can lead to 20% to 31% savings on popular domestic routes at around 57 days, although prices tend to increase dramatically within the two weeks before departure.
The savings has shrunk in the past year. In 2014, the comparable figures were a possible 43% to 56% savings on popular domestic routes when booking around 57 days in advance.
However, this only holds true for domestic travel. International flights hold to a much lower average ticket price far in advance of travel. Then the price increases dramatically at the 60-day mark and continues to rise.
While domestic ticket prices drop in price up until 2 months prior to travel, international fares just continue to rise past that mark. The valley for international travel sits at 171 days of advance purchase.
This data can be especially illuminating for those looking to encourage bookings by travelers, with the data acting as anchors for retargeting or custom audience marketing. For example, an airline could profile certain demographics of travelers likely to book at specific moments in this graph and then push marketing across paid search and social media to that demographic.
Increased capacity is meeting demand
There are very real fare implications when demand is matched with increased capacity. As the airlines add more seats to meet the increased appetite for air travel, this means that fares are relatively stable.
However, given the continued drop in oil prices, travelers haven’t enjoyed a commensurate drop in average fare prices.
This drop might finally be trickling into the world of high-octane aviation fuels, as airline hedges cycle through and airlines realize windfall profits.
The combination of lower fuel costs and demand-matched capacity means that airliners have increased flexibility in 2016. While not necessarily dropping fares across the board, airlines now have a significant lever for competitive price matching.
This kind of direct competition between airlines has been tampered by consolidation over the past decade, meaning that travelers might again see more favorable fares as airlines use the increased margins from cheap fuel to undercut competitors on certain routes.
This played out in 2015, where global fares dropped an average of 8 percent between October 2014 and October 2015. Summer fares were especially cheap, indicating deeper competition during that peak travel time.
Expedia predicts this trend to continue, saying:
“Most air ticket prices declined this year, and looking forward to 2016, we expect prices will continue to trend downward as airlines continue to add capacity.”
The overall drop in average air ticket prices alongside the capacity increases bodes well for travelers, while still leaving space for profitably undercutting competitors’ fares for airlines.
Statistical models can yield actionable data for travelers
Within those 8 billion searches lies a lot of predictive value. As Expedia continues to grow, it can offer deep analysis of trends in a nearly-live basis.
Metasearch sites such as Kayak and Skyscanner have earned their stripes with price forecast tools, and startups such as Hopper have hung their hats entirely on churning out predictions on when to “fly and buy.”
New tool
Expedia has also announced a new tool that will deploy statistical analysis to predict the likelihood that a particular fare will change.
The tool uses fare information from 14 days prior to a search to create a “confidence rating,” or a percentage chance that a fare will rise or fall. Expedia parses real-time data from all users searching on the site, so the data improves as more users search. This leads to the tool’s primary disadvantage:
“Perhaps the only downside: if you search fares on a particular route that is lightly traveled, the tool may not have enough comparative data to give you a confidence rating at all.”
See the Expedia ARC report yourself, here.