Six months after the first COVID-19 outbreak in China, the spread of the virus has been effectively contained. What does it mean for the airlines in China? The flight operations rate has recovered from 30% to 80% (as against the last year). Five Chinese airlines rely on our airRM Revenue Management System - to monitor the impact of the pandemic and devise actions for market recovery. In this article, we will explore how these airlines are analyzing their revenue management data for a smooth recovery.
1. Monitor market trends
With the markets changing so swiftly, YOY (year over year) data have become meaningless. In order to keep up with the rapid market changes and catch the fleeting revenue opportunities, Chinese airlines have leveraged the much more dynamic ‘WOW’ data (week over week) to adjust their RM strategies instantly.
For example, the table above shows that both flight load factor and operations rate on July 9th have increased compared to one week prior. This means that most markets are improving. Based on each airline’s networking structure, they drill down to a market-level or flight-level data to complete further comparison analysis in airRM.
2. Monitor booking trends
One airline uses the below graph (on the left-hand side) to track weekly bookings data from the beginning of 2020 to the current week. Week 4 to 7 is when the first outbreak happened in Wuhan and week 25 is the second outbreak in Beijing.
The second graph on the right-hand side plots ‘flown passenger number’ curve and ‘booking number’ curve, with ‘local new COVID-19 cases’ shown in bars. From this graph, analysts can tell that the booking data reveals market trends one week ahead of the passenger flown data. It makes this week critical for airlines to adjust their RM strategies.
3. Analyze recovery pace
Different markets have different pace of recovery.
The following three graphs show the pickup booking numbers in 3 days from 3 flights for Chengdu Airlines – an airRM customer. Flight X shows a relatively stable growing pace, so the RM analyst could gradually increase fares for this flight. Flight Y and flight Z reveal some signals of recovery, but the patterns are not stable, so the analyst can keep a close eye on these flights and avoid batch inventory changes based on subjective evaluations.
A single market could also have different recovery paces based on DOW (day of week).
In China, the booking curves / cycles are much shorter than western markets, and they have been further shortened during the pandemic. In general, most people tend to book tickets within 7 days, so bookings made outside of 7 days are considered as “further-out” bookings. Bookings within 3 days before departure are considered as “close-in” bookings.
Let’s see how an airline can infer this data.
Year 2020 has more booking pickup in 3 days than year 2019. There are two reasons for this: One, passengers tend to book very late during the pandemic. Two, more flights have been cancelled in 2020, so the average pickup number per flight is higher. One could also infer here that the mid-week bookings (Tue. to Thu.) have recovered at a relatively good level, but there are still gaps in weekend bookings. As the demand for weekends comes normally from leisure passengers, one can extract the “further out” booking data from airRM, which are bookings made outside of 7 days. The peaks of further-out bookings in 2019 are for weekend flights, because leisure passengers are more likely to book early. However, the weekend peaks in 2020 are not as obvious as those in 2019. This shows that business demand from weekdays recover faster than leisure demand from weekends.
The airline has come up with a strategy to find the recovery signals by comparing WOW pickup bookings and further-out bookings for different markets and flights:
After making such a strategy, the airline uses airRM inventory change functions to adjust the inventory for these flights.
Don’t miss the recovery signals.
Although full recovery will not happen overnight, we are seeing gradual recovery in some regions. WOW data can immediately reflect the pulse of the market in these uncertain times. We presented in this article how our customers in China are leveraging airRM to swiftly identify recovery signals, seize revenue opportunity and take action, ahead of their competitors. One airRM airline customer, for instance, has seen an 81% increase in WOW flown PAX data, much higher than a competing airline C, with a 64% increase, and another competing airline G, with a 29% increase - both operating in the same market. How are you leveraging your data for revenue management strategies during recovery? We would like to hear from you.