Business travel lags leisure early in coronavirus air travel recovery

• Passengers are returning to the skies, but recovery remains slow
• Online travel sentiment suggests leisure traffic is returning stronger than business traffic, with those visiting family and relatives as the most likely to fly.
• Even with increased interest in summer vacations, leisure travelers are likely to drive

Three months after COVID-19 nearly shut down flying in the United States, people are now slowly returning to travel. Already, some carriers are beginning to plan increases in capacity for the June schedule. Dallas-based Southwest Airlines, reported plans to increase capacity to 55% of that from 2019 numbers and by the end of the year will resume a full schedule by the end of the year. While aggressive, it still expects flights to be less than half full this summer.

As flights return, the challenge is now to understand how demand is returning. Questions also persist about various segments of traffic, as leisure and business travel trends diverge. The rate at which each segment recovers will drastically affect the overall ability for the airlines to recover.

Related: The airlines are staring down a slow and uneven recovery from coronavirus

As traffic inevitably begins its long climb back to 2019 levels, the warranted optimism around the “green shoots” does require a healthy dose of realism. Even though traffic is increasing five to ten times April levels, this is more an indication of just how low April numbers were.

Direct booking information is highly proprietary, but there are various clues that can be drawn from an unlikely source to begin predicting how passengers may return to the skies. Closely examining our collective lives on social media offers a unique set of indicators. In a new model developed by Visual Approach and presented in this TAC Analysis, the public’s online searching, posting, and tweeting patterns prove strongly correlated with travel demand.

Using several techniques including natural language processing, a type of artificial intelligence designed to convert human language into meaningful data, online behavior on a topic is aligned with the overall activity of the market. The recent collapse of traffic from the pandemic created an opportunity to accelerate this research as it became evident which terms and topics were directly associated with air travel. The daily-published Transportation Security Administration screening data in the U.S. provided a metric with which to compare the results, allowing for direct comparisons.

The correlations between the calibrated model and TSA screening data is impressive, serving between 90% and 98% confidence. While not direct indications people are booking tickets to fly, the model serves to show that people are beginning to search for, and discuss travel once again.