Seasonality is arguably the most defining characteristic of a short-term vacation rental market. While some markets earn the vast majority of their revenue over just a small time frame, others experience a steady, year-round flow of bookings and revenue.
What’s true of demand is also true of vulnerability. Even though the income for those highly seasonal markets can be quite lucrative, it can be a gamble relying on such a short time frame.
If this adage wasn’t apparent before, it certainly is now.
Worldwide lockdowns due to the Coronavirus have caused extraordinary losses for many short-term rental markets around the world — but the shock hasn’t been distributed evenly. As we saw in last week’s report on how the pandemic is causing booms for rural STR markets, many places are strangely benefiting from the virus’s onset.
In this report, we’re highlighting which markets around the world are most and least impacted by COVID-19. In other words, which markets are most reliant on spring seasonality, and which are not?
North America’s diverse climate, large events, and strong roots in spring break culture make it particularly vulnerable to the current pandemic. On the other hand, it’s not without its fair share of markets earning very little springtime income compared to the rest of the year. Here are the most and least vulnerable cities.
Note: For all charts below, data is from 2019. Ranked by the percentage of springtime revenue (March-May) compared to the remaining 9 months of the year. For example, a city ranked as 50% earned 50% more revenue in the 3-month stretch from March to May than it did during the other 9 months. Data is from Airbnb, and cities are filtered by those who earned at least $20M in 2019.
Given the virus’s timing, some of the worst-hit cities include those with large events (Indio, CA and New Orleans, LA), famous spring break beaches, and many locations throughout Florida.
Conversely, destinations relatively immune to the virus include true summertime getaways (like the Hamptons and Nantucket), large cities with unfavorable weather (Seattle, Vancouver, Montreal), and mountain resorts that are more reliant on winter and summer seasonality (Breckenridge, Park City, Steamboat).
The range of seasonality in Europe is far less extreme than it is in North America. In general, European cities are less reliant on springtime revenues than their North American counterparts. In fact, the top 20 most seasonal markets in Europe average just 27% versus over 80% in North America.
On the other end of the spectrum, the top European cities receive far less of their relative revenue from spring seasonality than those in North America.
The virus’s starting point presents an even more intriguing relationship with seasonality. Across the board, there aren’t many cities particularly exposed by a spring-heavy tourist season. The ones that are, however, really are. Ho Chi Minh City, Kowloon (Hong Kong), and Bali stand out leagues among the rest.
Massive urban metropolises like Shanghai, Manila, Beijing, Seoul, and Chiang Mai benefit from a very balanced, year-round travel season.
Africa, Oceana, and South America
Below are the distributions for the three continents of Africa, Oceana, and South America.
While data for Africa is fairly distributed, Oceana and South America are flip-flopped by nature of being in the Southern hemisphere. March, April, and May are fall months that see fewer travelers. Thus, many vacation rental markets are at less risk to the springtime outbreak.
Estimates on the expected duration of the Coronavirus run from a handful of weeks to well into the year 2021. For now, many experts are projecting a 3-month trajectory. If all social distancing efforts pan out, the travel industry could regain its bearings by mid-summer.
If that’s the case, the 2019 seasonality data above will likely align with the damage done in 2020. Vacation rental managers reliant on this 3-month time frame may be forced to rethink their strategies.
If you’re serious about tracking your market’s recovery, dive into MarketMinder to leverage more real-time, future-looking data.