Vacation Rentals - Portugal

Portugal

Highlights

By 2024, the Vacation Rentals market in Portugal is projected to reach a revenue of US$308.30m.
Looking ahead, the market is expected to display a Compound Annual Growth Rate (CAGR) of 3.40% between 2024 and 2029, resulting in a projected market volume of US$364.30m by 2029.
Furthermore, the number of users in this market is expected to reach 2.15m users by 2029.
In 2024, user penetration is expected to be 19.6%, which is projected to increase to 21.3% by 2029.
The average revenue per user (ARPU) is anticipated to be US$153.70.
Also, 83% of the total revenue generated in the Vacation Rentals market in Portugal is expected to come through online sales by 2029.
It is interesting to note that, in comparison to other countries worldwide, United States is expected to generate the most revenue in the Vacation Rentals market.
The projected revenue for the United States in 2024 is US$20bn.
Portugal's Vacation Rentals market is thriving, with a wide range of properties available in popular coastal destinations like the Algarve.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Portugal, known for its stunning coastlines, rich history, and vibrant culture, has seen a significant growth in the Vacation Rentals market.

Customer preferences: Travelers are increasingly seeking unique and authentic experiences, leading to a rise in demand for vacation rentals over traditional hotels. The flexibility, privacy, and often lower cost of vacation rentals appeal to a wide range of tourists, from families to solo travelers.

Trends in the market: One notable trend in the Portugal vacation rental market is the increasing popularity of properties in coastal regions such as the Algarve, where visitors can enjoy beautiful beaches and sunny weather. Additionally, the growth of digital platforms connecting property owners with travelers has made it easier for individuals to list and book vacation rentals, contributing to market expansion.

Local special circumstances: Portugal's favorable climate, diverse landscapes, and relatively affordable cost of living compared to other Western European countries make it an attractive destination for both property owners and tourists. The country's government has also implemented regulations to ensure quality and safety standards in the vacation rental market, boosting confidence among travelers.

Underlying macroeconomic factors: The steady growth of Portugal's tourism industry, supported by initiatives to promote the country as a year-round destination, has driven the demand for vacation rentals. Additionally, the country's improving infrastructure, including transportation networks and digital connectivity, has made it easier for tourists to explore different regions and book accommodations, further fueling the growth of the vacation rental market.

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and sales channels of vacation rentals.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market. As a basis for evaluating markets, we use financial reports, the Global Consumer Survey, third-party studies and reports, data from industry associations (e.g., UNWTO), and price data of major players in respective markets. To estimate the number of users and bookings, we furthermore use data from the Statista Consumer Insigths Global survey. In addition, we use relevant key market indicators and data from country-specific associations, such as country-related GDP, demographic data (e.g., population), tourism spending, consumer spending, internet penetration, and device penetration. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, ARIMA, which allows time series forecasts, accounting for stationarity of data and enabling short-term estimates. Additionally, simple linear regression, Holt-Winters forecast, and exponential trend smoothing methods are applied. A k-means cluster analysis allows for the estimation of similar countries. The main drivers are tourism GDP per capita and respective price indices.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.