Vacation Rentals - Spain

  • Spain
  • Spain's Vacation Rentals market is anticipated to experience a rise in revenue, with a projection of US$3.44bn by 2024.
  • The expected annual growth rate (CAGR 2024-2028) of 1.14% indicates a promising future, with a projected market volume of US$3.60bn by 2028.
  • The number of users is also expected to increase, with an estimation of 19.56m users by 2028.
  • In 2024, user penetration is calculated at 41.0%, which is expected to rise to 41.4% by 2028.
  • The average revenue per user (ARPU) is expected to be US$176.70.
  • It is predicted that 84% of the total revenue in the Vacation Rentals market will come from online sales by 2028.
  • In contrast, United States is expected to generate the most revenue globally, with US$19,770m in 2024.
  • Spain's Vacation Rentals market is seeing a rise in demand for luxury villas with private pools and outdoor spaces due to COVID-19 safety concerns.

Key regions: Vietnam, Malaysia, Indonesia, Germany, United Kingdom

Region comparison

Analyst Opinion

Vacation RentalsĀ are becoming increasingly popular. Rooms, apartments or vacation homes can often be rented at very short notice, which increasingly represents an attractive accommodation alternative for tourists, especially from the USA and Europe.


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.


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.


  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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