Vacation Rentals - Colombia

Colombia

Highlights

Colombia's Vacation Rentals market is projected to reach a revenue of US$633.50m in 2024.
The revenue is expected to exhibit an annual growth rate (CAGR 2024-2029) of 3.42%, resulting in a projected market volume of US$749.30m by 2029.
Additionally, the number of users in this market is expected to rise to 9.63m users by 2029.
The user penetration was recorded at 15.2% in 2024 and is predicted to drop marginally to 17.9% by 2029.
The average revenue per user (ARPU) is expected to remain steady at US$79.37.
Furthermore, in the Vacation Rentals market sector, online sales are estimated to account for 74% of the total revenue by 2029.
It is noteworthy that in global comparison, United States is expected to generate the most revenue, amounting to US$20bn in 2024.
Colombia's Vacation Rentals market is seeing a rise in popularity among international tourists seeking unique accommodations in vibrant cities like Cartagena and Medellin.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Colombia has been experiencing a significant growth in recent years, driven by various factors that have shaped the industry in the country.

Customer preferences: Travelers in Colombia are increasingly seeking unique and authentic experiences, leading to a growing demand for vacation rentals over traditional hotels. Customers are looking for more space, privacy, and flexibility, which vacation rentals can offer compared to standard accommodations.

Trends in the market: One notable trend in the Colombian Vacation Rentals market is the rise of online platforms that connect property owners with travelers, making it easier for both parties to find suitable matches. This trend has opened up a wider range of options for customers and has contributed to the overall expansion of the market.

Local special circumstances: Colombia's diverse geography and rich cultural heritage make it an attractive destination for both domestic and international tourists. The country's popularity has been increasing steadily, driving the demand for vacation rentals in popular tourist destinations such as Cartagena, Medellin, and Bogota. Additionally, the government's efforts to promote tourism and improve infrastructure have further boosted the Vacation Rentals market in Colombia.

Underlying macroeconomic factors: The Colombian economy has been growing steadily, leading to an increase in disposable income among the population. This has translated into higher spending on travel and accommodation, including vacation rentals. Additionally, the country's stable political environment and improved security situation in recent years have helped attract more tourists, further fueling the growth of the Vacation Rentals 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.