Vacation Rentals - Mongolia

  • Mongolia
  • By the year 2024, Mongolia's Vacation Rentals market is predicted to generate revenue of US$13.67m.
  • The projected market volume is anticipated to reach US$22.61m in 2029, displaying a Compound Annual Growth Rate (CAGR) of 10.59% between 2024 and 2029.
  • In the same year, the number of users in this market is expected to be 252.50k users, with a user penetration of 5.0%, which is predicted to increase to 6.8% by 2029.
  • The average revenue per user (ARPU) is expected to be US$78.08.
  • Additionally, by 2029, 58% of the total revenue in the Vacation Rentals market is expected to be generated through online sales.
  • It is noteworthy that in a global comparison, the highest revenue generation is expected to be United States, with a projected revenue of US$20,270m in 2024.
  • Despite its rich nomadic culture and vast natural landscapes, Mongolia's Vacation Rentals market remains largely undeveloped and untapped.

Key regions: India, Vietnam, Saudi Arabia, Singapore, Germany

 
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Analyst Opinion

The Vacation Rentals market in Mongolia is experiencing a steady growth trajectory, driven by evolving customer preferences, unique local circumstances, and underlying macroeconomic factors.

Customer preferences:
Travelers in Mongolia are increasingly seeking authentic and immersive experiences, opting for vacation rentals that offer a glimpse into the local culture and lifestyle. The demand for unique accommodations such as traditional Mongolian gers or yurts in scenic locations is on the rise, as tourists look for memorable stays off the beaten path.

Trends in the market:
One prominent trend in the Mongolian vacation rentals market is the growth of eco-friendly and sustainable lodging options. Travelers are showing a preference for properties that prioritize environmental conservation and offer opportunities to engage in responsible tourism practices, aligning with global trends towards eco-conscious travel.

Local special circumstances:
Mongolia's vast landscapes and nomadic heritage present a unique opportunity for vacation rental providers to offer one-of-a-kind experiences to guests. The country's rich cultural traditions, including hospitality customs and traditional cuisines, contribute to the appeal of vacation rentals as a way to immerse oneself in the local way of life.

Underlying macroeconomic factors:
The increasing connectivity and accessibility in Mongolia, with improved infrastructure and transportation networks, are facilitating the growth of the vacation rentals market. As the country opens up to international tourism and experiences a steady influx of visitors, the demand for diverse accommodation options, including vacation rentals, continues to expand. Additionally, favorable government policies and initiatives to promote tourism are supporting the development of the hospitality sector, including vacation rentals, in Mongolia.

Methodology

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.

Overview

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