Vacation Rentals - Kuwait

Kuwait

Highlights

By 2024, it is projected that the revenue in Kuwait's Vacation Rentals market will reach US$244.60m.
Furthermore, the revenue is expected to exhibit an annual growth rate (CAGR 2024-2029) of 3.00%, which will result in a projected market volume of US$283.60m by 2029.
It is also expected that the number of users will amount to 1.81m users by 2029, with user penetration being 36.1% in 2024 and predicted to reach 39.9% by 2029.
The average revenue per user (ARPU) is expected to amount to US$155.90 in Kuwait's Vacation Rentals market.
Additionally, it is anticipated that 84% of the total revenue will be generated through online sales by 2029.
It is noteworthy that in comparison to other countries, United States will generate the most revenue, which is estimated to be US$20bn in 2024.
The Vacation Rentals market in Kuwait is growing as more locals seek domestic tourism options due to travel restrictions.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Kuwait has been experiencing significant growth and development in recent years.

Customer preferences: Travelers in Kuwait are increasingly looking for unique and personalized accommodation options that offer a more authentic experience compared to traditional hotels. They are seeking vacation rentals that provide a sense of home away from home, with amenities such as fully equipped kitchens, private pools, and spacious living areas.

Trends in the market: One notable trend in the Kuwaiti Vacation Rentals market is the rising popularity of luxury villas and beachfront properties. High-end travelers are willing to pay a premium for exclusive and extravagant rental options that cater to their discerning tastes. Additionally, there is a growing demand for properties that can accommodate large groups or families, reflecting a shift towards group travel in the region.

Local special circumstances: Kuwait's strategic location in the Middle East, with its proximity to popular tourist destinations and business hubs, has contributed to the growth of the Vacation Rentals market. The country's stable economy and increasing investment in tourism infrastructure have also played a role in attracting both domestic and international travelers to explore the diverse range of rental properties available.

Underlying macroeconomic factors: The increasing disposable income among Kuwaiti residents, coupled with a growing preference for experiential travel, has fueled the demand for vacation rentals in the country. Additionally, government initiatives to promote tourism and improve the overall visitor experience have created a favorable environment for the expansion of the Vacation Rentals market in Kuwait.

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.