Vacation Rentals - Southern Africa

Southern Africa

Highlights

Southern Africa is expected to witness significant growth in the Vacation Rentals market.
By 2024, the projected revenue for the region is estimated to reach US$446.40m.
The revenue is further forecasted to grow annually at a rate of 5.11% from 2024 to 2029, resulting in a projected market volume of US$572.80m by 2029.
Additionally, the number of users in the Southern African region is expected to increase to 10.75m users by 2029.
As of 2024, the user penetration rate is 12.5% and is expected to reach 14.6% by 2029.
The average revenue per user (ARPU) is estimated to be US$50.85.
Notably, 64% of the total revenue generated in the Vacation Rentals market in the region is expected to be through online sales by 2029.
It is interesting to note that in global comparison, United States is projected to generate the most revenue in the Vacation Rentals market, with a forecasted revenue of US$20bn in 2024.
In Southern Africa, vacation rental demand is increasing due to the region's diverse landscape and cultural experiences.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Southern Africa is experiencing significant growth and development, driven by various factors influencing customer preferences, market trends, local special circumstances, and underlying macroeconomic factors.

Customer preferences: Travelers in Southern Africa are increasingly seeking unique and authentic experiences, leading to a growing preference for vacation rentals over traditional hotels. The flexibility, privacy, and local charm offered by vacation rentals appeal to tourists looking to immerse themselves in the culture and environment of the destinations they visit.

Trends in the market: In countries like South Africa and Namibia, there is a noticeable trend towards the development of luxury vacation rental properties to cater to high-end travelers seeking exclusive and upscale accommodation options. Additionally, the rise of digital platforms and online booking services has made it easier for property owners to market their rentals and for travelers to find and book vacation homes.

Local special circumstances: Countries in Southern Africa, such as Mozambique and Mauritius, are known for their stunning beach destinations and natural attractions, making them popular choices for vacation rentals. The proximity to wildlife reserves and national parks in countries like Botswana and Zimbabwe also contributes to the appeal of vacation rentals in the region, offering tourists a unique opportunity to experience nature up close.

Underlying macroeconomic factors: The overall economic stability and growth in Southern Africa have boosted the tourism industry, leading to an increase in both domestic and international travel. As disposable incomes rise and travel becomes more accessible, the demand for vacation rentals is expected to continue growing. Additionally, government initiatives to promote tourism and infrastructure development in the region are creating a conducive environment for the expansion 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.