Vacation Rentals - Cameroon

Cameroon

Highlights

Cameroon is projected to witness a substantial revenue growth in the Vacation Rentals market, with revenue expected to reach US$65.85m by 2024.
The market is anticipated to show an annual growth rate (CAGR 2024-2029) of 4.08%, resulting in a projected market volume of US$80.41m by 2029.
In Cameroon's Vacation Rentals market, the number of users is expected to reach 2.17m users by 2029.
User penetration is expected to increase from 5.3% in 2024 to 6.5% by 2029.
The average revenue per user (ARPU) is also expected to increase to US$41.94.
Furthermore, it is estimated that by 2029, 62% of total revenue in the Vacation Rentals market will be generated through online sales.
It is interesting to note that in global comparison, United States is expected to generate the most revenue (US$20bn in 2024) in the Vacation Rentals market.
Cameroon's Vacation Rentals market is still in its early stages, with limited options and a strong preference for traditional hotels among tourists.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Cameroon is experiencing a significant growth trajectory.

Customer preferences: Travelers in Cameroon are increasingly seeking unique and authentic experiences, leading to a rise in demand for vacation rentals that offer a more personalized stay. Customers are looking for accommodations that provide a sense of immersion in the local culture and environment, driving the popularity of vacation rentals over traditional hotels.

Trends in the market: One noticeable trend in the Vacation Rentals market in Cameroon is the diversification of offerings to cater to different traveler preferences. From cozy cottages in rural areas to modern apartments in urban centers, property owners are expanding their portfolios to attract a wider range of customers. Additionally, the integration of online booking platforms has made it easier for travelers to discover and book vacation rentals, contributing to the market's growth.

Local special circumstances: Cameroon's rich cultural heritage and diverse landscapes make it an attractive destination for both domestic and international travelers. The country's natural beauty, including national parks, beaches, and mountains, provides a unique backdrop for vacation rentals. Additionally, the warm hospitality of the Cameroonian people adds to the overall appeal of staying in a vacation rental while exploring the country.

Underlying macroeconomic factors: The growing tourism industry in Cameroon, coupled with increasing disposable incomes among the middle class, has fueled the demand for vacation rentals. As more people seek affordable yet comfortable accommodation options, the Vacation Rentals market in Cameroon is poised to continue its upward trajectory. Additionally, government initiatives to promote tourism and improve infrastructure are creating a conducive environment for the market to thrive.

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.