Vacation Rentals - Senegal

Senegal

Highlights

Senegal is projected to generate a revenue in the Vacation Rentals market amounting to US$36.70m in 2024.
The revenue is expected to grow annually at a rate of 6.28%, resulting in a projected market volume of US$49.76m by 2029.
It is also expected that the number of users in the Vacation Rentals market will amount to 2.06m users by 2029, with user penetration reaching 10.0% by that year.
The average revenue per user (ARPU) is projected to amount to US$30.95.
By 2029, 68% of the total revenue in this sector will be generated through online sales.
It is worth noting that United States will generate the most revenue in the Vacation Rentals market globally, with a projected amount of US$20bn in 2024.
Senegal's Vacation Rentals market is gradually gaining momentum with an increase in demand for beachfront properties and eco-tourism experiences.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

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

Customer preferences: Travelers in Senegal are increasingly seeking unique and authentic experiences, driving the demand for vacation rentals over traditional hotel stays. Tourists are looking for accommodations that offer a more personalized and local experience, allowing them to immerse themselves in the culture and lifestyle of the destination.

Trends in the market: One notable trend in the Senegalese vacation rentals market is the rise of eco-friendly and sustainable properties. Travelers are becoming more conscious of their environmental impact and are actively seeking accommodations that prioritize sustainability. This trend is in line with global efforts towards responsible tourism and green practices.

Local special circumstances: Senegal's diverse landscape and rich cultural heritage make it a unique and attractive destination for tourists. From the bustling markets of Dakar to the serene beaches of Saly, the country offers a wide range of experiences for visitors. This diversity contributes to the growing popularity of vacation rentals, as travelers look for accommodations that cater to their specific interests and preferences.

Underlying macroeconomic factors: The growing economy and increasing investment in tourism infrastructure in Senegal have also played a role in the expansion of the vacation rentals market. As the country continues to develop its tourism sector, more travelers are discovering the beauty and charm of Senegal, leading to a higher demand for alternative accommodations. Additionally, the rise of digital platforms and online booking services has made it easier for property owners to list their rentals and for travelers to find and book them, further fueling the growth of the 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.