Vacation Rentals - Equatorial Guinea

  • Equatorial Guinea
  • Equatorial Guinea is projected to generate a revenue of US$6.12m in the Vacation Rentals market by 2024.
  • The revenue is expected to witness an annual growth rate (CAGR 2024-2029) of 2.72%, leading to a projected market volume of US$7.00m by 2029.
  • By 2029, the number of users in the Vacation Rentals market is expected to be 167.20k users, with a user penetration of 8.5%.
  • In 2024, the user penetration is 7.4%.
  • The average revenue per user (ARPU) is expected to be US$47.38.
  • In the Vacation Rentals market, 68% of total revenue is projected to be generated through online sales by 2029.
  • It is worth noting that, in global comparison, United States is expected to generate the most revenue in the Vacation Rentals market, with a projected revenue of US$20,270m in 2024.
  • Despite being a small player in the Vacation Rentals market, Equatorial Guinea offers unique and luxurious options for travelers seeking an unconventional experience.

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

 
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Analyst Opinion

The Vacation Rentals market in Equatorial Guinea is experiencing a shift in consumer preferences and market dynamics, driven by various factors influencing the industry.

Customer preferences:
Travelers in Equatorial Guinea are increasingly seeking unique and authentic experiences, leading to a growing demand for vacation rentals over traditional hotel accommodations. Customers are looking for personalized and immersive stays that allow them to connect with the local culture and environment.

Trends in the market:
One of the notable trends in the Equatorial Guinea vacation rentals market is the rise of eco-friendly and sustainable properties. Travelers are showing a preference for accommodations that prioritize environmental conservation and offer eco-conscious amenities. This trend aligns with global movements towards responsible tourism and sustainable travel practices.

Local special circumstances:
Equatorial Guinea's unique geographical features, including its diverse landscapes and rich biodiversity, present opportunities for vacation rental owners to offer a wide range of experiences to guests. From beachfront villas to jungle retreats, the country's natural beauty attracts travelers seeking off-the-beaten-path destinations.

Underlying macroeconomic factors:
The development of the vacation rentals market in Equatorial Guinea is also influenced by macroeconomic factors such as government policies, infrastructure investments, and international tourism trends. Economic stability, political reforms, and improvements in transportation infrastructure can contribute to the growth of the market by attracting more visitors to the country. Additionally, partnerships with global booking platforms and marketing initiatives can help raise awareness of Equatorial Guinea as a vacation rental destination.

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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