Vacation Rentals - Kenya

  • Kenya
  • In Kenya, the Vacation Rentals market is expected to generate a revenue of US$281.00m by 2024.
  • Looking ahead, the market is expected to grow annually at a rate of 6.52% between 2024 and 2029, resulting in a market volume of US$385.30m in 2029.
  • The number of users in this market is projected to reach 9.08m users by 2029.
  • In 2024, the user penetration rate is expected to be 10.8%, increasing to 14.7% by 2029.
  • The average revenue per user is forecasted to be US$46.27.
  • By 2029, online sales are expected to contribute to 59% of the total revenue in the Vacation Rentals market in Kenya.
  • It is noteworthy that in global comparison, United States is projected to generate the highest revenue of US$20,270m in 2024.
  • Kenyan Vacation Rentals market is seeing a rise in demand for eco-friendly accommodations that offer a unique and immersive experience.

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

 
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Analyst Opinion

The Vacation Rentals market in Kenya is experiencing a notable growth trajectory, driven by various factors that cater to the evolving preferences of travelers and the unique local circumstances present in the country.

Customer preferences:
Travelers in Kenya are increasingly seeking unique and authentic experiences, which has led to a rise in demand for vacation rentals over traditional accommodation options. The desire to immerse oneself in the local culture and lifestyle is a key driver for choosing vacation rentals, as it allows for a more personalized and intimate stay.

Trends in the market:
One prominent trend in the Kenyan vacation rentals market is the growing popularity of eco-friendly and sustainable properties. Travelers are showing a preference for accommodations that are environmentally conscious and support local communities. This trend aligns with the global shift towards responsible tourism practices and reflects a greater awareness of sustainability among consumers.

Local special circumstances:
Kenya's diverse landscape and rich wildlife make it a prime destination for nature lovers and adventure seekers. This has influenced the vacation rentals market, with properties offering proximity to national parks, beaches, and other natural attractions gaining popularity. Additionally, the country's vibrant cultural heritage and warm hospitality contribute to the appeal of vacation rentals as a way to experience the local way of life.

Underlying macroeconomic factors:
The growth of the vacation rentals market in Kenya is also supported by favorable macroeconomic conditions, including increasing disposable incomes and a growing middle class. As more Kenyans have the means to travel domestically and explore their own country, the demand for vacation rentals is expected to continue rising. Moreover, the government's efforts to promote tourism and infrastructure development further enhance the attractiveness of Kenya as a travel 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
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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