Hotels - Uganda

  • Uganda
  • By 2024, the Hotels market in Uganda is expected to generate a revenue of US$249.30m.
  • The market is projected to grow at an annual growth rate of 6.60% (CAGR 2024-2029), resulting in a market volume of US$343.10m by 2029.
  • By this year, the number of users in the Hotels market is expected to reach 5.30m users, with a user penetration of 5.8% in 2024 and an expected increase to 9.3% by 2029.
  • The average revenue per user (ARPU) is expected to be US$86.54.
  • Online sales are projected to contribute to 62% of total revenue in the Hotels market by 2029.
  • In comparison with other countries, United States is expected to generate the highest revenue in the Hotels market, with a projected revenue of US$110,600m in 2024.
  • Uganda's hotel market is experiencing growth due to an increase in tourism, with a focus on eco-friendly and sustainable accommodations.

Key regions: Vietnam, Indonesia, United Kingdom, Malaysia, Saudi Arabia

 
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Analyst Opinion

Over the past few years, the Hotels market in Uganda has shown significant growth and development.

Customer preferences:
Customers in Uganda are increasingly looking for unique and authentic experiences when choosing hotels. They prefer accommodations that offer cultural immersion, eco-friendly practices, and personalized services. This shift in preferences is in line with global trends towards experiential travel and sustainable tourism.

Trends in the market:
One noticeable trend in the Hotels market in Uganda is the rise of boutique hotels and eco-lodges. These smaller, more intimate properties cater to the growing demand for personalized experiences and sustainable practices. Additionally, there has been an increase in the number of international hotel chains entering the market, aiming to tap into the country's growing tourism sector.

Local special circumstances:
Uganda's rich biodiversity and stunning natural landscapes make it a popular destination for eco-tourism and wildlife enthusiasts. This has influenced the development of hotels and lodges that are situated in close proximity to national parks and nature reserves. Additionally, the government's efforts to promote tourism and improve infrastructure have contributed to the growth of the Hotels market in the country.

Underlying macroeconomic factors:
The overall economic stability and steady GDP growth in Uganda have boosted consumer confidence and disposable income, leading to an increase in domestic travel and tourism. The government's investment in infrastructure development, such as roads and airports, has also made it easier for both domestic and international tourists to access different parts of the country. These macroeconomic factors have created a conducive environment for the Hotels market to thrive in Uganda.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and sales channels of hotels.

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
  • Hotel Star Rating
  • Methodology
  • Key Market Indicators
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