Hotels - Iran

  • Iran
  • Iran's Hotels market is projected to reach a revenue of US$1.77bn by 2024.
  • This market is expected to grow annually at a rate of 2.45% from 2024 to 2028, resulting in a market volume projection of US$1.95bn by 2028.
  • The projected number of users in this market is 17.94m users by 2028, with a user penetration of 17.5% in 2024 and an expected increase to 19.5% by 2028.
  • The average revenue per user (ARPU) is expected to be US$113.10.
  • Online sales are projected to generate 76% of the total revenue in the Hotels market by 2028.
  • In global comparison, United States is expected to generate the most revenue in this market with US$110,500m in 2024.
  • Despite recent economic and political challenges, Iran's hotel market is showing signs of growth with increased investment and a growing interest in tourism.

Key regions: Singapore, Indonesia, India, United States, Europe

 
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Analyst Opinion

Iran's Hotels market is experiencing significant growth and development, driven by various factors shaping consumer preferences and local special circumstances.

Customer preferences:
Travelers in Iran are increasingly seeking unique and authentic experiences when choosing accommodations. This has led to a rise in demand for boutique hotels, eco-friendly properties, and traditional guesthouses that offer a glimpse into the local culture and heritage. Additionally, with the growing influence of social media, there is a greater emphasis on aesthetically pleasing hotels that provide picturesque backdrops for travel photos.

Trends in the market:
One of the notable trends in Iran's Hotels market is the increasing focus on technology and online booking platforms. Hoteliers are investing in digital marketing strategies and online booking systems to reach a wider audience of tech-savvy travelers. Moreover, there is a growing trend towards sustainable practices in the hospitality industry, with many hotels in Iran implementing eco-friendly initiatives to appeal to environmentally conscious guests.

Local special circumstances:
Iran's unique geopolitical position and rich history make it a popular destination for both domestic and international tourists. The country's diverse landscapes, from bustling cities to serene deserts, offer a wide range of experiences for travelers. Additionally, the recent easing of international sanctions has led to a gradual increase in foreign visitors, further boosting the Hotels market in Iran.

Underlying macroeconomic factors:
The Hotels market in Iran is also influenced by macroeconomic factors such as government policies, exchange rates, and inflation rates. The government's efforts to promote tourism as a key driver of economic growth have led to investments in infrastructure development and tourism promotion initiatives. Moreover, fluctuations in exchange rates and inflation can impact travel costs and consumer spending behavior, thereby affecting the overall performance of the Hotels market in Iran.

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
  • Methodology
  • Key Market Indicators
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