Hotels - Russia

  • Russia
  • It is projected that the Hotels market in Russia will generate a revenue of US$6.27bn by 2024.
  • Furthermore, a steady annual growth rate of 0.20% (CAGR 2024-2028) is expected, resulting in a market volume of US$6.32bn by 2028.
  • In terms of users, the Hotels market is expected to have 26.76m users users by 2028.
  • The user penetration rate is predicted to increase from 18.5% in 2024 to 18.8% by 2028.
  • The average revenue per user (ARPU) is forecasted to be US$235.60.
  • By 2028, online sales are expected to generate 77% of the total revenue in the Hotels market.
  • When compared globally, United States is projected to generate the highest revenue with US$110,500m in 2024.
  • Russia's hotel market is seeing an increase in demand for luxury accommodations, particularly in major cities like Moscow and St. Petersburg.

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

 
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Analyst Opinion

The Hotels market in Russia has been experiencing significant developments in recent years, driven by various factors influencing customer preferences, market trends, local special circumstances, and underlying macroeconomic factors.

Customer preferences:
Customers in Russia are increasingly seeking unique and personalized experiences when choosing hotels. They value authenticity, local culture, and immersive activities, leading to a rise in demand for boutique and niche hotels. Additionally, there is a growing preference for eco-friendly and sustainable accommodation options among environmentally conscious travelers.

Trends in the market:
In Russia, there is a notable trend towards the digitalization of hotel services and operations. Many hotels are investing in technology to enhance guest experiences, streamline booking processes, and improve operational efficiency. Moreover, the rise of online travel agencies and digital platforms has transformed the way customers discover, compare, and book hotels, influencing market dynamics and competition among players.

Local special circumstances:
The geopolitical landscape and government regulations in Russia play a significant role in shaping the Hotels market. Foreign policy decisions, visa regulations, and economic sanctions can impact international tourism flows and hotel occupancy rates. Additionally, the vast geographical expanse of Russia presents unique challenges and opportunities for hotel development, with varying demand patterns across different regions.

Underlying macroeconomic factors:
Economic factors such as GDP growth, inflation rates, exchange rates, and consumer spending power have a direct impact on the Hotels market in Russia. Fluctuations in oil prices, as a key export commodity for Russia, can also influence tourism dynamics and hotel performance. Moreover, political stability, infrastructure investments, and government initiatives to promote tourism play a crucial role in shaping the overall market landscape.

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
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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