Hotels - Europe

  • Europe
  • The Hotels market in Europe is set to experience a rise in revenue as it is projected to reach US$113.40bn by 2024.
  • This projection is expected to show an annual growth rate (CAGR 2024-2028) of 1.76%, leading to a market volume of US$121.60bn by 2028.
  • The number of users in this market is expected to increase to 293.10m users by 2028, with a user penetration of 33.0% in 2024 and an estimated rise to 34.8% by 2028.
  • The average revenue per user (ARPU) is expected to be US$0.41k.
  • Online sales are set to generate 86% of total revenue in the Hotels market by 2028.
  • Comparing globally, United States is expected to generate the most revenue in this market, with a projection of US$110,500m in 2024.
  • The hotel market in Spain is experiencing an upward trend due to an increase in international tourism.

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

Region comparison

Analyst Opinion

The Hotels market in Europe is a dynamic and diverse industry that is constantly evolving to meet the changing needs and preferences of customers.

Customer preferences:
Customers in Europe are increasingly looking for unique and personalized experiences when choosing hotels. They are seeking accommodations that offer not only comfort and convenience but also a sense of local culture and authenticity. This trend has led to a rise in boutique hotels and eco-friendly properties that cater to the growing demand for sustainable tourism practices.

Trends in the market:
In countries like Italy, Spain, and France, there is a growing trend towards luxury and high-end hotels, particularly in popular tourist destinations. These hotels offer premium amenities and services to attract affluent travelers looking for a luxurious experience. On the other hand, Eastern European countries like Poland and Hungary are seeing a surge in budget and mid-range hotels to cater to cost-conscious travelers.

Local special circumstances:
In countries such as Greece and Portugal, the Hotels market is heavily influenced by seasonal tourism patterns. During the peak summer months, there is a high demand for beachfront resorts and hotels in coastal areas. In contrast, the winter season sees a shift towards ski resorts in countries like Austria and Switzerland. Hoteliers in these regions need to adapt their offerings and marketing strategies to cater to these seasonal fluctuations in demand.

Underlying macroeconomic factors:
The Hotels market in Europe is also influenced by broader macroeconomic factors such as economic growth, exchange rates, and political stability. Countries with strong economies and stable political environments tend to attract more tourists, leading to higher demand for hotels. On the other hand, economic downturns or geopolitical uncertainties can impact travel behavior and consumer confidence, affecting the overall performance of the hotel industry.


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.


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.


  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Hotel Star Rating
  • Methodology
  • Key Market Indicators
Please wait