Package Holidays - Russia

  • Russia
  • It is projected that the Package Holidays market in Russia will reach a revenue of US$7.99bn by 2024.
  • This is expected to grow annually at a rate of -0.09% between 2024 and 2028, resulting in a projected market volume of US$7.96bn by the latter year.
  • The number of users in this market is expected to reach 12.00m users by 2028, with a user penetration of 8.6% in 2024 rising to 8.4% by 2028.
  • The average revenue per user (ARPU) is expected to be US$0.64k.
  • Furthermore, it is anticipated that 65% of the total revenue in the Package Holidays market will be generated through online sales by 2028.
  • In terms of global comparison, China is projected to generate the most revenue in this market, with US$59,860m in 2024.
  • Despite economic challenges, Russians still prioritize package holidays as a way to relax and escape the stress of daily life.

Key regions: United Kingdom, India, Indonesia, Germany, Malaysia

 
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Analyst Opinion

The Package Holidays market in Russia has been experiencing significant growth and development in recent years.

Customer preferences:
Russian tourists have shown a growing interest in package holidays due to the convenience and cost-effectiveness they offer. With busy lifestyles, many customers prefer the ease of booking a complete holiday package that includes accommodation, transportation, and activities. Additionally, the all-inclusive nature of package holidays appeals to travelers looking for a hassle-free vacation experience.

Trends in the market:
One notable trend in the Package Holidays market in Russia is the increasing demand for domestic travel packages. As more Russians explore their own country, tour operators are designing attractive packages to popular destinations within Russia. This trend is fueled by a desire to discover the diverse cultural and natural attractions within the country while supporting the local tourism industry.

Local special circumstances:
Russia's vast territory and diverse landscapes present unique opportunities for package holiday offerings. From the historic cities of Moscow and St. Petersburg to the picturesque countryside and pristine beaches, Russia has a wide range of destinations to cater to different traveler preferences. Tour operators in Russia are capitalizing on these special circumstances by curating packages that showcase the country's rich heritage and natural beauty.

Underlying macroeconomic factors:
The growth of the Package Holidays market in Russia is also influenced by macroeconomic factors such as increasing disposable income and improved transportation infrastructure. As more Russians have higher spending power, they are willing to invest in travel experiences, including packaged holidays. Furthermore, the development of transportation networks makes it easier for tourists to access various regions within Russia, contributing to the overall expansion of the package holiday market.

Methodology

Data coverage:

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

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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