Vacation Rentals - Russia

Russia

Highlights

By 2024, it is predicted that the Vacation Rentals market in Russia will generate a revenue of US$2.40bn.
This revenue is expected to show an annual growth rate (CAGR 2024-2029) of 3.01%, resulting in a market volume of US$2.78bn by 2029.
In the same period, it is expected that the number of users in this market will reach 24.02m users, with a user penetration of 15.6% in 2024, which is projected to rise to 16.9% by 2029.
The average revenue per user (ARPU) is estimated to be US$107.00.
Furthermore, it is predicted that in the Vacation Rentals market in Russia, 76% of the total revenue will be generated through online sales by 2029.
It is worth noting that in global comparison, United States is expected to generate the most revenue in this market, with a projected revenue of US$20bn in 2024.
Despite economic challenges, the demand for vacation rentals in Russia remains strong due to a growing middle class seeking affordable travel options.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Russia has been experiencing a significant surge in recent years, with a growing number of travelers opting for alternative accommodation options over traditional hotels.

Customer preferences: Travelers in Russia are increasingly seeking unique and personalized experiences during their vacations, driving the demand for vacation rentals. The flexibility, space, and amenities offered by vacation rentals cater to the preferences of many modern travelers, especially those looking for a more local and authentic stay.

Trends in the market: One notable trend in the Russian vacation rentals market is the increasing popularity of rural and countryside properties. As more travelers seek to escape the hustle and bustle of city life, rural vacation rentals offer a peaceful retreat surrounded by nature. Additionally, the rise of digital platforms and online booking systems has made it easier for property owners to list their rentals and for travelers to discover and book accommodations.

Local special circumstances: Russia's vast and diverse landscape presents a unique opportunity for vacation rental growth. From cozy cabins in the snow-capped mountains to charming cottages by the lakeside, the country offers a wide range of vacation rental options to cater to different preferences. Additionally, the growing focus on domestic tourism in Russia has further fueled the demand for vacation rentals as more locals explore their own country.

Underlying macroeconomic factors: The growth of the vacation rentals market in Russia can also be attributed to the increasing disposable income of the population. As more Russians have the means to travel and explore new destinations, the demand for alternative accommodations like vacation rentals continues to rise. Furthermore, the government's efforts to promote tourism and improve infrastructure have made travel within the country more accessible, contributing to the expansion of the vacation rentals market.

Data coverage:

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

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.