Package Holidays - Georgia

Georgia

Highlights

By 2024, it is anticipated that the Package Holidays market in Georgia will generate a revenue of US$10.34m.
The market is expected to grow annually at a rate of 7.86% during 2024-2029, resulting in a projected market size of US$15.09m by 2029.
The number of users in this market is predicted to increase to 33.88k users by 2029.
It is estimated that user penetration will decrease from 0.8% in 2024 to 0.9% in 2029.
The average revenue per user (ARPU) is expected to be US$357.40.
Furthermore, it is anticipated that 73% of the total revenue in the Package Holidays market will be generated through online sales by 2029.
In comparison to the rest of the world, China is expected to generate the most revenue (US$49bn in 2024).
Georgia's package holiday market is on the rise, with an increasing number of tourists opting for all-inclusive deals to explore the country's rich history and breathtaking landscapes.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Package Holidays market in Georgia is experiencing a notable growth trajectory, reflecting the changing preferences of customers and the unique local circumstances in the country.

Customer preferences: Customers in Georgia are increasingly seeking convenience and hassle-free travel experiences, leading to a rising demand for package holidays. The all-inclusive nature of these holidays, which typically include accommodation, meals, and activities, appeals to travelers looking for a seamless vacation experience without the need to plan every detail themselves.

Trends in the market: One of the key trends in the Package Holidays market in Georgia is the growing popularity of domestic package holidays. As more Georgians explore and appreciate the beauty of their own country, there is a noticeable shift towards opting for packaged tours within Georgia. This trend is driven by a desire to support local tourism industry and explore lesser-known destinations within the country.

Local special circumstances: Georgia's unique geographical location at the crossroads of Europe and Asia, coupled with its diverse landscapes ranging from mountains to beaches, makes it an attractive destination for a wide range of travelers. This diversity allows for a variety of package holiday options, catering to different preferences - whether it's adventure seekers looking to hike in the Caucasus Mountains or beach lovers wanting to relax on the Black Sea coast.

Underlying macroeconomic factors: The growth of the Package Holidays market in Georgia is also influenced by macroeconomic factors such as increasing disposable income levels and improving infrastructure for tourism. As the country's economy continues to develop, more Georgians are able to afford travel packages, driving the demand for such offerings. Additionally, investments in tourism infrastructure, such as hotels and transportation, have made it easier for tour operators to offer diverse and attractive package holidays to customers.

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.