Package Holidays - Qatar

Qatar

Highlights

Qatar is expected to see a significant increase in revenue in the Package Holidays market, with projected earnings of US$290.70m in 2024.
This revenue is expected to experience a Compound Annual Growth Rate (CAGR 2024-2029) of 3.28%, resulting in a projected market volume of US$341.70m by 2029.
Additionally, the number of users in the Package Holidays market is projected to reach 396.10k users by 2029, with a user penetration rate of 12.2% in 2024 and an expected increase to 14.0% by 2029.
The average revenue per user (ARPU) is projected to be US$872.90.
Interestingly, 88% of the total revenue generated in the Package Holidays market will be from online sales by 2029.
It is worth noting that China is expected to generate the most revenue in this market, with projected earnings of US$49bn in 2024 when compared to other countries globally.
Qatar's growing middle class is increasingly opting for all-inclusive package holidays to popular destinations like Turkey and the Maldives.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

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

Customer preferences: Customers in Qatar are increasingly seeking convenience and hassle-free travel experiences, which has led to a growing demand for package holidays. The all-inclusive nature of these packages appeals to busy individuals and families looking to maximize their vacation time without the stress of planning every detail.

Trends in the market: One notable trend in the Package Holidays market in Qatar is the rise of luxury package holidays. With a high per capita income and a penchant for luxury experiences, Qatari travelers are willing to invest in premium package deals that offer exclusive accommodations, personalized services, and unique experiences tailored to their preferences. This trend is driving the growth of high-end package holiday offerings in the country.

Local special circumstances: Qatar's strategic location in the Middle East, coupled with its world-class infrastructure and amenities, makes it an attractive destination for both regional and international tourists. The country's efforts to diversify its economy away from oil and gas have also led to investments in the tourism sector, further enhancing Qatar's appeal as a holiday destination. Additionally, the upcoming FIFA World Cup in 2022 is expected to boost tourism and drive demand for package holidays as visitors flock to the country for the event.

Underlying macroeconomic factors: The strong economic growth and high disposable income levels in Qatar have contributed to the increasing popularity of package holidays among its residents. As more Qataris prioritize leisure travel and seek unique experiences, the Package Holidays market is poised for continued expansion. Additionally, the government's focus on promoting tourism and developing the hospitality sector is creating a supportive environment for the growth of package holiday offerings in the country.

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.