Package Holidays - Portugal

Portugal

Highlights

It is forecasted that the Package Holidays market in Portugal will generate a revenue of US$1.03bn by 2024.
This number is expected to grow annually at a rate of 3.32%, resulting in a projected market volume of US$1.21bn by 2029.
Moreover, the number of users in this market is anticipated to reach 1.63m users by 2029.
In 2024, user penetration is 14.6%, which is expected to increase to 16.1% by 2029.
The average revenue per user (ARPU) is estimated to be US$692.10.
Furthermore, it is projected that 52% of the total revenue in this market will be generated through online sales by 2029.
Finally, in a global comparison, the highest revenue is expected to come from China, which is projected to generate US$49bn in 2024.
In Portugal, package holidays are increasingly popular due to the country's sunny climate, beautiful beaches, and vibrant culture.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Portugal, known for its beautiful beaches and rich cultural heritage, has seen significant developments in the Package Holidays market.

Customer preferences: Travelers in Portugal are increasingly seeking convenience and hassle-free experiences when planning their vacations. This has led to a growing preference for package holidays, which offer all-inclusive deals that cover flights, accommodation, and activities. Customers appreciate the simplicity and cost-effectiveness of package holidays, allowing them to enjoy a stress-free vacation without having to worry about making individual bookings.

Trends in the market: One notable trend in the Package Holidays market in Portugal is the rise of personalized and experiential packages. Travel companies are now offering unique and tailored experiences to cater to the diverse preferences of customers. Whether it's culinary tours, wellness retreats, or adventure packages, travelers in Portugal are increasingly looking for immersive and authentic experiences that go beyond the traditional holiday package.

Local special circumstances: Portugal's strategic location on the Iberian Peninsula makes it a gateway to Europe, attracting a diverse range of tourists from neighboring countries. The country's stable political environment, warm climate, and stunning landscapes make it an attractive destination for both domestic and international travelers. Additionally, Portugal's strong cultural heritage and vibrant local cuisine contribute to its appeal as a top tourist destination.

Underlying macroeconomic factors: The Package Holidays market in Portugal is also influenced by macroeconomic factors such as income levels, exchange rates, and economic stability. As disposable incomes rise and the economy continues to grow, more Portuguese residents are able to afford travel packages, driving demand in the market. Furthermore, favorable exchange rates and government initiatives to promote tourism further support the growth of the Package Holidays market in Portugal.

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.