Package Holidays - Brazil

  • Brazil
  • It is projected that the Package Holidays market in Brazil will reach a revenue of €5.42bn by 2024.
  • This revenue is expected to grow annually at a rate of 3.89%, resulting in a market volume of €6.56bn by 2029.
  • In terms of user base, the Package Holidays market is expected to have 25.45m users users by 2029, with a user penetration rate of 11.4%, down from 9.8% in 2024.
  • The average revenue per user (ARPU) is expected to be €253.40.
  • By 2029, 83% of the total revenue in the Package Holidays market is expected to come from online sales.
  • In comparison to other countries, China is projected to generate the most revenue in the Package Holidays market, reaching €45,670m in 2024.
  • Despite economic struggles, Brazilians still prioritize package holidays for their affordability, convenience, and all-inclusive options.

Key regions: Singapore, India, Indonesia, Germany, Saudi Arabia

 
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Comparaison de régions
 
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Analyst Opinion

The Package Holidays market in Brazil has been experiencing significant growth and evolution in recent years.

Customer preferences:
Brazilian consumers are increasingly seeking convenience and value for money when it comes to holiday planning. The all-inclusive nature of package holidays, which often include accommodation, meals, and activities, aligns well with these preferences. Additionally, the ease of booking a complete travel package appeals to busy individuals and families looking to simplify their vacation planning process.

Trends in the market:
One notable trend in the Brazilian Package Holidays market is the rise of domestic tourism. As more Brazilians explore destinations within their own country, there is a growing demand for package holidays that cater to local travel experiences. This trend is fueled by a combination of factors, including a desire to support the local economy and discover hidden gems within Brazil.

Local special circumstances:
Brazil's vast and diverse landscape offers a wide range of travel opportunities, from pristine beaches to lush rainforests and vibrant cities. This diversity presents a unique advantage for the Package Holidays market, as tour operators can design packages that showcase the best of what Brazil has to offer. Additionally, the country's rich cultural heritage and warm hospitality contribute to the overall appeal of package holidays for both domestic and international tourists.

Underlying macroeconomic factors:
The economic stability and growing middle class in Brazil have contributed to the expansion of the Package Holidays market. With more disposable income and a desire to explore new destinations, Brazilian consumers are increasingly opting for packaged travel options that provide convenience and affordability. Additionally, government initiatives to promote tourism and improve infrastructure have further boosted the growth of the market, making Brazil an attractive destination for both domestic and international travelers.

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.

Vue d’ensemble

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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