Package Holidays - Italy

  • Italy
  • It is projected that the Package Holidays market in Italy will reach a revenue of €8.34bn by 2024.
  • This is expected to grow annually at a rate of 2.70% between 2024 and 2029, resulting in a projected market volume of €9.53bn by 2029.
  • By 2029, the number of users in this market is expected to reach 9.95m users.
  • The user penetration rate is projected to increase from 16.4% in 2024 to 17.2% in 2029.
  • The average revenue per user (ARPU) is expected to be €0.86k in Italy.
  • Furthermore, online sales are expected to generate 55% of the total revenue in this market by 2029.
  • In comparison to other countries, China is projected to generate the most revenue in the Package Holidays market, with €45,670m in 2024.
  • Italian package holidays cater to a broad spectrum of budgets, offering luxury experiences and budget-friendly 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 Italy has been experiencing a significant growth in recent years.

Customer preferences:
Italian consumers have shown a growing interest in hassle-free travel experiences, leading to an increased demand for package holidays. The convenience of having all travel arrangements taken care of by a single provider appeals to busy individuals and families looking to simplify their vacation planning process.

Trends in the market:
One notable trend in the Package Holidays market in Italy is the shift towards more personalized and experiential travel packages. Tour operators are now offering unique itineraries that cater to specific interests such as culinary tours, wellness retreats, and eco-friendly vacations. This trend reflects a broader global movement towards tailored travel experiences that go beyond traditional sightseeing.

Local special circumstances:
Italy's rich cultural heritage, diverse landscapes, and world-renowned cuisine make it a highly desirable destination for tourists seeking a mix of history, nature, and gastronomy. The country's popularity as a travel destination contributes to the robust demand for package holidays, as visitors look for convenient ways to explore all that Italy has to offer in a single trip.

Underlying macroeconomic factors:
The stability of Italy's economy and the strength of the tourism sector play a crucial role in driving the growth of the Package Holidays market. Favorable economic conditions, combined with government initiatives to promote tourism, have boosted consumer confidence and spending on leisure activities. Additionally, the competitive pricing of package holidays compared to individual bookings has further incentivized Italians to opt for all-inclusive travel packages.

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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