Package Holidays - Canada

  • Canada
  • Canada is expected to see a significant increase in the Package Holidays market revenue, with a projected revenue of US$6.54bn by 2024.
  • Moreover, the revenue is anticipated to grow annually at a rate of 2.33% from 2024 to 2029.
  • This growth rate is expected to result in a projected market volume of US$7.34bn in 2029.
  • In terms of user base, the Package Holidays market is expected to see the number of users increase to 9.09m users by 2029.
  • In 2024, user penetration is expected to be 20.5%, a figure which is expected to decrease to 22.3% by 2029.
  • The average revenue per user (ARPU) is expected to be US$0.82k in Canada.
  • Additionally, it is projected that 84% of the total revenue in the Package Holidays market will be generated through online sales by 2029.
  • In terms of global comparison, China is expected to generate the most revenue in the Package Holidays market, with a projected revenue of US$49,250m in 2024.
  • Canadian package holiday demand is rising due to the country's diverse outdoor activities, scenic beauty, and cultural experiences.

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

 
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Analyst Opinion

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

Customer preferences:
Canadian customers are increasingly seeking convenience and hassle-free travel experiences, which has led to a rise in demand for package holidays. The all-inclusive nature of package holidays appeals to customers looking for a stress-free vacation where all arrangements are taken care of in one booking.

Trends in the market:
One noticeable trend in the Canadian Package Holidays market is the shift towards more personalized and experiential offerings. Tour operators are now focusing on creating unique and tailored packages that cater to the specific interests and preferences of travelers. This trend has been driven by the desire for authentic and immersive travel experiences.

Local special circumstances:
Canada's vast and diverse landscape offers a wide range of travel opportunities, from stunning natural wonders to vibrant cities. This diversity has contributed to the popularity of package holidays, as travelers seek convenient ways to explore the country's various attractions in a single trip. Additionally, the seasonal nature of certain tourist destinations in Canada has led to the development of specialized package holidays for different times of the year.

Underlying macroeconomic factors:
The stable economy and growing disposable income in Canada have made travel more affordable for a larger segment of the population. As a result, more Canadians are opting for package holidays as a cost-effective way to experience different destinations. Additionally, the strong Canadian dollar has made international travel more accessible, leading to an increase in demand for outbound package holidays.

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.

Overview

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