Package Holidays - Finland

Finland

Highlights

In 2024, the revenue in Finland's Package Holidays market is projected to reach US$1.40bn.
It is expected to display an annual growth rate (CAGR 2024-2029) of 3.24%, resulting in a market volume projection of US$1.64bn by 2029.
By 2029, the number of users in the mentioned market is expected to amount to 1.42m users.
Furthermore, the user penetration rate is projected to rise from 23.3% in 2024 to 25.5% by 2029.
The average revenue per user (ARPU) is expected to be US$1.08k.
In addition, 99% of the total revenue will be generated through online sales by 2029.
It is noteworthy that in the global comparison, China will generate the most revenue (US$49bn in 2024).
Package holidays to warm destinations are popular among Finns seeking to escape the cold and dark winter months.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Package Holidays market in Finland has been experiencing a notable shift in recent years, reflecting changing consumer preferences and local special circumstances.

Customer preferences: Travelers in Finland are increasingly seeking personalized and unique experiences in their holiday packages, moving away from traditional all-inclusive offerings. There is a growing demand for eco-friendly and sustainable tourism options, as well as an interest in cultural immersion and authentic local experiences. Additionally, convenience and flexibility play a crucial role in decision-making, with many consumers opting for customizable packages that cater to their specific needs and preferences.

Trends in the market: One of the key trends shaping the Package Holidays market in Finland is the rise of digital platforms and online booking services. Travelers are now more inclined to research, compare, and book their holiday packages online, leading to a surge in online travel agencies and aggregators. This shift towards digitalization has also facilitated greater transparency and price competitiveness in the market, empowering consumers to make informed choices.

Local special circumstances: Finland's unique geographical location and natural attractions, such as the Northern Lights and picturesque landscapes, have positioned the country as a desirable holiday destination. The seasonal variability in daylight hours and weather conditions have influenced the timing and nature of package holidays offered in the market. For instance, winter packages focusing on activities like skiing and snowmobiling are popular during the colder months, while summer packages may revolve around outdoor adventures and cultural events.

Underlying macroeconomic factors: The Package Holidays market in Finland is also influenced by broader macroeconomic factors, including disposable income levels, employment rates, and currency fluctuations. As the economy fluctuates, consumer spending on travel and tourism is impacted, leading to shifts in demand for holiday packages. External factors such as global economic trends and geopolitical events can further influence consumer confidence and travel behavior, shaping the overall market dynamics in Finland.

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.