Package Holidays - Cameroon

Cameroon

Highlights

By 2024, the Package Holidays market in Cameroon is forecasted to generate a revenue of US$63.38m.
The market is expected to experience an annual growth rate (CAGR 2024-2029) of 4.16%, which will bring the projected market volume to US$77.71m by 2029.
In the same period, the number of users is expected to reach 502.20k users.
The user penetration rate is anticipated to increase from 1.3% in 2024 to 1.5% by 2029.
The average revenue per user (ARPU) is expected to be US$166.90.
In terms of online sales, 67% of the total Package Holidays market revenue is expected to be generated through online channels by 2029.
Comparing to other countries, China is projected to generate the highest revenue in the Package Holidays market, with a revenue of US$49bn in 2024.
Cameroon's package holiday market is still developing, with a focus on nature and cultural tourism.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Package Holidays market in Cameroon is experiencing significant growth and development, driven by various factors influencing consumer behavior and market dynamics.

Customer preferences: Cameroonian travelers are increasingly seeking convenience, affordability, and unique experiences when choosing package holidays. With busy lifestyles and a growing middle-class population, there is a rising demand for all-inclusive travel packages that offer hassle-free planning and a range of amenities. Additionally, customers are showing a preference for personalized and tailored holiday packages that cater to their specific interests and preferences.

Trends in the market: In Cameroon, there is a noticeable trend towards eco-friendly and sustainable tourism practices within the package holidays market. Travelers are showing a growing interest in environmentally conscious travel options, such as eco-lodges, nature reserves, and community-based tourism initiatives. This trend aligns with global efforts towards sustainable tourism and reflects a shift in consumer awareness and preferences.

Local special circumstances: The diverse cultural and natural landscapes of Cameroon present unique opportunities for the package holidays market. From the lush rainforests of the South to the savannas of the North, travelers have a wide range of destinations to explore within the country. The rich cultural heritage and warm hospitality of the Cameroonian people also contribute to the appeal of package holidays in the region, offering tourists a chance to immerse themselves in local traditions and customs.

Underlying macroeconomic factors: The growth of the package holidays market in Cameroon is also influenced by macroeconomic factors such as increasing disposable incomes, improved infrastructure, and government initiatives to promote tourism. As the country continues to develop and attract foreign investment, the tourism sector is poised to expand further, creating new opportunities for package holiday providers to cater to a growing market of domestic and international travelers.

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.