Package Holidays - Zambia

  • Zambia
  • By the year 2024, the Package Holidays market in Zambia is expected to generate a revenue of US$50.38m.
  • Furthermore, this revenue is projected to grow annually at a rate of 10.05% (CAGR 2024-2029), resulting in a market volume projection of US$81.32m by the year 2029.
  • The number of users in this market is expected to reach 523.20k users by 2029.
  • In 2024, the user penetration is expected to be 1.6%, and it is projected to increase to 2.2% by 2029.
  • The average revenue per user (ARPU) is expected to be US$145.90.
  • Additionally, it is estimated that 59% of the total revenue in this market will be generated through online sales by 2029.
  • When compared globally, China is expected to generate the most revenue in this market, with a projected revenue of US$49,250m in 2024.
  • Despite the growth of domestic tourism, package holidays to Zambia's national parks remain popular among international tourists seeking a safari adventure.

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

 
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Analyst Opinion

The Package Holidays market in Zambia has been experiencing significant growth and development in recent years.

Customer preferences:
Customers in Zambia are increasingly seeking convenience and hassle-free travel experiences, leading to a growing demand for package holidays. The all-inclusive nature of package holidays, which typically include accommodation, meals, and activities, appeals to customers looking for a seamless vacation experience without the need to plan every detail themselves.

Trends in the market:
One notable trend in the Zambian package holidays market is the rise of domestic tourism. As more Zambians explore and appreciate the beauty of their own country, there has been a surge in demand for domestic package holiday offerings. This trend is supported by the development of new and exciting domestic tourism packages tailored to local preferences and interests.

Local special circumstances:
Zambia's rich natural landscapes, including the majestic Victoria Falls and diverse national parks, make it a prime destination for tourists seeking adventure and wildlife experiences. This unique selling point has contributed to the growth of the package holidays market in Zambia, with tour operators and travel agencies capitalizing on the country's natural attractions to design attractive holiday packages.

Underlying macroeconomic factors:
The improving economic conditions in Zambia have also played a role in the development of the package holidays market. As disposable incomes rise and the middle class expands, more Zambians are able to afford travel packages, driving demand in the market. Additionally, government initiatives to promote tourism and infrastructure development have further boosted the tourism sector, creating a conducive environment for the growth of the package holidays market.

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
  • Global Comparison
  • Methodology
  • Key Market Indicators
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