Package Holidays - Kenya

  • Kenya
  • Kenya is expected to experience growth in its Package Holidays market as revenue is projected to reach US$316.80m by 2024.
  • The country is expected to maintain an annual growth rate (CAGR 2024-2029) of 6.92%, resulting in a projected market volume of US$442.60m by 2029.
  • By this period, the number of users in the Package Holidays market is expected to amount to 1.89m users.
  • The user penetration rate is projected to decrease from 2.4% in 2024 to 3.0% in 2029.
  • The average revenue per user (ARPU) is expected to be US$235.00.
  • In Kenya's Package Holidays market, 58% of the total revenue will be generated through online sales by 2029.
  • It is noteworthy to mention that in global comparison, China is projected to generate the most revenue in the Package Holidays market, with a projected revenue of US$49,250m in 2024.
  • Kenya's package holiday market is growing rapidly, driven by the country's diverse wildlife, stunning beaches and unique cultural experiences.

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

 
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Analyst Opinion

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

Customer preferences:
Travelers in Kenya are increasingly looking for convenient and hassle-free holiday experiences, which has led to a growing demand for package holidays. These all-inclusive offerings provide customers with a one-stop solution for their travel needs, including accommodation, meals, transportation, and activities. The convenience and cost-effectiveness of package holidays appeal to a wide range of consumers, from families to solo travelers.

Trends in the market:
One noticeable trend in the Package Holidays market in Kenya is the diversification of offerings to cater to different customer segments. Tour operators and travel agencies are now providing specialized packages targeting specific interests such as adventure tourism, cultural experiences, and eco-friendly holidays. This trend reflects the evolving preferences of Kenyan travelers who are seeking unique and personalized holiday experiences.

Local special circumstances:
Kenya's rich natural beauty and diverse wildlife are major attractions for tourists, making it a popular destination for safari holidays. The country's stunning national parks and reserves, such as the Maasai Mara and Amboseli, offer unique opportunities for wildlife viewing and nature exploration. This natural bounty has positioned Kenya as a top choice for travelers seeking unforgettable safari adventures, driving the demand for package holidays that include safari experiences.

Underlying macroeconomic factors:
The growth of the Package Holidays market in Kenya is also influenced by macroeconomic factors such as rising disposable incomes and improved infrastructure. As more Kenyans enter the middle-class income bracket, they have greater purchasing power to afford travel packages. Additionally, ongoing investments in transportation networks and accommodation facilities have made it easier for tour operators to offer a wider range of package holidays across the country. These macroeconomic factors have created a favorable environment for the expansion of the Package Holidays market in Kenya.

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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