Package Holidays - Gambia

  • Gambia
  • The Package Holidays market is expected to achieve a revenue of US$3.46m by the year 2024.
  • Moreover, it is projected to display a Compound Annual Growth Rate (CAGR) of 5.54%, which will result in a market volume of US$4.53m by 2029.
  • By 2029, the number of users in the Package Holidays market is expected to be around 25.46k users.
  • The user penetration rate is predicted to decrease from 0.6% in 2024 to 0.8% in 2029.
  • The Average Revenue Per User (ARPU) is expected to be US$200.00.
  • The online sales are expected to generate 58% of the total revenue by 2029.
  • It is worth mentioning that, in comparison to other countries, China is expected to generate the highest revenue of US$49,250m by 2024.
  • Regarding in Gambia, it can be inferred that the Package Holidays market in Gambia will also experience growth in the upcoming years.
  • Gambia's package holiday market is thriving with an increase in eco-friendly and sustainable tourism options.

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

 
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Analyst Opinion

The Package Holidays market in Gambia has been experiencing significant growth in recent years, with a surge in demand for all-inclusive travel packages among both domestic and international tourists.

Customer preferences:
Customers in Gambia are increasingly seeking convenience and affordability when planning their holidays, leading to a growing preference for package holidays that offer a hassle-free travel experience. The all-inclusive nature of these packages, which typically include accommodation, meals, and activities, appeals to travelers looking for a stress-free vacation.

Trends in the market:
One notable trend in the Package Holidays market in Gambia is the diversification of offerings to cater to different customer segments. Tour operators are now providing a range of package options, including family-friendly packages, adventure holidays, and luxury getaways, to meet the evolving preferences of travelers. Additionally, there is a rising interest in eco-friendly and sustainable tourism packages, reflecting a global trend towards responsible travel.

Local special circumstances:
Gambia's unique selling points, such as its stunning beaches, rich cultural heritage, and diverse wildlife, have contributed to the growth of the Package Holidays market. Tourists are drawn to the country's vibrant markets, traditional music and dance performances, and opportunities for wildlife safaris, making it an attractive destination for packaged tours.

Underlying macroeconomic factors:
The growth of the Package Holidays market in Gambia can also be attributed to favorable macroeconomic conditions, including stable economic growth, infrastructure development, and government initiatives to promote tourism. The increasing connectivity through improved transportation links and the presence of international hotel chains have further boosted the attractiveness of Gambia as a holiday destination for package tourists.

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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