Meal Delivery - Uganda

  • Uganda
  • Revenue in the Meal Delivery market in Uganda is projected to reach US$190.50m in 2024.
  • The market is expected to show an annual growth rate (CAGR 2024-2029) of 11.61%, resulting in a projected market volume of US$329.90m by 2029.
  • In Uganda, the Restaurant Deliverymarket has a projected market volume of US$165.60m in 2024.
  • In global comparison, China is expected to generate the highest revenue in the Meal Delivery market with US$182,900.00m in 2024.
  • The average revenue per user (ARPU) in the Meal Delivery market in Uganda is projected to amount to US$218.50 in 2024.
  • By 2029, the number of users in the Meal Delivery market in Uganda is expected to reach 1.4m users.
  • The user penetration in the Meal Delivery market in Uganda will be at 1.8% in 2024.
  • Uganda's meal delivery market is witnessing a surge in demand due to the increasing urbanization and busy lifestyles of its population.
 
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Analyst Opinion

Meal delivery services have been on the rise globally due to the convenience it offers to consumers. In Uganda, the meal delivery market is also experiencing steady growth.

Customer preferences:
Ugandan consumers are increasingly looking for convenience and time-saving options when it comes to meal preparation. With the busy lifestyles of urban dwellers, meal delivery services provide a solution to the challenge of preparing home-cooked meals. Additionally, there is a growing interest in healthy eating habits, which has led to an increase in demand for meal delivery services that offer healthy meal options.

Trends in the market:
The meal delivery market in Uganda is still in its early stages, but there is a growing number of players entering the market. One of the trends in the market is the use of technology to streamline the ordering and delivery process. Many meal delivery services in Uganda have mobile apps that allow customers to place orders and track their deliveries in real-time. Another trend is the use of social media platforms to market meal delivery services, which has been effective in reaching a wider audience.

Local special circumstances:
One of the challenges facing the meal delivery market in Uganda is the lack of infrastructure, which can make it difficult for delivery companies to reach customers in remote areas. Additionally, the high cost of internet data can limit the number of consumers who are able to access online meal delivery services. However, there is a growing middle class in Uganda that is willing to pay for convenience, which presents an opportunity for meal delivery services to expand their customer base.

Underlying macroeconomic factors:
The Ugandan economy has been growing steadily over the past few years, which has led to an increase in disposable income for many consumers. This has contributed to the growth of the meal delivery market as more consumers are able to afford the convenience of having meals delivered to their doorstep. Additionally, the growth of the tourism industry in Uganda has led to an increase in demand for meal delivery services as tourists look for convenient meal options during their stay.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on Gross Merchandise Value (GMV) and represent what consumers pay for these products and services. The user metrics show the number of customers who have made at least one online purchase within the past 12 months.

Modeling approach / Market size:

Market sizes are determined through a bottom-up approach, building on predefined factors for each market. As a basis for evaluating markets, we use annual financial reports of the market-leading companies, third-party studies and reports, as well as survey results from our primary research (e.g., the Statista Global Consumer Survey). In addition, we use relevant key market indicators and data from country-specific associations, such as GDP, GDP per capita, and internet connection speed. 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, the S-curve function and exponential trend smoothing. The main drivers are internet users, urban population, usage of key players, and attitudes toward online services.

Additional notes:

The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. GCS data is reweighted for representativeness.

Overview

  • Revenue
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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