Retail Delivery - Eastern Africa

  • Eastern Africa
  • The Reail Delivery market in Eastern Africa is projected to reach a revenue of US$1.07bn in 2024.
  • This indicates an annual growth rate (CAGR 2024-2029) of 7.83%, resulting in a projected market volume of US$1.56bn by 2029.
  • Moreover, the number of users in the Reail Delivery market is expected to reach 61.2m users by 2029.
  • The user penetration is predicted to be 8.0% in 2024 and is projected to increase to 11.8% by 2029.
  • The average revenue per user (ARPU) is expected to amount to US$29.17.
  • In global comparison, the majority of revenue will be generated United States with an estimated US$195,400.00m in 2024.
  • Furthermore, the country with the highest projected user penetration rate in the Reail Delivery market is United States, with a rate of 30.4%.
  • In Eastern Africa, the retail delivery market is witnessing a surge in demand for online grocery shopping services.
 
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Analyst Opinion

The retail delivery market in Eastern Africa has been experiencing significant growth in recent years, driven by various factors such as increasing urbanization, rising disposable incomes, and the growth of e-commerce.

Customer preferences:
Customers in Eastern Africa are increasingly turning to online shopping due to the convenience it offers. The growth of e-commerce platforms has made it easier for customers to access a wide range of products from the comfort of their homes. Additionally, customers are looking for faster and more reliable delivery services. This has led to an increase in demand for same-day or next-day delivery services.

Trends in the market:
One of the trends in the retail delivery market in Eastern Africa is the growth of third-party logistics providers (3PLs). These companies offer a range of services such as warehousing, transportation, and delivery. They are becoming increasingly popular among retailers who want to outsource their logistics operations to focus on their core business. Another trend is the use of technology to improve delivery services. For example, some companies are using drones and other unmanned vehicles to deliver packages, especially in remote areas.

Local special circumstances:
The retail delivery market in Eastern Africa faces some unique challenges. One of the main challenges is poor infrastructure, especially in rural areas. This makes it difficult for delivery companies to reach some customers, leading to delays and increased costs. Additionally, there is a lack of standardization in the industry, which can lead to inefficiencies and increased costs.

Underlying macroeconomic factors:
The retail delivery market in Eastern Africa is being driven by various macroeconomic factors. One of these is the growth of the middle class. As more people move into the middle class, they have more disposable income to spend on goods and services, including online shopping. Additionally, the region is experiencing rapid urbanization, which is increasing demand for delivery services in cities. Finally, the growth of e-commerce platforms is driving demand for more efficient and reliable delivery services.

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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