Quick Commerce - Africa

  • Africa
  • The Quick Commerce market in Africa is projected to reach a revenue of US$1.07bn in 2024.
  • The market is expected to show an annual growth rate (CAGR 2024-2029) of 2.1%, resulting in a projected market volume of US$2.10bn by 2029.
  • By 2029, the number of users in the Quick Commerce market is expected to amount to 46.6m users.
  • The user penetration rate, which is currently at 2.1% in 2024, is expected to increase to 3.2% by 2029.
  • The average revenue per user (ARPU) is projected to be US$38.84.
  • In the global comparison, China is expected to generate the highest revenue in the Quick Commerce market, reaching US$80,840.00m in 2024.
  • Additionally, with a projected user penetration rate of 21.4%, China leads in this market.
  • In Nigeria, the Quick Commerce market is booming, with the rise of mobile payment solutions driving convenience and rapid delivery for consumers.
 
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Analyst Opinion

The Quick Commerce market in Africa is experiencing rapid growth, driven by changing consumer preferences and technological advancements.

Customer preferences:
African consumers are increasingly looking for convenience and speed in their shopping experience, leading to a rise in demand for Quick Commerce services. With the growth of e-commerce, consumers are now more comfortable with online shopping and expect fast delivery times. Additionally, the rise of urbanization has led to more time-pressed consumers who are willing to pay a premium for convenience.

Trends in the market:
In Nigeria, the Quick Commerce market has seen significant growth due to the country's large population and increasing smartphone penetration. Quick Commerce providers are leveraging this opportunity by offering a range of products, including groceries, pharmaceuticals, and electronics. In South Africa, the Quick Commerce market has seen the entry of global players such as UberEats and Mr. D Food, which are competing with local players to capture market share. In Kenya, the Quick Commerce market is being driven by the growth of mobile money and the increasing popularity of online shopping.

Local special circumstances:
The Quick Commerce market in Africa is also being shaped by local circumstances. For instance, in Nigeria, the lack of reliable logistics infrastructure has led to the emergence of informal delivery networks, which are being leveraged by Quick Commerce providers. In South Africa, the dominance of traditional retailers has led to a slow adoption of Quick Commerce services, with many consumers still preferring to shop in-store. In Kenya, the Quick Commerce market is being driven by the growth of e-commerce platforms such as Jumia and Kilimall, which are partnering with Quick Commerce providers to offer fast and reliable delivery services.

Underlying macroeconomic factors:
The growth of the Quick Commerce market in Africa is being supported by underlying macroeconomic factors such as increasing internet penetration, rising smartphone adoption, and growing urbanization. Additionally, the COVID-19 pandemic has accelerated the shift towards online shopping and increased demand for Quick Commerce services. However, challenges such as inadequate logistics infrastructure, regulatory hurdles, and low consumer trust in online shopping remain barriers to the growth of the Quick Commerce market in Africa.

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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