Restaurant Delivery - Northern Africa

  • Northern Africa
  • The Restaurant Delivery market in Northern Africa is projected to reach a revenue of US$547.30m in 2025.
  • This is expected to show an annual growth rate (CAGR 2025-2029) of 6.31%, resulting in a projected market volume of US$699.20m by 2029.
  • By that time, the number of users in the Restaurant Delivery market is expected to reach 14.6m users.
  • The user penetration in the market is estimated to be 4.5% in 2025 and is projected to increase to 5.2% by 2029.
  • The average revenue per user (ARPU) is expected to be US$45.57.
  • In global comparison, United States is anticipated to generate the highest revenue in the Restaurant Delivery market, amounting to US$39,050.00m in 2025.
  • Austria, on the other hand, is projected to have the highest user penetration rate in the market, with a rate of 47.6%.
  • In Northern Africa, the restaurant delivery market is experiencing rapid growth due to the increasing adoption of online food ordering platforms.
 
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Analyst Opinion

The popularity of food delivery services has been on the rise in recent years, and Northern Africa is no exception. With a growing middle class and increasing urbanization, the demand for restaurant delivery services has been steadily increasing in the region.

Customer preferences:
Customers in Northern Africa have shown a strong preference for convenience and affordability when it comes to food delivery. Many people lead busy lives and do not have the time or energy to cook for themselves, so food delivery services offer a convenient solution. Additionally, with rising food prices in the region, many customers are looking for affordable options for their meals.

Trends in the market:
One of the biggest trends in the restaurant delivery market in Northern Africa is the rise of online ordering platforms. Many customers are now using apps and websites to place their orders, which has made the process more efficient and streamlined. Additionally, there has been a trend towards healthier food options, with many delivery services now offering salads, smoothies, and other healthy choices.

Local special circumstances:
One of the unique challenges in the Northern African market is the prevalence of cash payments. Many customers do not have access to credit cards or other electronic payment methods, so many delivery services have had to adapt to accept cash payments. Additionally, the region's diverse culinary landscape has led to a wide variety of food options, with many delivery services offering traditional local dishes alongside international cuisine.

Underlying macroeconomic factors:
The restaurant delivery market in Northern Africa is being driven by several macroeconomic factors. As the region's middle class continues to grow, more people are able to afford restaurant delivery services. Additionally, as more people move to urban areas, the demand for convenient food options has increased. Finally, the region's young population is also a factor, as younger people are more likely to use technology to order food and are more open to trying new and different cuisines.

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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