Market Insights eCommerce Online Food Delivery Meal Delivery

Restaurant Delivery - Kenya

Kenya

The Restaurant Delivery market in Kenya is projected to reach a revenue of US$296.20m by 2024.
It is expected to exhibit a compound annual growth rate (CAGR) of 8.28% from 2024 to 2029, resulting in a market volume of US$440.80m by 2029.
Furthermore, the number of users in the Restaurant Delivery market is anticipated to reach 21.8m users by 2029.
The user penetration rate, which currently stands at 26.7% in 2024, is projected to increase to 35.3% by 2029.
The average revenue per user (ARPU) is expected to be approximately US$19.71.
In terms of global comparison, United States is expected to generate the highest revenue in the Restaurant Delivery market, with an estimated value of US$36,950.00m in 2024.
On the other hand, South Korea is projected to have the highest user penetration rate in the market, with a forecasted rate of 53.1%.
Kenya's restaurant delivery market is experiencing a surge in demand due to the growing urban population and increasing adoption of online food ordering platforms.

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Analyst Opinion

The popularity of restaurant delivery services has been on the rise in Kenya.

Customer preferences: Kenyan consumers are increasingly turning to restaurant delivery services due to the convenience they offer. With the busy lifestyles that most Kenyans lead, many are finding it difficult to find time to cook, and restaurant delivery services provide a solution to this problem. Additionally, the COVID-19 pandemic has led to an increase in demand for restaurant delivery services as many people are avoiding crowded places such as restaurants.

Trends in the market: The restaurant delivery market in Kenya is becoming increasingly competitive, with new players entering the market every year. This has led to a wider range of options for consumers, with many restaurants now offering delivery services. Furthermore, the market is becoming more tech-savvy, with many delivery services now available through mobile apps, making it easier for consumers to place orders and track their deliveries.

Local special circumstances: One of the unique aspects of the restaurant delivery market in Kenya is the prevalence of informal dining establishments such as street food vendors. These vendors are often not included in formal restaurant delivery services, but they still play a significant role in the market. Many Kenyans prefer street food to formal dining, and as such, there is a growing demand for delivery services that cater to this market.

Underlying macroeconomic factors: Kenya's economy has been growing steadily over the past few years, and this has led to an increase in disposable income among Kenyans. As a result, more people are eating out, and restaurant delivery services are becoming more popular. Additionally, Kenya's youthful population is increasingly tech-savvy, and this has led to an increase in demand for online services such as restaurant delivery. Finally, the COVID-19 pandemic has accelerated the growth of the restaurant delivery market in Kenya, as more people are opting to stay home and order food rather than going out to eat.

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.