Platform Delivery - Kenya

Kenya

Highlights

The Platform Delivery market in Kenya is projected to reach a revenue of US$123.30m in 2024.
It is expected to grow at an annual rate of 7.45% (CAGR 2024-2029), resulting in a projected market volume of US$176.50m by 2029.
By that time, the number of users in the Platform Delivery market is expected to reach 8.8m users.
The user penetration rate, which currently stands at 11.2% in 2024, is projected to increase to 14.2% by 2029.
The average revenue per user (ARPU) is expected to be US$19.55.
When compared globally, China is forecasted to generate the highest revenue in the Platform Delivery market, amounting to US$166.80bn in 2024.
Furthermore, China is expected to have the highest user penetration rate in the market, with a projected rate of 52.8%.
Kenya's platform delivery market is experiencing rapid growth fueled by the increasing demand for convenient and efficient delivery services.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The demand for platform delivery services in Kenya has been on the rise in recent years, driven by a growing middle class and increased adoption of e-commerce.

Customer preferences: Kenyan consumers are becoming increasingly accustomed to the convenience of online shopping and home delivery. This trend is particularly evident among the younger generation, who are more tech-savvy and comfortable with using digital platforms. Additionally, the COVID-19 pandemic has accelerated the shift towards online shopping, as consumers seek to avoid crowded public spaces.

Trends in the market: The platform delivery market in Kenya is becoming increasingly competitive, with both local and international players vying for market share. One notable trend is the emergence of specialized delivery services catering to specific niches, such as food delivery or last-mile logistics. Another trend is the use of technology to improve the efficiency of delivery operations, such as real-time tracking and automated dispatch.

Local special circumstances: Kenya's geography and infrastructure present unique challenges for platform delivery providers. The country's large rural population and poor road network make it difficult to reach certain areas, while high levels of crime and insecurity pose risks to delivery personnel. Additionally, the lack of a formal addressing system in many parts of the country can make it difficult to accurately locate delivery addresses.

Underlying macroeconomic factors: Kenya's relatively stable political environment and growing economy have made it an attractive destination for foreign investment, including in the e-commerce and logistics sectors. However, the country still faces challenges such as high levels of unemployment and income inequality, which could limit the growth of the platform delivery market in the long run. Additionally, regulatory uncertainty and a lack of clear guidelines for the operation of platform delivery services could pose risks to investors and operators alike.

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.