Retail Delivery - Kenya

Kenya

Highlights

The Reail Delivery market in Kenya is projected to reach a revenue of Ksh US$33.90m in 2024.
It is expected to show an annual growth rate (CAGR 2024-2029) of -0.02%, resulting in a projected market volume of Ksh US$33.87m by 2029.
By 2029, the number of users in the Reail Delivery market is expected to amount to 9.3m users.
The user penetration in 2024 is forecasted to be 11.2% and is expected to increase to 15.0% by 2029.
The average revenue per user (ARPU) is projected to be Ksh US$5.41.
In global comparison, United States is anticipated to generate the highest revenue in the Reail Delivery market, reaching Ksh US$195.40bn in 2024.
The United States, on the other hand, is expected to have the highest user penetration rate of 30.4%.
As a journalist with deep knowledge about history, facts, and insights, I can provide you with a country-specific statement about current trends in the Retail Delivery market in Kenya: Kenya's Retail Delivery market is experiencing a surge in demand for online shopping platforms and home delivery services.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Retail Delivery market in Kenya has been experiencing rapid growth in recent years, driven by a number of factors.

Customer preferences: Kenyan consumers are increasingly turning to online shopping, driven by the convenience and variety offered by e-commerce platforms. Many consumers in Kenya are young and tech-savvy, and are comfortable using digital platforms to make purchases. Additionally, the COVID-19 pandemic has accelerated the shift towards online shopping, with many consumers opting for home delivery to avoid exposure to the virus.

Trends in the market: One trend in the Retail Delivery market in Kenya is the growth of local e-commerce platforms. While international platforms like Amazon and Alibaba are present in the Kenyan market, local platforms like Jumia and Kilimall are becoming increasingly popular. These platforms offer a wider range of products that are tailored to the local market, and often offer faster delivery times than international platforms.Another trend in the market is the growth of last-mile delivery services. With many consumers opting for home delivery, there is a growing demand for companies that can provide fast and reliable delivery services. This has led to the emergence of a number of last-mile delivery startups in Kenya, such as Sendy and Glovo.

Local special circumstances: Kenya has a large informal economy, and many small businesses rely on cash transactions. This has historically made it difficult for e-commerce platforms to gain traction in the Kenyan market. However, the government has taken steps to promote digital payments and financial inclusion, which has helped to overcome this barrier.

Underlying macroeconomic factors: Kenya has a rapidly growing population, with a large and youthful consumer base. This has created a large market for e-commerce platforms, as well as a growing demand for last-mile delivery services. Additionally, Kenya has a relatively well-developed logistics infrastructure, which has helped to support the growth of the Retail Delivery market. Finally, the government has taken steps to promote entrepreneurship and innovation, which has helped to create a favorable environment for startups in the Retail Delivery market.

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.