Market Insights eCommerce Online Food Delivery Grocery Delivery

Quick Commerce - South Korea

South Korea

In 2024, the projected revenue in the Quick Commerce market in South Korea is expected to reach US$2.85bn.
This market is anticipated to experience an annual growth rate (CAGR 2024-2029) of 7.44%, resulting in a projected market volume of US$4.08bn by 2029.
Moreover, the number of users in the Quick Commerce market in South Korea is expected to reach 9.6m users by 2029.
The user penetration rate is projected to be 13.3% in 2024 and is expected to increase to 18.6% by 2029.
Additionally, the average revenue per user (ARPU) is expected to amount to US$415.80.
When comparing in South Korea to other countries, it is important to note that China is anticipated to generate the highest revenue in the Quick Commerce market, reaching US$80,840.00m in 2024.
Furthermore, China is expected to have the highest user penetration rate in the Quick Commerce market, with a projected rate of 21.4%.
In South Korea, there is a growing trend of consumers relying on quick commerce platforms to meet their immediate needs for groceries and other essential items.

Market

Region

Region comparison

Currency

Analyst Opinion

South Korea, known for its advanced technology and fast-paced lifestyle, has seen a significant rise in the Quick Commerce market.

Customer preferences: South Korean consumers are known for their high demand for convenience, which has led to the growth of the Quick Commerce market. With busy work schedules and a desire for efficient shopping experiences, consumers are turning to Quick Commerce platforms to purchase their daily necessities. The COVID-19 pandemic has also accelerated the demand for contactless delivery services, further driving the growth of the Quick Commerce market.

Trends in the market: The Quick Commerce market in South Korea has seen a rise in competition, with both local and global players entering the market. Companies are offering a wider range of products and services, including groceries, pharmaceuticals, and even home appliances. The market is also seeing a trend towards eco-friendly delivery options, such as electric bikes and reusable packaging.

Local special circumstances: South Korea's high population density and advanced infrastructure make it an ideal market for Quick Commerce platforms. The country's large urban areas, such as Seoul, have a high concentration of potential customers in a small geographic area, making it easier and more cost-effective for companies to provide quick delivery services. Additionally, South Korea's tech-savvy population has embraced the use of mobile apps for shopping and delivery services.

Underlying macroeconomic factors: South Korea's strong economy and high internet penetration rate have contributed to the growth of the Quick Commerce market. The country's GDP per capita is among the highest in Asia, and its middle class has significant purchasing power. Additionally, South Korea has one of the highest smartphone penetration rates in the world, making it easier for companies to reach consumers through mobile apps.

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.