Online Food Delivery - Asia

  • Asia
  • Revenue in the Online Food Delivery market in Asia is expected to reach €593.40bn by 2024.
  • The market is projected to show an annual growth rate (CAGR 2024-2029) of 9.52%, resulting in a projected market volume of €935.10bn by 2029.
  • In the Grocery Delivery market, revenue is expected to grow by 17.3% in 2025.
  • The market volume in 2024 is projected to be €353.60bn.
  • China is expected to generate the highest revenue in the global comparison, with €416,300.00m in 2024.
  • The average revenue per user (ARPU) in the Grocery Delivery market is projected to be €315.50 in 2024.
  • In the Meal Delivery market, the number of users is expected to reach 1.8bn users by 2029.
  • User penetration in the Meal Delivery market will be at 33.7% in 2024.
  • In Japan, the online food delivery market is dominated by major players like Uber Eats and Rakuten, offering a wide range of cuisine options to cater to the diverse tastes of consumers.
 
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Analyst Opinion

The demand for online food delivery services in Asia has been on the rise in recent years, with several factors contributing to its growth.

Customer preferences:
Customers in Asia have shown a growing preference for convenience and time-saving services, which has led to an increase in demand for online food delivery services. With busy work schedules and long commutes, many consumers are opting for the convenience of having their meals delivered to their doorstep.

Trends in the market:
The online food delivery market in Asia is highly competitive, with several players vying for market share. In countries like China and India, local players dominate the market, while in Southeast Asia, international players like GrabFood and Foodpanda have a strong presence. One trend that has emerged in the market is the use of technology to improve the customer experience, such as the use of AI-powered chatbots to take orders and provide customer support.

Local special circumstances:
In China, the online food delivery market is dominated by two players, Meituan Dianping and Ele.me, which collectively account for over 90% of the market share. This duopoly has led to intense competition, with both companies offering steep discounts and subsidies to attract customers. In India, the market is highly fragmented, with several players operating in different regions. Swiggy and Zomato are the two largest players in the market, with a combined market share of over 80%.

Underlying macroeconomic factors:
The growth of the online food delivery market in Asia can be attributed to several macroeconomic factors, including rising urbanization, a growing middle class, and increasing internet penetration. As more people move to cities and adopt busy lifestyles, the demand for convenient and time-saving services like online food delivery is expected to continue to grow. The increasing penetration of smartphones and the internet has also made it easier for consumers to order food online. Additionally, the COVID-19 pandemic has accelerated the adoption of online food delivery services, as more people are staying home and avoiding crowded places.

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.

Visión general

  • Revenue
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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