Restaurant Delivery - ASEAN

ASEAN

Highlights

The Restaurant Delivery market in ASEAN is projected to reach a revenue of US$4.91bn by 2024.
The market is expected to grow at an annual growth rate (CAGR 2024-2029) of 3.45%, resulting in a projected market volume of US$5.82bn by 2029.
By 2029, the number of users in the Restaurant Delivery market is expected to reach 105.0m users.
The user penetration rate is projected to be 13.4% in 2024 and is expected to increase to 14.6% by 2029.
The average revenue per user (ARPU) is expected to be US$53.04.
In comparison to other countries, United States is expected to generate the highest revenue in the Restaurant Delivery market, reaching US$36.95bn in 2024.
South Korea has the highest projected user penetration rate of 44.8% in the Restaurant Delivery market.
In Singapore, the restaurant delivery market is dominated by food delivery platforms like GrabFood and Deliveroo, offering a wide variety of cuisines to customers.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The ASEAN region has seen a surge in the popularity of restaurant delivery services in recent years.

Customer preferences: Customers in ASEAN countries are increasingly turning to restaurant delivery services due to their convenience and time-saving benefits. With busy work schedules and long commutes, many consumers prefer the ease of ordering food online and having it delivered directly to their doorstep. Additionally, the COVID-19 pandemic has accelerated the adoption of restaurant delivery services as more people are staying at home and avoiding crowded public spaces.

Trends in the market: In Thailand, the restaurant delivery market is dominated by local players such as GrabFood and Foodpanda, which have expanded rapidly in recent years. These companies have been successful in attracting customers by offering a wide range of food options from both local and international restaurants. In Indonesia, GoFood has emerged as a dominant player in the market due to its extensive network of restaurant partners and competitive pricing.

Local special circumstances: One unique aspect of the restaurant delivery market in ASEAN is the prevalence of street food culture. In countries such as Thailand and Vietnam, street food is a beloved part of the local cuisine and many customers prefer to order from street food vendors through delivery services. This has led to the emergence of specialized delivery companies that focus exclusively on street food delivery.

Underlying macroeconomic factors: The growth of the restaurant delivery market in ASEAN can be attributed to a number of underlying macroeconomic factors. The region has experienced rapid economic growth in recent years, leading to an expanding middle class with higher disposable incomes. Additionally, the rise of digital technology and e-commerce platforms has made it easier for consumers to order food online and for restaurants to offer delivery services. Finally, the COVID-19 pandemic has accelerated the adoption of restaurant delivery services as more people are staying at home and avoiding crowded public spaces.

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.