Restaurant Delivery - Central Asia

  • Central Asia
  • The Restaurant Delivery market in Central Asia is projected to reach a revenue of US$39.71m by 2024.
  • This is expected to show an annual growth rate (CAGR 2024-2029) of 4.48%, resulting in a projected market volume of US$49.45m by 2029.
  • In Central Asia's Restaurant Delivery market, the number of users is expected to reach 1.8m users by 2029.
  • The user penetration is projected to be 1.8% in 2024 and is expected to increase to 2.1% by 2029.
  • The average revenue per user (ARPU) is expected to be US$27.21.
  • In global comparison, United States is expected to generate the most revenue in the Restaurant Delivery market, with US$36,950.00m in 2024.
  • On the other hand, South Korea is projected to have the highest user penetration rate of 44.8%.
  • Central Asian consumers are increasingly embracing restaurant delivery services, as it offers convenience and a wide variety of cuisines to choose from.
 
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Analyst Opinion

The popularity of food delivery services has been on the rise in Central Asia, driven by changing consumer preferences and local special circumstances.

Customer preferences:
Consumers in Central Asia are increasingly looking for convenience and speed when it comes to their food options. With busy work schedules and hectic lifestyles, many people are turning to food delivery services as a way to save time and effort. In addition, the COVID-19 pandemic has accelerated the adoption of food delivery services as people look for ways to avoid crowded public spaces.

Trends in the market:
In Kazakhstan, the food delivery market has seen significant growth in recent years, with a number of local and international players entering the market. Customers in Kazakhstan are particularly interested in healthy food options, with many delivery services offering organic and locally-sourced ingredients. In Uzbekistan, the market is dominated by a few major players, but there is still room for growth as more people become comfortable with the idea of ordering food online. In Turkmenistan, the market is still in its early stages, but there is potential for growth as the country continues to modernize and more people gain access to smartphones and the internet.

Local special circumstances:
One of the key factors driving the growth of food delivery services in Central Asia is the lack of reliable public transportation. In many cities, it can be difficult to get around quickly and efficiently, making food delivery an attractive option for busy consumers. In addition, the region's harsh winters and hot summers make it difficult to dine out or pick up food in person, further fueling the demand for delivery services.

Underlying macroeconomic factors:
Central Asia's growing middle class is another important factor driving the growth of the food delivery market. As more people move into urban areas and earn higher incomes, they are becoming more interested in convenient and high-quality food options. In addition, the region's relatively young population is comfortable with technology and increasingly reliant on smartphones and other digital devices, making it easy for them to order food online. Finally, the COVID-19 pandemic has accelerated the adoption of food delivery services as people look for ways to stay safe and avoid crowded public spaces.

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.

Overview

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