Restaurant Delivery - Tajikistan

Tajikistan

Highlights

The projected revenue in the Restaurant Delivery market in Tajikistan is expected to reach US$1.01m by 2024.
Furthermore, there is an anticipated annual growth rate (CAGR 2024-2029) of 6.72%, resulting in a projected market volume of US$1.40m by 2029.
As for the number of users in the Restaurant Delivery market, it is expected to amount to 82.8k users by 2029.
The user penetration rate is projected to be 0.7% in 2024 and is expected to rise to 0.7% by 2029.
The average revenue per user (ARPU) is expected to be US$15.00.
In a global comparison, United States is expected to generate the highest revenue in the Restaurant Delivery market, with an estimated amount of US$36.95bn in 2024.
On the other hand, South Korea is projected to have the highest user penetration rate in the Restaurant Delivery market, with a rate of 44.8%.
Tajikistan's restaurant delivery market is experiencing a surge in demand due to the growing urban population and increasing preference for convenience among consumers.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Tajikistan, a country located in Central Asia, has seen a significant increase in the demand for restaurant delivery services in recent years.

Customer preferences: The younger generation in Tajikistan is increasingly turning to online platforms to order food, which has led to a surge in demand for restaurant delivery services. The convenience of ordering food online and having it delivered to their doorstep is a major factor driving this trend. Additionally, with the COVID-19 pandemic, more people are staying at home and relying on delivery services for their meals.

Trends in the market: The restaurant delivery market in Tajikistan is dominated by local players, with a few international companies also operating in the country. These local players have been expanding their services to reach more customers and offer a wider range of cuisines. Furthermore, the trend of healthy eating has also influenced the restaurant delivery market, with many restaurants offering healthy and organic options on their menus.

Local special circumstances: Tajikistan has a unique cuisine that is heavily influenced by Persian, Russian, and Uzbek cuisine. This has led to a diverse range of food options being available for delivery, from traditional Tajik dishes to international cuisine. However, the lack of infrastructure and underdeveloped logistics network in the country can pose challenges for delivery companies.

Underlying macroeconomic factors: Tajikistan has a young and growing population, with a median age of just 23 years old. This demographic shift has led to a rise in demand for modern services, including restaurant delivery. Additionally, the country's improving economy and rising disposable incomes have also contributed to the growth of the restaurant delivery market. However, the country still faces challenges such as a lack of internet penetration and limited access to financial services, which can hinder the growth of the restaurant 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.