Restaurant Delivery - Eastern Europe

Eastern Europe

Highlights

The Eastern European Restaurant Delivery market is predicted to achieve a revenue of US$1.75bn by 2024.
This revenue is estimated to experience a compound annual growth rate (CAGR) of 7.31% from 2024 to 2029, resulting in a projected market volume of US$2.49bn by 2029.
Additionally, the number of users in the Eastern European Restaurant Delivery market is expected to reach 40.7m users by 2029.
In terms of user penetration, it is anticipated to be 13.0% in 2024 and is projected to increase to 17.3% by 2029.
The average revenue per user (ARPU) is expected to be US$56.48.
When compared globally, United States is forecasted to generate the highest revenue in the Restaurant Delivery market, amounting to US$36.95bn in 2024.
Furthermore, South Korea is expected to have the highest user penetration rate of 44.8%.
In Eastern Europe, the restaurant delivery market in Russia is experiencing a surge in demand due to the convenience and time-saving benefits it offers to busy urban dwellers.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Eastern European restaurant delivery market has been experiencing a significant growth in recent years.

Customer preferences: The rising popularity of online food delivery services can be attributed to the busy lifestyle of customers, who prefer the convenience of ordering food from the comfort of their homes. Moreover, the increasing number of tech-savvy millennials who value time and convenience has also contributed to the growth of the market.

Trends in the market: In Eastern Europe, the restaurant delivery market is dominated by local players who have a better understanding of the local food culture and customer preferences. However, international players are slowly making inroads into the market, offering customers a wider range of cuisine options. Furthermore, the market is witnessing a shift towards healthier food options, with more customers opting for vegetarian, vegan, and gluten-free meals.

Local special circumstances: The Eastern European market is unique in terms of its food culture, with each country having its own distinct cuisine. This has led to the emergence of several local players who are able to cater to the specific tastes of customers. Furthermore, the region has a large student population, who are price-sensitive and are more likely to opt for cheaper food options. This has led to the emergence of several budget-friendly food delivery services in the region.

Underlying macroeconomic factors: The growing popularity of the restaurant delivery market in Eastern Europe can be attributed to several macroeconomic factors. Firstly, the region has been experiencing steady economic growth, which has led to an increase in disposable income and a higher standard of living. Secondly, the region has a high internet penetration rate, which has made it easier for customers to access online food delivery services. Finally, the COVID-19 pandemic has accelerated the growth of the market, with more customers opting for food delivery services due to social distancing measures.

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.