Market Insights Digital Online Food Delivery Grocery Delivery

Quick Commerce - Russia

Russia

The Quick Commerce market in Russia is projected to achieve a revenue of US$1.14bn by 2024.
This estimation suggests an annual growth rate (CAGR 2024-2028) of 7.28%, resulting in a projected market volume of US$1.51bn by 2028.
Moreover, it is anticipated that the number of users in this market will reach 11.0m users by 2028.
In terms of user penetration, it is predicted to be 5.8% in 2024 and is expected to increase to 7.6% by 2028.
The average revenue per user (ARPU) is projected to be US$133.50.
When compared globally, in China is expected to generate the highest revenue in the Quick Commerce market, reaching US$80,840.00m in 2024.
Furthermore, in China is also anticipated to have the highest user penetration rate in the Quick Commerce market, with a projected rate of 21.0%.
In Russia, the Quick Commerce market is experiencing a surge in popularity as consumers increasingly rely on convenient and fast delivery services for their daily needs.

Market

Region

Region comparison

Currency

Analyst Opinion

As consumer trends turn towards ultra-convenience and consumer demands grow, Quick Commerce grocery start-up’s growth exploded. At the end of 2021, Getir, Flink, and Gorillas dominated the European markets, having a total of more than 350 locations. But as demand slows down, we see these player scale back operations. With this, we are also seeing more acquisitions between Meal Delivery players and instant grocery players such as Delivery Hero’s purchase of a majority stake in Glovo.

China leads the quick commerce market of Online Grocery Delivery owing its growth to the rapid increase of internet users, established players, and a mature digital market. Players like MissFresh, and Meituan dominate the market.

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.