Market Insights eCommerce 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 2024-2029) of 7.01%, resulting in a projected market volume of US$1.60bn by 2029.
Moreover, it is anticipated that the number of users in this market will reach 11.6m users by 2029.
In terms of user penetration, it is predicted to be 5.9% in 2024 and is expected to increase to 8.2% by 2029.
The average revenue per user (ARPU) is projected to be US$133.50.
When compared globally, China is expected to generate the highest revenue in the Quick Commerce market, reaching US$80,840.00m in 2024.
Furthermore, China is also anticipated to have the highest user penetration rate in the Quick Commerce market, with a projected rate of 21.4%.
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

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Currency

Analyst Opinion

The Quick Commerce market in Russia has been rapidly growing over the past few years, with a number of key players entering the market.

Customer preferences: Russian consumers have shown a growing preference for convenience and speed when it comes to their shopping habits. Quick Commerce, or Q-Commerce, offers just that - fast delivery times and a wide range of products available at the touch of a button. With the rise of e-commerce in Russia, consumers have become accustomed to shopping online and receiving their purchases quickly. Q-Commerce takes this one step further, offering delivery times as short as 15 minutes.

Trends in the market: One of the key trends in the Q-Commerce market in Russia is the emergence of local players. While global giants like Glovo and Delivery Hero have entered the market, they face stiff competition from local companies like Samokat and Yandex.Lavka. These local players have a better understanding of the Russian market and are able to tailor their offerings to local preferences. Another trend is the expansion of Q-Commerce beyond food and grocery delivery. While food and grocery delivery still dominate the market, companies are starting to offer a wider range of products, from electronics to clothing, delivered in record time.

Local special circumstances: Russia's vast geography and extreme weather conditions can make delivery a challenge. However, Q-Commerce companies have been able to overcome these obstacles by using technology to optimize their delivery routes and ensure timely delivery. Another local circumstance is the high level of competition in the market. With so many players vying for market share, Q-Commerce companies have had to innovate and differentiate themselves in order to stand out.

Underlying macroeconomic factors: The COVID-19 pandemic has accelerated the growth of the Q-Commerce market in Russia, as consumers have become more reliant on home delivery. Additionally, Russia's relatively low level of e-commerce penetration compared to other countries has created a large market opportunity for Q-Commerce companies. Finally, the Russian government's push to modernize the economy and improve infrastructure has created an environment conducive to the growth of Q-Commerce.

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.