Quick Commerce - Eastern Europe

Eastern Europe

Highlights

The Quick Commerce market in Eastern Europe is projected to reach a revenue of US$1.43bn by 2024.
This market is expected to demonstrate an annual growth rate (CAGR 2024-2029) of 6.73%, resulting in a projected market volume of US$1.98bn by 2029.
By that year, the number of users in the Quick Commerce market is anticipated to reach 17.5m users.
The user penetration rate is estimated to be 5.4% in 2024 and is projected to increase to 7.4% by 2029.
The average revenue per user (ARPU) is expected to be US$110.20.
In terms of global comparison, China is anticipated to generate the highest revenue in the Quick Commerce market, with US$80.84bn in 2024.
Additionally, China is expected to have the highest user penetration rate in the Quick Commerce market, with a projected rate of 21.4%.
In Eastern Europe, Quick Commerce is rapidly growing, with Poland leading the way as the country with the highest number of Q-commerce platforms.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Eastern Europe has been experiencing a surge in the Quick Commerce market, with the industry set to continue its growth trajectory in the coming years. This can be attributed to several factors such as customer preferences, local special circumstances, and underlying macroeconomic factors.

Customer preferences: Customers in Eastern Europe are increasingly looking for fast and convenient ways to shop for their daily essentials. The rise of the Quick Commerce market can be attributed to the growing demand for instant delivery of goods. With the busy lifestyles of people in the region, there is a need for fast and reliable delivery of goods, which Quick Commerce companies are providing.

Trends in the market: One of the major trends in the Quick Commerce market in Eastern Europe is the increasing competition among players. With the rise in demand for instant delivery, more companies are entering the market, leading to stiff competition. Another trend is the use of technology to improve efficiency in the delivery process. Quick Commerce companies are adopting new technologies such as drones and autonomous vehicles to make deliveries faster and more efficient.

Local special circumstances: Eastern Europe is a diverse region with varying levels of economic development and infrastructure. This has led to the emergence of different models of Quick Commerce operations in different countries. For instance, in countries with well-developed infrastructure, Quick Commerce companies are using bicycles and motorbikes for deliveries, while in countries with poor infrastructure, drones and autonomous vehicles are being used.

Underlying macroeconomic factors: The Quick Commerce market in Eastern Europe is also being driven by underlying macroeconomic factors such as increasing internet penetration and smartphone usage. With more people having access to the internet and smartphones, there is a growing demand for online shopping and instant delivery. Additionally, the rise of e-commerce in the region is also contributing to the growth of the Quick Commerce market.In conclusion, the Quick Commerce market in Eastern Europe is experiencing significant growth due to customer preferences, local special circumstances, and underlying macroeconomic factors. The industry is expected to continue its growth trajectory in the coming years, with more companies entering the market and adopting new technologies to improve delivery efficiency.

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.