Quick Commerce - EU-27

  • EU-27
  • The Quick Commerce market in the EU-27 is anticipated to achieve a revenue of US$6.28bn by 2024.
  • This projection suggests a steady annual growth rate (CAGR 2024-2029) of 8.40%, resulting in a projected market volume of US$9.40bn by 2029.
  • Furthermore, the number of users in the Quick Commerce market is expected to reach 47.1m users by 2029.
  • The user penetration rate, which currently stands at 7.3% in 2024, is projected to increase to 10.6% by 2029.
  • Additionally, the average revenue per user (ARPU) is expected to reach US$193.20.
  • In terms of global comparison, China is expected to generate the highest revenue in the Quick Commerce market, amounting to US$80,840.00m in 2024.
  • Moreover, China is projected to have the highest user penetration rate in the Quick Commerce market, with a rate of 21.4%.
  • In Germany, the Quick Commerce market is experiencing rapid growth, with consumers increasingly relying on on-demand delivery services for their daily essentials.
 
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Analyst Opinion

The Quick Commerce market in EU-27 has seen significant growth in recent years, driven by changing consumer preferences and technological advancements.

Customer preferences:
Consumers in EU-27 are increasingly looking for convenience and speed in their shopping experiences. Quick Commerce, or Q-Commerce, provides a solution to this demand by offering fast and efficient delivery of goods. With the rise of on-demand services, consumers are expecting faster delivery times and more personalized experiences. Q-Commerce companies are able to meet these demands by leveraging technology and data to optimize their operations and provide a seamless customer experience.

Trends in the market:
The Q-Commerce market in EU-27 is becoming increasingly competitive, with both established players and new entrants vying for market share. Large e-commerce companies are expanding their offerings to include Q-Commerce services, while startups are emerging to specialize in this area. As the market becomes more crowded, companies are looking for ways to differentiate themselves and offer unique value propositions to consumers. Some companies are focusing on sustainability and eco-friendliness, while others are leveraging partnerships with local retailers to offer a wider selection of goods.

Local special circumstances:
The Q-Commerce market in EU-27 is diverse, with different countries and regions having unique characteristics that affect the market. For example, densely populated urban areas may have higher demand for Q-Commerce services due to traffic congestion and limited parking, while rural areas may have lower demand. Additionally, cultural differences may affect consumer preferences and willingness to adopt new technologies. Companies operating in EU-27 must take these local factors into account when developing their strategies.

Underlying macroeconomic factors:
The Q-Commerce market in EU-27 is influenced by broader macroeconomic trends, such as economic growth, inflation, and consumer confidence. A strong economy can drive consumer spending and increase demand for Q-Commerce services, while inflation can make consumers more price-sensitive. Additionally, changes in regulations and trade policies can affect the cost and availability of goods, which can in turn impact the Q-Commerce market. Companies operating in EU-27 must be aware of these underlying macroeconomic factors and adjust their strategies accordingly.

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.

Overview

  • Revenue
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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