Quick Commerce - D-A-CH

  • D-A-CH
  • The Quick Commerce market in the D-A-CH region is anticipated to achieve a revenue of US$1.40bn by 2024.
  • This projection reflects a steady annual growth rate (CAGR 2024-2029) of 9.36%, leading to an estimated market volume of US$2.19bn by 2029.
  • Moreover, the number of users in the Quick Commerce market is expected to reach 7.5m users by 2029.
  • In terms of user penetration, the Quick Commerce market is projected to have a penetration rate of 5.0% in 2024, which is expected to increase to 7.5% by 2029.
  • The average revenue per user (ARPU) is estimated to be US$274.50.
  • When compared globally, China is predicted to generate the highest revenue in the Quick Commerce market, amounting to US$80,840.00m 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 Germany, the quick commerce market is experiencing rapid growth due to the high demand for convenience and time-saving solutions.
 
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Analyst Opinion

Quick Commerce, also known as Q-Commerce, is a rapidly growing market in the D-A-CH region, which includes Germany, Austria, and Switzerland. This market has seen significant growth in recent years, driven by changing customer preferences and the rise of e-commerce.

Customer preferences:
Customers in the D-A-CH region have increasingly turned to online shopping in recent years, with many preferring the convenience of having products delivered directly to their homes. This has led to a rise in demand for fast and efficient delivery services, which has helped to fuel the growth of the Q-Commerce market. Additionally, customers in this region have shown a preference for high-quality products and services, which has led to the emergence of premium Q-Commerce providers.

Trends in the market:
One of the key trends in the Q-Commerce market in D-A-CH is the emergence of new players in the market. This has led to increased competition and innovation, with companies looking to differentiate themselves by offering unique products and services. Another trend is the increasing use of technology to streamline the delivery process, with many companies using algorithms and artificial intelligence to optimize delivery routes and improve efficiency.

Local special circumstances:
The D-A-CH region is known for its high standards of quality and efficiency, which has led to the emergence of premium Q-Commerce providers that cater to this market. Additionally, the region has a strong culture of sustainability, which has led to the development of eco-friendly delivery options and packaging.

Underlying macroeconomic factors:
The strong economy in the D-A-CH region has helped to fuel the growth of the Q-Commerce market, with consumers having more disposable income to spend on online shopping. Additionally, the region has a highly developed infrastructure, which has made it easier for Q-Commerce providers to establish themselves and expand their operations. Finally, the region's central location in Europe has made it an attractive market for international Q-Commerce providers looking to expand their reach.

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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