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Quick Commerce - United Kingdom

United Kingdom

The revenue in the Quick Commerce market of the United Kingdom is projected to reach €2.33bn in 2024.
It is expected to show an annual growth rate (CAGR 2024-2029) of 8.79%, resulting in a projected market volume of €3.55bn by 2029.
By 2029, the number of users in the Quick Commerce market is expected to amount to 10.8m users.
The user penetration is projected to be 10.8% in 2024 and is expected to increase to 15.7% by 2029.
The average revenue per user (ARPU) is anticipated to be €317.40.
In global comparison, the highest revenue will be generated China, with €74,960.00m in 2024.
Furthermore, China will have the highest user penetration in the Quick Commerce market, with a projected rate of 21.4%.
The rise of on-demand delivery services in the United Kingdom has revolutionized the Quick Commerce market, providing consumers with unprecedented convenience and speed.

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Analyst Opinion

The Quick Commerce market in United Kingdom has been growing rapidly in recent years, driven by changing customer preferences and local special circumstances.

Customer preferences: Customers in the United Kingdom are increasingly looking for convenience and speed when it comes to their shopping experience. This has led to a rise in demand for Quick Commerce services, which allow customers to order products online and receive them within a matter of hours. In addition, customers are becoming more environmentally conscious, which has led to a growing demand for sustainable and eco-friendly products.

Trends in the market: One of the key trends in the Quick Commerce market in the United Kingdom is the increasing competition between providers. As more companies enter the market, there is a growing focus on innovation and differentiation. This has led to the development of new services and features, such as real-time tracking of deliveries and the use of drones for delivery.Another trend in the market is the rise of partnerships between Quick Commerce providers and traditional retailers. Many retailers are partnering with Quick Commerce providers to offer customers a faster and more convenient shopping experience. This has led to the development of new business models and has helped to drive the growth of the Quick Commerce market.

Local special circumstances: The United Kingdom has a highly developed e-commerce market, which has helped to drive the growth of the Quick Commerce market. In addition, the country has a large urban population, which makes it well-suited for Quick Commerce services. The high population density in cities such as London has led to a high demand for fast and convenient delivery services.

Underlying macroeconomic factors: The growth of the Quick Commerce market in the United Kingdom is also being driven by underlying macroeconomic factors. The country has a strong economy and a high level of disposable income, which has led to a growing demand for luxury and premium products. In addition, the rise of mobile technology has made it easier for customers to order products online and has helped to drive the growth of the Quick Commerce 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.