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Quick Commerce - United States

United States

The Quick Commerce market in the United States is projected to reach a revenue of €52.41bn in 2024.
This is expected to show an annual growth rate of 7.93% (CAGR 2024-2029), resulting in a projected market volume of €76.76bn by 2029.
By 2029, the number of users in the Quick Commerce market is expected to amount to 71.5m users.
The user penetration rate, which is the percentage of the population using Quick Commerce market services, is projected to be 16.4% in 2024 and is expected to reach 20.4% by 2029.
The average revenue per user (ARPU) is forecasted to be €0.93k.
In global comparison, China is expected to generate the most revenue in the Quick Commerce market, with €74,960.00m in 2024.
Additionally, China will have the highest user penetration rate in the Quick Commerce market, projected to be 21.4%.
The United States is experiencing a surge in Quick Commerce, with consumers demanding faster delivery and convenience in their shopping experience.

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Analyst Opinion

Quick Commerce, also known as q-commerce, is a rising trend in the United States. With the increasing demand for convenience, consumers are looking for faster and more efficient ways to receive their purchases.

Customer preferences: Customers in the United States are showing a preference for quick and easy delivery options. The rise of e-commerce has already changed the way people shop, and now the demand for quick and efficient delivery is driving the growth of the q-commerce market. Consumers are looking for same-day or even one-hour delivery options, and companies are responding by offering these services.

Trends in the market: The q-commerce market in the United States is rapidly growing, with major players like Amazon, Walmart, and Target investing in same-day delivery options. These companies are expanding their delivery networks and partnering with local stores to offer a wider range of products and faster delivery times. Additionally, new startups are emerging in the market, offering specialized services like grocery delivery and meal kits.

Local special circumstances: The United States is a large and diverse country, with varying levels of urbanization and population density. This creates unique challenges for q-commerce companies, as they must navigate different regulations and infrastructures in different regions. For example, in densely populated cities like New York and San Francisco, delivery services must contend with traffic congestion and limited parking options. In more rural areas, companies must find ways to efficiently deliver to customers who may be farther away from distribution centers.

Underlying macroeconomic factors: The growth of the q-commerce market in the United States is driven by several macroeconomic factors. Firstly, the rise of e-commerce has created a culture of convenience and instant gratification among consumers. Secondly, the increasing use of smartphones and mobile devices has made it easier for consumers to shop online and track their deliveries. Finally, the COVID-19 pandemic has accelerated the adoption of online shopping and delivery services, as more people are staying home and avoiding physical stores. These factors have created a fertile environment for the growth of the q-commerce market in the United States.

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.