Quick Commerce - Netherlands

Netherlands

Highlights

The Quick Commerce market in the Netherlands is projected to reach a revenue of US$548.70m by 2024.
This market is expected to demonstrate an annual growth rate (CAGR 2024-2029) of 8.83%, resulting in a projected market volume of US$837.70m by 2029.
Furthermore, the number of users in the Quick Commerce market is anticipated to amount to 3.5m users by 2029.
The user penetration rate is estimated to be 13.3% in 2024 and is expected to reach 19.5% by 2029.
The average revenue per user (ARPU) is projected to be US$233.00.
In global comparison, China is expected to generate the highest revenue in the Quick Commerce market, reaching US$80.84bn by 2024.
Additionally, China is projected to have the highest user penetration rate of 21.4% in the Quick Commerce market.
The Netherlands is experiencing a surge in quick commerce platforms, with a focus on efficient delivery and a wide range of products.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Quick Commerce market in Netherlands has been rapidly developing in recent years, driven by a combination of customer preferences, local special circumstances, and underlying macroeconomic factors.

Customer preferences: Dutch customers have increasingly been demanding faster and more convenient delivery options, which has led to the rise of Quick Commerce companies. Additionally, there has been a growing trend towards online shopping, which has further fueled the demand for Quick Commerce services.

Trends in the market: One trend in the Quick Commerce market in Netherlands is the increasing use of technology to improve delivery times and optimize logistics. Many Quick Commerce companies are using advanced algorithms and machine learning to predict demand and optimize their delivery routes. Another trend is the expansion of Quick Commerce services into new areas, such as grocery delivery and pharmaceuticals.

Local special circumstances: The Netherlands has a highly urbanized population, with many people living in densely populated cities. This has led to a high demand for Quick Commerce services, as customers seek faster and more convenient delivery options in order to avoid the challenges of navigating crowded city streets. Additionally, the Netherlands has a highly developed logistics infrastructure, which has helped to support the growth of Quick Commerce companies.

Underlying macroeconomic factors: The Netherlands has a strong economy and a high standard of living, which has helped to create a favorable environment for the Quick Commerce market to thrive. Additionally, the Dutch government has been supportive of the development of new technologies and innovation, which has helped to create a favorable regulatory environment for Quick Commerce companies. Finally, the Netherlands is home to a number of large international companies, which has helped to create a thriving business ecosystem that has supported the growth of Quick Commerce companies.

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.