Quick Commerce - Australia & Oceania

  • Australia & Oceania
  • The Quick Commerce market in Australia & Oceania is projected to reach a revenue of US$1.28bn in 2024.
  • This market is expected to experience an annual growth rate of 7.18% from 2024 to 2029, resulting in a projected market volume of US$1.81bn by 2029.
  • By 2029, the number of users in the Quick Commerce market is expected to reach 5.2m users.
  • In terms of user penetration, the Quick Commerce market is expected to have a penetration rate of 8.7% in 2024, which is projected to increase to 11.4% by 2029.
  • The average revenue per user (ARPU) is expected to be US$340.30.
  • When comparing the Quick Commerce market globally, China is anticipated to generate the highest revenue, amounting to US$80,840.00m in 2024.
  • Furthermore, China is also projected to have the highest user penetration rate in the Quick Commerce market, with a rate of 21.4%.
  • In Australia, the Quick Commerce market is booming with the rise of online food delivery platforms like Deliveroo and Uber Eats.
 
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Analyst Opinion

The Quick Commerce market in Australia & Oceania has been growing at a rapid pace in recent years, driven by changing customer preferences and the emergence of new technologies.

Customer preferences:
Customers in Australia & Oceania are increasingly looking for convenience and speed when it comes to shopping for goods. This has led to a surge in demand for Quick Commerce services, which offer fast and efficient delivery of goods directly to customers' doors. In addition, customers in the region are increasingly interested in sustainable and ethical products, which has led to the emergence of new Quick Commerce players focused on offering environmentally-friendly options.

Trends in the market:
One of the key trends in the Quick Commerce market in Australia & Oceania is the emergence of local players, who are focused on meeting the unique needs of customers in the region. These players often have a deep understanding of local preferences and are able to offer tailored services that meet the needs of customers in specific markets. Another trend is the increasing use of technology to improve the efficiency and speed of Quick Commerce services. This includes the use of artificial intelligence and machine learning to optimize delivery routes and improve the accuracy of delivery estimates.

Local special circumstances:
One of the key challenges facing Quick Commerce players in Australia & Oceania is the vast geography of the region. This can make it difficult to offer fast and efficient delivery to customers in remote areas. In addition, the region has a diverse mix of cultures and languages, which can make it challenging for Quick Commerce players to offer services that are tailored to the needs of local customers.

Underlying macroeconomic factors:
The growth of the Quick Commerce market in Australia & Oceania is being driven by a range of underlying macroeconomic factors, including rising incomes, increasing urbanization, and a growing middle class. In addition, the region has a young and tech-savvy population, which is driving demand for new and innovative delivery services. Finally, the region has a strong e-commerce market, which is providing a fertile ground for the growth of Quick Commerce services.

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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