Quick Commerce - Brazil

  • Brazil
  • The Quick Commerce market in Brazil is set to achieve a projected revenue of BRL €0.97bn by 2024.
  • This is expected to grow at an annual rate of 11.07% (CAGR 2024-2029), resulting in a projected market volume of BRL €1.64bn by 2029.
  • The number of users in the Quick Commerce market is anticipated to reach 11.9m users by 2029.
  • The user penetration rate, which is currently at 3.5% in 2024, is projected to increase to 5.3% by 2029.
  • The average revenue per user (ARPU) is expected to be BRL €127.80.
  • When compared globally, China is forecasted to generate the highest revenue in the Quick Commerce market, with an estimated amount of BRL €74,960.00m in 2024.
  • Additionally, China is expected to have the highest user penetration rate in the Quick Commerce market, reaching 21.4%.
  • Despite economic challenges, Brazil's Quick Commerce market is experiencing significant growth due to the country's large population and increasing demand for convenience.
 
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Analyst Opinion

Quick Commerce, also known as Q-commerce, is a rapidly growing market in Brazil. This market allows customers to order and receive products within a short period of time, typically within an hour. The market has seen significant growth in recent years, driven by changing customer preferences and local special circumstances.

Customer preferences:
Brazilian customers are increasingly looking for convenience and speed when it comes to shopping. This is largely due to the rise of e-commerce and the increasing availability of mobile devices. Customers are now able to order products from their phone or computer and have them delivered to their doorstep in a matter of hours. This has led to a growing demand for Q-commerce services, which offer even faster delivery times.

Trends in the market:
One of the key trends in the Q-commerce market in Brazil is the rise of local players. While international companies like Amazon and Uber Eats have entered the market, they face stiff competition from local companies like iFood and Rappi. These companies have a better understanding of the local market and are able to tailor their services to meet the needs of Brazilian customers.Another trend in the market is the increasing use of technology. Q-commerce companies are investing heavily in technology to improve their delivery times and offer more personalized services. For example, some companies are using AI-powered algorithms to predict customer behavior and offer personalized recommendations.

Local special circumstances:
Brazil has a unique geography and infrastructure that presents challenges for Q-commerce companies. The country is vast, with many remote areas that are difficult to access. This makes it challenging to offer fast and reliable delivery services across the entire country. Additionally, Brazil has a complex tax system that can make it difficult for companies to operate.

Underlying macroeconomic factors:
The growth of the Q-commerce market in Brazil is also being driven by underlying macroeconomic factors. Brazil has a large and growing middle class, which is increasingly using technology to shop. Additionally, the country has a high population density in urban areas, which makes it easier for Q-commerce companies to offer fast and reliable delivery services. Finally, the COVID-19 pandemic has accelerated the growth of the Q-commerce market in Brazil, as more customers are looking for contactless delivery options.

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.

Vue d’ensemble

  • Revenue
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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