Market Insights eCommerce Online Food Delivery

Meal Delivery - Brazil

Brazil

In 2024, the projected revenue in the Meal Delivery market in Brazil is expected to reach €8.44bn.
Furthermore, it is anticipated that the revenue will exhibit an annual growth rate (CAGR 2024-2029) of 4.06%, resulting in a projected market volume of €10.30bn by 2029.
The Platform Deliverymarket, on the other hand, is projected to have a market volume of €6.13bn in 2024.
In comparison to other countries, China is expected to generate the highest revenue in the Meal Delivery market, amounting to €171,100.00m in 2024.
Additionally, the average revenue per user (ARPU) in the Meal Delivery market in Brazil is projected to be €105.80 in 2024.
As for the number of users, it is expected to reach 90.5m users by 2029.
Lastly, the user penetration in the Meal Delivery market is estimated to be at 36.6% in 2024.
The meal delivery market in Brazil is experiencing a surge in demand due to the convenience and time-saving benefits it offers to busy urban dwellers.

Marché

Région

Comparaison de régions

Monnaie

Analyst Opinion

Brazil is a country known for its rich culture, diverse population, and love for food. It is no surprise that the Meal Delivery market in the country is thriving.

Customer preferences: Brazilian customers are increasingly looking for convenience and speed when it comes to their food choices. The Meal Delivery market has been able to cater to these preferences by offering a wide range of options, from traditional Brazilian cuisine to international dishes. Customers are also looking for healthy and sustainable meal options, which has prompted many Meal Delivery companies to offer organic and locally sourced ingredients.

Trends in the market: One of the biggest trends in the Meal Delivery market in Brazil is the rise of mobile ordering. Customers are now able to order their meals through mobile apps, making the process even more convenient. Another trend is the emergence of Meal Delivery companies that specialize in specific dietary requirements, such as vegan or gluten-free options. This has allowed customers to have more tailored options when it comes to their meal choices.

Local special circumstances: Brazil is a country with a high crime rate, which has led to many customers preferring to order their meals for delivery rather than going out to eat. Additionally, the country has a large population of busy professionals who do not have the time to cook or go out to eat. This has created a large demand for Meal Delivery services.

Underlying macroeconomic factors: Brazil has a growing middle class, which has led to an increase in disposable income. This increase in income has allowed customers to spend more on food, including Meal Delivery services. Additionally, the country has a large population of young people who are tech-savvy and are comfortable with ordering food online. This has created a large market for Meal Delivery companies to tap into. In conclusion, the Meal Delivery market in Brazil has been able to thrive due to a combination of customer preferences, local special circumstances, and underlying macroeconomic factors. As the market continues to grow, it will be interesting to see how Meal Delivery companies adapt to meet the changing needs and preferences of Brazilian customers.

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.