App - Brazil

Brazil

The App market in Brazil is set to experience significant growth in the coming years.
By 2022, the total revenue in this market is projected to reach €4,320.00m.
This growth is expected to continue at an annual rate of 7.93% from 2022 to 2027, resulting in a projected market volume of €6,360.00m by 2027.
When looking specifically at in-app purchases (IAP), the revenue is projected to reach €1,078.00m in 2022.
Additionally, paid app revenue is expected to reach €41.65m in the same year.
On the other hand, advertising revenue is projected to reach €3,200.00m in 2022.
In terms of downloads, the App market in Brazil is expected to reach a total of 12,720.00m downloads in 2022.
Currently, the average revenue per download is estimated to be €0.34.
These figures highlight the significant growth and potential of the App market in Brazil.
When compared globally, it is worth noting that in China generates the highest revenue in the App market, with a projected revenue of €154.60bn in 2022.
This further emphasizes the importance and scale of the App market in different countries.

Key regions: China, United States, Europe, Germany, Asia

Mercado

Región

Comparación de regiones

Moneda

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on revenue from in-app purchases, revenue from the purchase of apps, and revenue from advertising, as well as the number of downloads for each app category.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market segment. As a basis for evaluating markets, we use market data from independent databases and third-party sources, current trends, and reported performance indicators of top market players. In addition, we use relevant key market indicators and data from country-specific associations, such as smartphone users and mobile broadband connections. 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 are well suited for forecasting digital products and services due to the non-linear growth of technology adoption. The main drivers are GDP/capita, level of digitization, and consumer attitudes toward apps.

Additional notes:

The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. The market is updated twice a year in case market dynamics change.