App - Norway

Norway

The revenue generated in the App market in Norway is projected to reach US$972.00m in 2022.
This indicates a positive growth trend as the market is expected to experience an annual growth rate of 8.96% between 2022 and 2027.
By 2027, the projected market volume is estimated to reach US$1,581.00m.
In terms of revenue sources, the In-app purchase (IAP) revenue in the Norwegian App market is projected to reach US$374.70m in 2022.
Additionally, the revenue from paid app downloads is expected to reach US$23.07m in the same year.
Advertising revenue, on the other hand, is projected to reach US$574.20m in 2022.
The number of app downloads in the Norwegian market is projected to reach 155.20m downloads in 2022.
This indicates a significant user base and potential for revenue generation.
Currently, the average revenue per download is estimated to be US$6.26.
When compared globally, it is interesting to note that in China generates the highest revenue in the App market, reaching US$162.90bn in 2022.
This highlights the dominance of the Chinese market in terms of revenue generation.

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

Market

Region

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Currency

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.