App - Saudi Arabia

Saudi Arabia

The App market in Saudi Arabia is expected to experience significant growth in the coming years.
By 2022, the total revenue in this market is projected to reach US$1,595.00m.
Furthermore, it is anticipated that the App market will continue to expand at a compound annual growth rate (CAGR 2022-2027) of 9.95%.
This growth rate is expected to result in a market volume of US$2,480.00m by 2027.
In terms of revenue sources within the App market, in-app purchases (IAP) are projected to contribute US$1,152.00m in 2022.
Additionally, paid app revenue is expected to reach US$20.18m in the same year.
Advertising revenue, on the other hand, is projected to amount to US$422.60m in 2022.
The number of app downloads in Saudi Arabia is also expected to see substantial growth, reaching 2,360.00m downloads in 2022.
Currently, the average revenue per download is estimated to be US$0.68.
When comparing the App market revenue globally, it is noteworthy that in China generates the highest revenue, with an expected revenue of US$162.90bn in 2022.

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

Market

Region

Region comparison

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.