Market Insights Digital Digital Media Video Games

In-game Advertising - Jordan

Jordan

Revenue in the In-game Advertising market is projected to reach US$7.10m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2027) of 6.68%, resulting in a projected market volume of US$8.62m by 2027.
In the In-game Advertising market, the number of users is expected to amount to 0.00 by 2027.
User penetration will be 0.00 in 2024 and is expected to hit 0.00 by 2027.
In global comparison, most revenue will be generated in China (US$46,610.00m in 2024).
The average revenue per user (ARPU) in the In-game Advertising market is projected to amount to US$0.62 in 2024.

Key regions: China, India, Japan, Germany, Europe

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Methodology

Data coverage:

The data encompasses B2C revenues. Figures are based on in-app advertising spending and exclude agency commissions, rebates, production costs, and taxes. The market covers ad spending on advertisements displayed within a mobile application.

Modeling approach / Market size:

The market size is determined through a combined top-down and bottom-up approach. We use market data from independent databases, the number of application downloads from data partners, survey results taken from our primary research (e.g., the Statista Global Consumer Survey), and third-party reports to analyze and estimate global in-app advertising spending. To analyze the markets, we start by researching digital advertising in mobile applications for each advertising format, incidents of in-app and mobile browser usage, as well as the time spent in mobile apps by categories. To estimate the market size for each country individually, we use relevant key market indicators and data from country-specific industry associations, such as GDP, mobile users, and digital consumer spending. Lastly, we benchmark key countries and/or regions (e.g., global, the United States, China) with external sources.

Forecasts:

We apply a variety of forecasting techniques, depending on the behavior of the relevant market. For instance, 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.

Additional Notes:

The market is updated twice per year in case market dynamics change. GCS data is unbiased for representativeness.