Key regions: China, Europe, United States, Asia, Germany
The In-App Advertising market in Eastern Asia is experiencing significant growth and development due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. Customer preferences in Eastern Asia are shifting towards mobile devices as the primary means of accessing the internet and consuming content. With the increasing popularity of smartphones and tablets, users are spending more time on mobile apps, creating a lucrative opportunity for in-app advertising. Advertisers are recognizing the potential of reaching a large and engaged audience through in-app ads, leading to a rise in demand for this form of advertising. Trends in the market indicate that advertisers are increasingly adopting programmatic advertising in Eastern Asia. Programmatic advertising allows for automated ad buying and targeting, enabling advertisers to reach their desired audience more effectively. This trend is driven by the growing availability of data and advanced targeting capabilities, which enable advertisers to deliver personalized and relevant ads to users. Additionally, the use of artificial intelligence and machine learning algorithms is enhancing the efficiency and effectiveness of programmatic advertising in Eastern Asia. Local special circumstances in Eastern Asia also contribute to the development of the In-App Advertising market. The region has a large and diverse population, with different languages, cultures, and consumer behaviors. Advertisers are recognizing the importance of localized advertising campaigns to effectively engage with the target audience. This has led to an increase in the creation of localized in-app ads, tailored to the specific needs and preferences of users in Eastern Asian countries. Underlying macroeconomic factors in Eastern Asia, such as rapid urbanization and increasing disposable incomes, are driving the growth of the In-App Advertising market. As more people migrate to urban areas and gain access to smartphones and internet connectivity, the potential audience for in-app advertising expands. Additionally, rising disposable incomes in the region are leading to increased consumer spending on mobile apps and digital content, further fueling the demand for in-app advertising. In conclusion, the In-App Advertising market in Eastern Asia is experiencing growth and development due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. Advertisers are recognizing the potential of reaching a large and engaged audience through in-app ads, leading to a rise in demand for this form of advertising. The adoption of programmatic advertising, the localization of ads, and the influence of macroeconomic factors are all contributing to the growth of the market in Eastern Asia.
Data coverage:
The data encompasses B2B enterprises. 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:
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 Consumer Insights), 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 data is modeled using current exchange rates. The market is updated twice a year.
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