Definition:
In-app advertising refers to the promotion of products or services within a mobile application and to ad spending on displaying advertisements within an application. This includes various formats, such as banner ads, interstitial ads, video ads, and native ads, that are integrated into the mobile app's user interface and appear as part of the app's content. The ads are usually shown to target users based on their preferences and online behavior.
Structure:
In-app advertising consists of 21 app categories, books & reference, business, education, entertainment, finance, food & drink, game, health & fitness, lifestyle, medical, music, navigation, news & magazines, photo & video, productivity, shopping, social networking, sports, travel, utilities, and weather.
Additional information:
In-app advertising comprises advertising spending, users, and average revenue per user. The market only displays B2B spending. Figures are based on in-app advertising spending and exclude agency commissions, rebates, production costs, and taxes. For more information on the data displayed and definition of each category, use the info button right next to the boxes.Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Oct 2024
Source: Statista Market Insights
Notes: The chart “Comparable Estimates” shows the forecasted development of the selected market from different sources. Please see the additional information for methodology and publication date.
Most recent update: Mar 2024
Most recent update: Oct 2024
Source: Statista Market Insights
Most recent update: Mar 2024
Source: Statista Company Insights
The In-App Advertising market in Americas is experiencing significant growth and development.
Customer preferences: Customers in the Americas have shown a strong preference for mobile devices, with a large portion of the population owning smartphones and tablets. This has led to an increase in the usage of mobile apps, creating a lucrative market for in-app advertising. Additionally, customers in the Americas are increasingly seeking personalized and relevant advertisements, which has driven the adoption of targeted in-app advertising strategies.
Trends in the market: One of the key trends in the In-App Advertising market in Americas is the shift towards programmatic advertising. Programmatic advertising allows for real-time bidding and automated ad placement, enabling advertisers to reach their target audience more effectively. This trend has been fueled by the availability of advanced data analytics and machine learning algorithms, which enable advertisers to optimize their campaigns and deliver personalized ads to users. Another trend in the market is the increasing popularity of native advertising. Native ads seamlessly blend into the app's content, providing a non-intrusive and engaging advertising experience for users. This form of advertising has gained traction in the Americas as it allows advertisers to deliver relevant and contextual ads that do not disrupt the user experience.
Local special circumstances: The Americas is a diverse region with varying levels of economic development and cultural preferences. This diversity has led to the emergence of localized in-app advertising strategies. Advertisers in the Americas are adapting their campaigns to cater to the unique preferences and needs of each country and region. For example, in countries where mobile data is expensive, advertisers are focusing on delivering lightweight and data-efficient ads to minimize data consumption for users.
Underlying macroeconomic factors: The strong economic growth in the Americas has contributed to the development of the In-App Advertising market. As economies grow, disposable incomes increase, leading to higher spending on mobile devices and apps. This growth in the user base has attracted advertisers who are looking to capitalize on the growing market. Furthermore, the increasing digitalization in the Americas has created a favorable environment for in-app advertising. With more people relying on mobile devices for various activities such as shopping, entertainment, and communication, the demand for in-app advertising has surged. Advertisers are recognizing the potential of reaching consumers through mobile apps and are allocating a larger portion of their advertising budgets to this channel. In conclusion, the In-App Advertising market in Americas is witnessing significant growth driven by customer preferences for mobile devices and personalized ads. The shift towards programmatic advertising and the popularity of native advertising are shaping the market. Localized strategies and the region's strong macroeconomic factors are further contributing to the development of the market.
Most recent update: Oct 2024
Source: Statista Market Insights
Most recent update: Oct 2024
Source: Statista Market Insights
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 Global 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 data is modeled using current exchange rates. The market is updated twice a year.Notes: Based on data from IMF, World Bank, UN and Eurostat
Most recent update: Sep 2024
Source: Statista Market Insights