Casual Games - Thailand

Thailand

The Casual Games market in Thailand is anticipated to witness significant growth in the coming years.
According to projections, the total revenue is expected to reach US$58.06m in 2022.
This represents a substantial figure, highlighting the market's potential in the country.
Furthermore, the market is predicted to exhibit an impressive annual growth rate of 9.11% from 2022 to 2027, resulting in a projected market volume of US$90.06m by 2027.
This steady growth showcases the increasing popularity and demand for Casual Games market in Thailand.
Breaking down the revenue streams within the Casual Games market, it is projected that in-app purchases (IAP) will contribute significantly, reaching US$43.80m in 2022.
This indicates the willingness of consumers to invest in additional features and content within these games.
Additionally, paid app revenue is expected to reach US$2.34m in 2022, demonstrating that a portion of users are willing to pay upfront for access to premium Casual Games market.
Moreover, advertising revenue within the market is projected to reach US$11.92m in 2022, highlighting the potential for companies to monetize through advertisements within these games.
The number of downloads in the Casual Games market is also expected to rise significantly, reaching 290.60m downloads in 2022.
This surge in downloads indicates the growing interest and engagement among users in Thailand.
Currently, the average revenue per download is estimated to be US$0.20.
This metric highlights the financial benefit that developers and publishers can derive from each download, emphasizing the profitability of the Casual Games market.
In a global comparison, it is noteworthy that in the United States generates the highest revenue in the Casual Games market, projected to reach a staggering US$5,463.00m in 2022.
This demonstrates the dominance of the United States in terms of revenue generation within this market segment.
Overall, the Casual Games market in Thailand is poised for substantial growth, with various revenue streams contributing to its success.
The projected figures for revenue, downloads, and average revenue per download exemplify the opportunities for developers, publishers, and stakeholders in the country's gaming industry.

Key regions: India, United States, Europe, Japan, Asia

Market

Region

Region comparison

Currency

Analyst Opinion

Since the start of Apple, Inc.'s App Store in 2008 with around 500 apps, mobile apps have come to dominate the digital economy and have quickly outpaced the demand for desktop applications. As of 2021, the Apple App Store and Google Play Store had more than 5 million apps combined. Because many apps from the West are not available in China, many new app stores have emerged there. Digital lifestyles around the world now depend on adopting mobile apps, especially when it comes to social networking. The games industry has also been thoroughly transformed by the app revolution and is demonstrated by the fact that the games category is the largest and highest-grossing app category.

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.