The global App Store Optimization Software Market was valued at around US$ 27,600.2 million in 2022. With a projected CAGR of 17.5% for the next ten years, the market is likely to reach a valuation of nearly US$ 160,918.1 million by the end of 2033. One of the key drivers of the app store optimization software market's growth is the expanding necessity to optimize applications for app stores.
| Attribute | Details |
|---|---|
| Global App Store Optimization Software Market Size (2022) | US$ 27,600.2 million |
| Global App Store Optimization Software Estimated Market Value (2023) | US$ 31,988.6 million |
| Global App Store Optimization Software Forecasted Market Value (2033) | US$ 160,918.1 million |
| Global App Store Optimization Software Market Growth Rate (2023 to 2033) | 17.5% CAGR |
| United States App Store Optimization Software Growth Rate (2023 to 2033) | 17.2% CAGR |
| Key Companies Covered |
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Future Market Insights’ analysis reveals that in 2022 revenue through the App Store Optimization Software Market was estimated at US$ 27.6 billion. The market for app store optimization software is expected to expand as a result of the rising need for tracking application download and rating information and the requirement for competitive intelligence mapping.
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The global market for the App Store Optimization Software Market expanded at a CAGR of 21.8% over the last four years (2018 to 2022). With an absolute dollar opportunity of US$ 109.9 billion during 2023 to 2033, the market is projected to reach a valuation of US$ 160,918.1 million by 2033.
The two key drivers of market growth are the increase in downloads and growth in the number of devoted mobile users. Increased organic app installs are one of the key benefits of Google Play Store and App Store Optimization. As a result of the marketing plan, the app will rank higher in the App Store/Play Store's search section, making it even simpler for people to find and download the app while looking for a comparable one. In the long term, this increases the likelihood of more app installs. Additionally, the number of people seeking a similar app rises when it comes to optimizing the Google Play Store or App Store app for the proper keywords.
ASO software increases the likelihood of attracting relevant traffic rather than simply consumers who accidentally land on the app page while searching for a different type of app. Furthermore, it is much simpler to persuade the appropriate customers to download and use the app once they have arrived at it. This suggests that it takes less time and money to convert consumers into paying customers.
Additionally, ASO makes suggestions for improving or keeping positioning. Many products in the market offer competitive intelligence elements, including detailed ranking and download information for both an app developed by a company and its rivals. Developers and app marketers frequently use app store optimization software to boost their app's ranking and make it stand out in app stores like the App Store and Google Play. Similar to SEO software in many aspects, app store optimization software is created expressly for app stores.
Principal Consultant
ASO offers a number of benefits over conventional updating and other forms of advertising. To promote their apps, app developers and marketers are able to select ASA keywords that suit their needs. By raising prices for exact match keywords or designating certain terms as negative keywords to prevent bidding for them, they can modify bids based on performance.
ASO ranking is primarily influenced by relevance rather than just bids, therefore advertisers must find relevant keywords rather than just bidding randomly on terms. Basic and advanced payment models are available.
The fundamental strategy is based on CPI (cost per installation), thus marketers wouldn't need to select audience granularities or pertinent keywords. Instead, Apple automatically matches ads to likely clients and allows marketers to pause them whenever they like. For advertisers who have limited time and financial resources but want to boost the number of installations, this type of ASO is appropriate. The enhanced model offers more options and provides marketers more control over their targeting abilities, making it more sophisticated.
The sophisticated approach allows marketers to choose their own keywords, manage when viewers see their ads and make use of their own creative resources. The advanced ASO, which is ideal for marketers with advertising knowledge and a sufficient budget, is based on CPT (cost per tap).
The key drawback of ASO is that it takes a lot of time and requires continual supervision. The ASO software has to be updated and needs to perform A/B testing, deep linking, and periodic description changes. Therefore, the development of the app store optimization software has been hampered by the expense of putting up teams of trained workers and equipment.
According to a study, around 3.5 million apps are now being offered on Google Play. It would affect about 11.0% of the apps by the new Google Play guidelines. This includes nearly equal shares of mobile games which are 11.2% and non-gaming apps which are 10.4%. More popular apps won't encounter many difficulties. However, this will be a significant issue for other applications that rely on utilizing every character that Google has available. In other words, the new guidelines will have the terrible unintended consequence of reducing a crucial competitive advantage for less well-known apps and games. The development of app store optimization tools has been significantly hampered by the app shop's constantly changing policies.
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The large market share of App Store Optimization Software in North America is attributed to the presence of key players along with several emerging start-ups in the region. North America accounts for 2/5th of the global app store optimization software market. It is realistic to anticipate that more North American app publishers will make investments in business growth tools and solutions.
In any event, both good and negative effects are expected to affect more than 385 thousand apps. when the app marketplaces undergo any structural modifications. There is a significant probability that these apps are already carefully selecting their keywords for optimization. That is to say, publishers are aware of the significant adjustments made by the app store businesses and will take the essential action by utilizing app store optimization software to lessen that difficulty. As a result, North America offers significant potential for future market expansion.
The United States will account for over US$ 48.8 billion of the global App Store Optimization Software Market by the year 2033. App Store Optimization Software Market growth from 2018 to 2022 was estimated at 21.4% CAGR. The United States has the headquarters of the world’s biggest IT companies like Google, Amazon, Facebook, etc. Many of the popular app stores are owned by these companies which brings huge revenue to the company. This revenue is reinvested again in the development of the platform. Hence the United States dominates the App store optimization software market.
The market growth through social media applications expanded at a CAGR of 21.2% during 2018 to 2022. With a projected CAGR of 17% for the next ten years. The social media platform has greater penetration among all sections of society. 58.4% of the world population uses one or other social media platforms, directly or indirectly. The average time spent on the platform is around 2 hours and 27 minutes. Around 450 Million people around the world came online in the past 24 hours. Providing a seamless experience is crucial for I.T. companies to survive the competition. Hence ASO market is huge potential for growth in the future.
At present, App Store Optimization companies are largely aiming to bring policy reforms in their app stores and setting up collaboration for better market capture. The key companies operating in the App Store Optimization Software Market include Gummicube, App Annie, App Radar, Lab Cave, PreApps, Tune, Appfigures, SensorTower Inc., StoreMaven, TheTool, AppTopia, PrioriData, ASODesk, AppCodes, Mobile Action, AppTweak, SearchMan, Keyword Tool, appScatter, SplitMetrics, Reflection.io, RankMyApps, AppFollow, App Annie, Adjust GmbH, MightySignal, and KUMULOS.
Some of the recent developments by key providers of the App Store Optimization Software Market are as follows:
Similarly, recent developments related to companies providing services for App Store Optimization Software have been tracked by the team at Future Market Insights, which is available in the full report.
North America is projected to emerge as a lucrative market.
The growth potential of the market is 17.5% through 2033.
A lack of trained workers is likely to limit market growth.
The United States is likely to capture a higher share of the global market.
The market is anticipated to secure a valuation of US$ 31,988.6 million in 2023.
1. Executive Summary
1.1. Global Market Outlook
1.2. Demand-side Trends
1.3. Supply-side Trends
1.4. Technology Roadmap Analysis
1.5. Analysis and Recommendations
2. Market Overview
2.1. Market Coverage / Taxonomy
2.2. Market Definition / Scope / Limitations
3. Market Background
3.1. Market Dynamics
3.1.1. Drivers
3.1.2. Restraints
3.1.3. Opportunity
3.1.4. Trends
3.2. Scenario Forecast
3.2.1. Demand in Optimistic Scenario
3.2.2. Demand in Likely Scenario
3.2.3. Demand in Conservative Scenario
3.3. Opportunity Map Analysis
3.4. Investment Feasibility Matrix
3.5. PESTLE and Porter’s Analysis
3.6. Regulatory Landscape
3.6.1. By Key Regions
3.6.2. By Key Countries
3.7. Regional Parent Market Outlook
4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033
4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022
4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033
4.2.1. Y-o-Y Growth Trend Analysis
4.2.2. Absolute $ Opportunity Analysis
5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Type
5.1. Introduction / Key Findings
5.2. Historical Market Size Value (US$ Million) Analysis By Type, 2018 to 2022
5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Type, 2023 to 2033
5.3.1. Data Platform
5.3.2. Keyword Trackers
5.3.3. Ranking Optimizing
5.4. Y-o-Y Growth Trend Analysis By Type, 2018 to 2022
5.5. Absolute $ Opportunity Analysis By Type, 2023 to 2033
6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Application
6.1. Introduction / Key Findings
6.2. Historical Market Size Value (US$ Million) Analysis By Application, 2018 to 2022
6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2023 to 2033
6.3.1. Lifestyle
6.3.2. Social Media
6.3.3. Utilities
6.3.4. Gaming and Entertainment
6.3.5. News and Information
6.3.6. Others
6.4. Y-o-Y Growth Trend Analysis By Application, 2018 to 2022
6.5. Absolute $ Opportunity Analysis By Application, 2023 to 2033
7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region
7.1. Introduction
7.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022
7.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033
7.3.1. North America
7.3.2. Latin America
7.3.3. Western Europe
7.3.4. Eastern Europe
7.3.5. South Asia and Pacific
7.3.6. East Asia
7.3.7. Middle East and Africa
7.4. Market Attractiveness Analysis By Region
8. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
8.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
8.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
8.2.1. By Country
8.2.1.1. The USA
8.2.1.2. Canada
8.2.2. By Type
8.2.3. By Application
8.3. Market Attractiveness Analysis
8.3.1. By Country
8.3.2. By Type
8.3.3. By Application
8.4. Key Takeaways
9. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
9.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
9.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
9.2.1. By Country
9.2.1.1. Brazil
9.2.1.2. Mexico
9.2.1.3. Rest of Latin America
9.2.2. By Type
9.2.3. By Application
9.3. Market Attractiveness Analysis
9.3.1. By Country
9.3.2. By Type
9.3.3. By Application
9.4. Key Takeaways
10. Western Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
10.2.1. By Country
10.2.1.1. Germany
10.2.1.2. United Kingdom
10.2.1.3. France
10.2.1.4. Spain
10.2.1.5. Italy
10.2.1.6. Rest of Western Europe
10.2.2. By Type
10.2.3. By Application
10.3. Market Attractiveness Analysis
10.3.1. By Country
10.3.2. By Type
10.3.3. By Application
10.4. Key Takeaways
11. Eastern Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
11.2.1. By Country
11.2.1.1. Poland
11.2.1.2. Russia
11.2.1.3. Czech Republic
11.2.1.4. Romania
11.2.1.5. Rest of Eastern Europe
11.2.2. By Type
11.2.3. By Application
11.3. Market Attractiveness Analysis
11.3.1. By Country
11.3.2. By Type
11.3.3. By Application
11.4. Key Takeaways
12. South Asia and Pacific Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
12.2.1. By Country
12.2.1.1. India
12.2.1.2. Bangladesh
12.2.1.3. Australia
12.2.1.4. New Zealand
12.2.1.5. Rest of South Asia and Pacific
12.2.2. By Type
12.2.3. By Application
12.3. Market Attractiveness Analysis
12.3.1. By Country
12.3.2. By Type
12.3.3. By Application
12.4. Key Takeaways
13. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
13.2.1. By Country
13.2.1.1. China
13.2.1.2. Japan
13.2.1.3. South Korea
13.2.2. By Type
13.2.3. By Application
13.3. Market Attractiveness Analysis
13.3.1. By Country
13.3.2. By Type
13.3.3. By Application
13.4. Key Takeaways
14. Middle East and Africa Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
14.2.1. By Country
14.2.1.1. GCC Countries
14.2.1.2. South Africa
14.2.1.3. Israel
14.2.1.4. Rest of MEA
14.2.2. By Type
14.2.3. By Application
14.3. Market Attractiveness Analysis
14.3.1. By Country
14.3.2. By Type
14.3.3. By Application
14.4. Key Takeaways
15. Key Countries Market Analysis
15.1. USA
15.1.1. Pricing Analysis
15.1.2. Market Share Analysis, 2022
15.1.2.1. By Type
15.1.2.2. By Application
15.2. Canada
15.2.1. Pricing Analysis
15.2.2. Market Share Analysis, 2022
15.2.2.1. By Type
15.2.2.2. By Application
15.3. Brazil
15.3.1. Pricing Analysis
15.3.2. Market Share Analysis, 2022
15.3.2.1. By Type
15.3.2.2. By Application
15.4. Mexico
15.4.1. Pricing Analysis
15.4.2. Market Share Analysis, 2022
15.4.2.1. By Type
15.4.2.2. By Application
15.5. Germany
15.5.1. Pricing Analysis
15.5.2. Market Share Analysis, 2022
15.5.2.1. By Type
15.5.2.2. By Application
15.6. United Kingdom
15.6.1. Pricing Analysis
15.6.2. Market Share Analysis, 2022
15.6.2.1. By Type
15.6.2.2. By Application
15.7. France
15.7.1. Pricing Analysis
15.7.2. Market Share Analysis, 2022
15.7.2.1. By Type
15.7.2.2. By Application
15.8. Spain
15.8.1. Pricing Analysis
15.8.2. Market Share Analysis, 2022
15.8.2.1. By Type
15.8.2.2. By Application
15.9. Italy
15.9.1. Pricing Analysis
15.9.2. Market Share Analysis, 2022
15.9.2.1. By Type
15.9.2.2. By Application
15.10. Poland
15.10.1. Pricing Analysis
15.10.2. Market Share Analysis, 2022
15.10.2.1. By Type
15.10.2.2. By Application
15.11. Russia
15.11.1. Pricing Analysis
15.11.2. Market Share Analysis, 2022
15.11.2.1. By Type
15.11.2.2. By Application
15.12. Czech Republic
15.12.1. Pricing Analysis
15.12.2. Market Share Analysis, 2022
15.12.2.1. By Type
15.12.2.2. By Application
15.13. Romania
15.13.1. Pricing Analysis
15.13.2. Market Share Analysis, 2022
15.13.2.1. By Type
15.13.2.2. By Application
15.14. India
15.14.1. Pricing Analysis
15.14.2. Market Share Analysis, 2022
15.14.2.1. By Type
15.14.2.2. By Application
15.15. Bangladesh
15.15.1. Pricing Analysis
15.15.2. Market Share Analysis, 2022
15.15.2.1. By Type
15.15.2.2. By Application
15.16. Australia
15.16.1. Pricing Analysis
15.16.2. Market Share Analysis, 2022
15.16.2.1. By Type
15.16.2.2. By Application
15.17. New Zealand
15.17.1. Pricing Analysis
15.17.2. Market Share Analysis, 2022
15.17.2.1. By Type
15.17.2.2. By Application
15.18. China
15.18.1. Pricing Analysis
15.18.2. Market Share Analysis, 2022
15.18.2.1. By Type
15.18.2.2. By Application
15.19. Japan
15.19.1. Pricing Analysis
15.19.2. Market Share Analysis, 2022
15.19.2.1. By Type
15.19.2.2. By Application
15.20. South Korea
15.20.1. Pricing Analysis
15.20.2. Market Share Analysis, 2022
15.20.2.1. By Type
15.20.2.2. By Application
15.21. GCC Countries
15.21.1. Pricing Analysis
15.21.2. Market Share Analysis, 2022
15.21.2.1. By Type
15.21.2.2. By Application
15.22. South Africa
15.22.1. Pricing Analysis
15.22.2. Market Share Analysis, 2022
15.22.2.1. By Type
15.22.2.2. By Application
15.23. Israel
15.23.1. Pricing Analysis
15.23.2. Market Share Analysis, 2022
15.23.2.1. By Type
15.23.2.2. By Application
16. Market Structure Analysis
16.1. Competition Dashboard
16.2. Competition Benchmarking
16.3. Market Share Analysis of Top Players
16.3.1. By Regional
16.3.2. By Type
16.3.3. By Application
17. Competition Analysis
17.1. Competition Deep Dive
17.1.1. Gummicube
17.1.1.1. Overview
17.1.1.2. Product Portfolio
17.1.1.3. Profitability by Market Segments
17.1.1.4. Sales Footprint
17.1.1.5. Strategy Overview
17.1.1.5.1. Marketing Strategy
17.1.2. App Annie
17.1.2.1. Overview
17.1.2.2. Product Portfolio
17.1.2.3. Profitability by Market Segments
17.1.2.4. Sales Footprint
17.1.2.5. Strategy Overview
17.1.2.5.1. Marketing Strategy
17.1.3. App Radar
17.1.3.1. Overview
17.1.3.2. Product Portfolio
17.1.3.3. Profitability by Market Segments
17.1.3.4. Sales Footprint
17.1.3.5. Strategy Overview
17.1.3.5.1. Marketing Strategy
17.1.4. Lab Cave
17.1.4.1. Overview
17.1.4.2. Product Portfolio
17.1.4.3. Profitability by Market Segments
17.1.4.4. Sales Footprint
17.1.4.5. Strategy Overview
17.1.4.5.1. Marketing Strategy
17.1.5. PreApps, Tune
17.1.5.1. Overview
17.1.5.2. Product Portfolio
17.1.5.3. Profitability by Market Segments
17.1.5.4. Sales Footprint
17.1.5.5. Strategy Overview
17.1.5.5.1. Marketing Strategy
17.1.6. Appfigures
17.1.6.1. Overview
17.1.6.2. Product Portfolio
17.1.6.3. Profitability by Market Segments
17.1.6.4. Sales Footprint
17.1.6.5. Strategy Overview
17.1.6.5.1. Marketing Strategy
17.1.7. SensorTower Inc.
17.1.7.1. Overview
17.1.7.2. Product Portfolio
17.1.7.3. Profitability by Market Segments
17.1.7.4. Sales Footprint
17.1.7.5. Strategy Overview
17.1.7.5.1. Marketing Strategy
17.1.8. StoreMaven
17.1.8.1. Overview
17.1.8.2. Product Portfolio
17.1.8.3. Profitability by Market Segments
17.1.8.4. Sales Footprint
17.1.8.5. Strategy Overview
17.1.8.5.1. Marketing Strategy
17.1.9. TheTool
17.1.9.1. Overview
17.1.9.2. Product Portfolio
17.1.9.3. Profitability by Market Segments
17.1.9.4. Sales Footprint
17.1.9.5. Strategy Overview
17.1.9.5.1. Marketing Strategy
17.1.10. AppTopia
17.1.10.1. Overview
17.1.10.2. Product Portfolio
17.1.10.3. Profitability by Market Segments
17.1.10.4. Sales Footprint
17.1.10.5. Strategy Overview
17.1.10.5.1. Marketing Strategy
18. Assumptions & Acronyms Used
19. Research Methodology
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App Store Optimization Software Market
