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Global Automatic Content Recognition Market to reach USD XX million by 2028.

Global Automatic Content Recognition Market Size study, By Component (Software, Services), By Technology (Audio and Video Watermarking, Audio and Video Fingerprinting, Speech Recognition, Optical Character Recognition, Other Technologies), By Deployment Mode (Cloud, On-premises), By Application (Audience Segmentation & Measurement, Broadcast Monitoring, Advertisement Targeting & Pricing, Content Filtering, Other applications), By End User (Media & Entertainment, Consumer Electronics, Retail & E-commerce, IT & Telecommunication, Other Verticals), and Regional Forecasts 2022-2028

Product Code: ICTEITS-55807898
Publish Date: 17-05-2022
Page: 200

Global Automatic Content Recognition Market is valued at approximately USD XX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2028. Automatic content recognition is a novel technology for analyzing data on a media device or within a media file. This method uses algorithms to evaluate and route information with pictures, audio, and video characteristics using real-time data. The surging demand for smart devices and content streaming services, rising penetration of speech and voice recognition technology in smart appliances, coupled with the growing deployment of automatic content recognition technologies by media & entertainment are the major factors propelling the market demand across the globe. For instance, as per Statista, in 2020, the total consumer expenditure on a smart home-related device globally is accounted for USD 86 billion, and the amount is likely to grow and reach USD 173 billion by 2025. Thereby, the rising adoption of the smart device by the population is fueling the demand for automatic content recognition, which, is bolstering the market growth in the impending years. However, overcoming loopholes in automatic content recognition technologies and rising concerns for data security impede the growth of the market over the forecast period of 2022-2028. Also, the growing adoption of AI, ML, and NLP technologies and evolving concept of contextual advertising, contextual commerce, enhanced contextual experiences, and spoiler-proof social feeds are anticipated to act as catalyzing factors for the market demand during the forecast period.

The key regions considered for the global Automatic Content Recognition Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the rising penetration of speech and voice recognition technology in smart appliances and thriving growth of the media and entertainment industry. Whereas, Asia-Pacific is anticipated to exhibit the highest CAGR over the forecast period 2022-2028. Factors such as the increasing disposable income, as well as the growing popularity of BYOD technology, would create lucrative growth prospects for the Automatic Content Recognition Market across the Asia-Pacific region.

Major market players included in this report are:
Microsoft Corporation
IBM Corporation
Google
Apple
KT Corporation
Kudelski Group
VoiceBase
Beatgrid Media BV
DataScouting
Viscovery Pte Ltd

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product Components of key players. The detailed segments and sub-segment of the market are explained below:
By Component:
Software
Services
By Technology:
Audio and Video Watermarking
Audio and Video Fingerprinting
Speech Recognition
Optical Character Recognition
Other Technologies
By Deployment Mode:
Cloud
On-premises
By Application:
Audience Segmentation & Measurement
Broadcast Monitoring
Advertisement Targeting & Pricing
Content Filtering
Other applications
By End-User:
Media & Entertainment
Consumer Electronics
Retail & E-commerce
IT & Telecommunication
Other Verticals
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Automatic Content Recognition Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Million)
1.2.1. Automatic Content Recognition Market, by Region, 2020-2028 (USD Million)
1.2.2. Automatic Content Recognition Market, by Component, 2020-2028 (USD Million)
1.2.3. Automatic Content Recognition Market, by Technology, 2020-2028 (USD Million)
1.2.4. Automatic Content Recognition Market, by Deployment Mode, 2020-2028 (USD Million)
1.2.5. Automatic Content Recognition Market, by Application, 2020-2028 (USD Million)
1.2.6. Automatic Content Recognition Market, by End-User, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Automatic Content Recognition Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Automatic Content Recognition Market Dynamics
3.1. Automatic Content Recognition Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Surging demand for smart devices and content streaming services
3.1.1.2. Rising penetration of speech and voice recognition technology in smart appliances
3.1.2. Market Challenges
3.1.2.1. Overcoming loopholes in automatic content recognition technologies
3.1.2.2. Rising concerns for data security
3.1.3. Market Opportunities
3.1.3.1. Growing adoption of AI, ML, and NLP technologies
3.1.3.2. Evolving concept of contextual advertising, contextual commerce, enhanced contextual experiences, and spoiler-proof social feeds
Chapter 4. Global Automatic Content Recognition Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Automatic Content Recognition Market, by Component
6.1. Market Snapshot
6.2. Global Automatic Content Recognition Market by Component, Performance – Potential Analysis
6.3. Global Automatic Content Recognition Market Estimates & Forecasts by Component, 2018-2028 (USD Million)
6.4. Automatic Content Recognition Market, Sub Segment Analysis
6.4.1. Software
6.4.2. Services
Chapter 7. Global Automatic Content Recognition Market, by Technology
7.1. Market Snapshot
7.2. Global Automatic Content Recognition Market by Technology, Performance – Potential Analysis
7.3. Global Automatic Content Recognition Market Estimates & Forecasts by Technology, 2018-2028 (USD Million)
7.4. Automatic Content Recognition Market, Sub Segment Analysis
7.4.1. Audio and Video Watermarking
7.4.2. Audio and Video Fingerprinting
7.4.3. Speech Recognition
7.4.4. Optical Character Recognition
7.4.5. Other Technologies
Chapter 8. Global Automatic Content Recognition Market, by Deployment Mode
8.1. Market Snapshot
8.2. Global Automatic Content Recognition Market by Deployment Mode, Performance – Potential Analysis
8.3. Global Automatic Content Recognition Market Estimates & Forecasts by Deployment Mode, 2018-2028 (USD Million)
8.4. Automatic Content Recognition Market, Sub Segment Analysis
8.4.1. Cloud
8.4.2. On-premises
Chapter 9. Global Automatic Content Recognition Market, by Application
9.1. Market Snapshot
9.2. Global Automatic Content Recognition Market by Application, Performance – Potential Analysis
9.3. Global Automatic Content Recognition Market Estimates & Forecasts by Application, 2018-2028 (USD Million)
9.4. Automatic Content Recognition Market, Sub Segment Analysis
9.4.1. Audience Segmentation & Measurement
9.4.2. Broadcast Monitoring
9.4.3. Advertisement Targeting & Pricing
9.4.4. Content Filtering
9.4.5. Other applications
Chapter 10. Global Automatic Content Recognition Market, by End-User
10.1. Market Snapshot
10.2. Global Automatic Content Recognition Market by End-User, Performance – Potential Analysis
10.3. Global Automatic Content Recognition Market Estimates & Forecasts by End-User, 2018-2028 (USD Million)
10.4. Automatic Content Recognition Market, Sub Segment Analysis
10.4.1. Media & Entertainment
10.4.2. Consumer Electronics
10.4.3. Retail & E-commerce
10.4.4. IT & Telecommunication
10.4.5. Other Verticals
Chapter 11. Global Automatic Content Recognition Market, Regional Analysis
11.1. Automatic Content Recognition Market, Regional Market Snapshot
11.2. North America Automatic Content Recognition Market
11.2.1. U.S. Automatic Content Recognition Market
11.2.1.1. Component breakdown estimates & forecasts, 2018-2028
11.2.1.2. Technology breakdown estimates & forecasts, 2018-2028
11.2.1.3. Deployment Mode breakdown estimates & forecasts, 2018-2028
11.2.1.4. Application breakdown estimates & forecasts, 2018-2028
11.2.1.5. End-User breakdown estimates & forecasts, 2018-2028
11.2.2. Canada Automatic Content Recognition Market
11.3. Europe Automatic Content Recognition Market Snapshot
11.3.1. U.K. Automatic Content Recognition Market
11.3.2. Germany Automatic Content Recognition Market
11.3.3. France Automatic Content Recognition Market
11.3.4. Spain Automatic Content Recognition Market
11.3.5. Italy Automatic Content Recognition Market
11.3.6. Rest of Europe Automatic Content Recognition Market
11.4. Asia-Pacific Automatic Content Recognition Market Snapshot
11.4.1. China Automatic Content Recognition Market
11.4.2. India Automatic Content Recognition Market
11.4.3. Japan Automatic Content Recognition Market
11.4.4. Australia Automatic Content Recognition Market
11.4.5. South Korea Automatic Content Recognition Market
11.4.6. Rest of Asia Pacific Automatic Content Recognition Market
11.5. Latin America Automatic Content Recognition Market Snapshot
11.5.1. Brazil Automatic Content Recognition Market
11.5.2. Mexico Automatic Content Recognition Market
11.6. Rest of The World Automatic Content Recognition Market

Chapter 12. Competitive Intelligence
12.1. Top Market Strategies
12.2. Company Profiles
12.2.1. Microsoft Corporation
12.2.1.1. Key Information
12.2.1.2. Overview
12.2.1.3. Financial (Subject to Data Availability)
12.2.1.4. Product Summary
12.2.1.5. Recent Developments
12.2.2. IBM Corporation
12.2.3. Google
12.2.4. Apple
12.2.5. KT Corporation
12.2.6. Kudelski Group
12.2.7. VoiceBase
12.2.8. Beatgrid Media BV
12.2.9. DataScouting
12.2.10. Viscovery Pte Ltd
Chapter 13. Research Process
13.1. Research Process
13.1.1. Data Mining
13.1.2. Analysis
13.1.3. Market Estimation
13.1.4. Validation
13.1.5. Publishing
13.2. Research Attributes
13.3. Research Assumption

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Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
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Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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