REPORT SCOPE & OVERVIEW
The Emotion Detection and Recognition Market size was USD 37.9 billion in 2022 and is expected to Reach USD 131.2 billion by 2030 and grow at a CAGR of 16.8 % over the forecast period of 2023-2030
Emotion detection and recognition have become increasingly popular in recent years. Due to substantial developments in machine learning and artificial intelligence, the ability to read facial emotions utilizing computer vision, deep learning algorithms, and AI is known as emotion detection and recognition. Software for detecting and identifying emotions would also look at micro expressions like contempt and disdain, in addition to happiness, wrath, and sorrow. Since it offers quick and accurate results, trustworthy matching, a non-contact process, and a variety of applications such as access control, border control, crime-fighting, and law enforcement agencies. the facial expression and emotion recognition segment commands the largest market share for emotion detection and recognition. Additionally, time theft, greater security, an automated face system, simple integration, and a high success rate are some of the main advantages that support the use of facial expression recognition solutions. The use of voice-activated and gesture-activated workstations and navigation systems is expanding, driving up demand for software and hardware. Understanding emotions is essential when interacting with machine communication systems. Software that recognizes emotions enhances both the human-computer interface and the responses that computers provide to users' feedback. Without human interaction, the devices communicate data such as sensor input that regulates the output of a distant industrial process.
In Electronic Health Record (EHR) systems, the process of data capture is improved via speech recognition. By using this approach, doctors may communicate with the system by just a few phrases. From an experimental stage, emotion-sensing technology is now becoming a reality. For instance, the mood-tracking app Moodnotes uses Apple Inc.'s virtual assistant 'Siri' to customize how feelings are shown. Consequently, it would support expanding the use of emotion recognition. Many sectors now use emotional AI products and solutions to create emotionally rich experiences. It can help in the diagnosis of neurological and mental diseases in the medical field. Encourage teachers to include students more deeply in their lessons and assist hiring specialists in finding the most qualified candidates. End-user adoption is accelerating as a result of the growing technology developments in emotion detection and recognition solutions by a few chosen firms. One of the most fascinating issues is the use of cutting-edge technology to recognize emotions because it defines the interactions between humans and machines. Additionally, in countries like China, AI emotion detection technology has been used in many areas, such as police questioning and behaviour monitoring in classrooms.
MARKET DYNAMICS
KEY DRIVERS
Increasing Adoption of AI and ML
Rising Demand for Human-Computer Interaction
The growing adoption of artificial intelligence and machine learning technologies across various industries is driving the demand for emotion detection and recognition solutions.
RESTRAIN
The use of emotion detection raises privacy and ethical concerns related to data collection and potential misuse of emotional data.
The accuracy of emotion detection systems can be affected by environmental factors leading to challenges in real-world deployment.
Emotion detection algorithms need to be designed in a way that protects user privacy. This means that the algorithms should not be able to collect personal information about the user without their consent.
OPPORTUNITY
Emotion detection can be integrated into VR and AR applications to create more immersive and emotionally engaging experiences.
Emotion detection technology can be integrated with IoT devices to enhance user experiences and offer more personalized services.
Emotion detection could be used to create more realistic and engaging experiences by responding to the user's emotional state. For example, if the user is feeling scared, the VR or AR experience could become more intense, while if the user is feeling relaxed, the experience could become more serene.
CHALLENGES
Achieving real-time emotion detection and recognition, especially in resource-constrained environments, is a technical challenge
Emotion detection and recognition algorithms need to be robust to noise and variations in the data. This means that the algorithms need to be able to accurately detect and recognize emotions even when the data is noisy or the subject is not facing the camera directly.
IMPACT OF RUSSIAN UKRAINE WAR
The war has led to a heightened awareness of the importance of emotion detection and recognition technology. some estimates suggest that the market could grow by up to 20% in the next few years. This growth is being driven by the increased demand for emotion detection and recognition technology in crisis situations. This is because technology can be used to monitor and understand the emotional state of people in crisis situations. For example, the technology can be used to identify people who are at risk of self-harm or violence. The war has led to increased investment in emotion detection and recognition technology. This is because governments and businesses are recognizing the value of technology in crisis situations. For example, the US government has invested in emotion detection and recognition technology to help with the screening of refugees from Ukraine. Nuralogix is a company that develops emotion detection technology that uses EEG electroencephalography sensors. The company's technology is used to measure brain activity and identify emotions such as happiness, sadness, and anger. Nuralogix has seen a surge in interest in its technology since the war began.
IMPACT OF ONGOING RECESSION
The impact of the recession on the emotion detection and recognition market is mixed. Some companies are seeing a decrease in sales revenue and demand, while others are seeing an increase. some experts estimate that up to 20% of companies may stop using emotion detection and recognition technology during a recession. This is because businesses are often forced to cut costs during a recession, and emotion detection and recognition technology can be seen as a luxury. Companies that are seeing an increase in sales revenue and demand include those that sell emotion detection and recognition technology to governments and healthcare organizations. These organizations are increasingly using emotion detection and recognition technology to improve their services. the US government is using emotion detection and recognition technology to screen refugees for signs of trauma. And, healthcare organizations are using emotion detection and recognition technology to diagnose mental health conditions. on the other hand, Semantix is a company that develops emotion detection technology that uses facial expressions. The company's technology is used to identify emotions such as happiness, sadness, and anger. Semantix has seen a decrease in sales revenue since the recession began. The market is expected to grow in the next few years, but the pace of growth may be slower than it would have been without the recession.
KEY MARKET SEGMENTS
By Software Tool
Facial Expression
Emotion Recognition
Gesture
Posture Recognition
Voice Recognition
By Application
Law Enforcement Surveillance
Monitoring
Entertainment
Consumer Electronics
Marketing
Advertising
Others
By Technology
Pattern Recognition Network
Machine Learning
Natural Language Processing
Others
By End-Use
Commercial
Entertainment
Retail
Others
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Region Coverage:
North America
USA
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
REGIONAL ANALYSIS
North America is the largest market for emotion detection and recognition, accounting for a 30.6% share in 2021. owing to the presence of countries, such as the United States and Canada, which are home to the largest retail markets, with demand for IoT and smart wearables and high ad spending. Marketers in the region are among the global leaders in adopting technologies that enable gaining consumer insights. The United States is the dominating country in the North American market, accounting for a 25.3% share in 2021. The North American market is driven by the increasing demand for emotion detection and recognition technology in a variety of industries, including healthcare, customer service, and education.
Asia Pacific is the second-largest market for emotion detection and recognition, accounting for a 24.4% share in 2021. China is the dominating country in the Asia Pacific market, accounting for a 16.2% share in 2021. The Asia Pacific market is driven by the growing demand for emotion detection and recognition technology in countries such as China, India, and Japan. Furthermore, the growing population, strong technical centers, and the existence of a large number of companies in the region are also providing impetus for regional growth.
KEY PLAYERS
The major key players in the Emotion Detection and Recognition Market are IBM CORPORATION, Noldus Information Technology BV, Affectiva, SkyBiometry, Sentiance NV, Kairos AR, Inc., NVISO SA, Intel Corporation, Realeyes, Sightcorp, and other players.
RECENT DEVELOPMENTS
Intetics:
In August 2022, Intetics introduced a new AI facial recognition and detection solution for enterprises. Such factors help to enhance the services through a better understanding of the users that drive the market growth.
Noldus and Affectiva:
In May 10, 2023, Noldus and Affectiva announced a partnership with the University of Amsterdam to develop new research in the field of emotion detection and recognition. The partnership will focus on developing new methods for measuring and understanding emotions.
| Report Attributes | Details |
| Market Size in 2022 | US$ 37.9 Bn |
| Market Size by 2030 | US$ 131.2 Bn |
| CAGR | CAGR of 16.8 % From 2023 to 2030 |
| Base Year | 2022 |
| Forecast Period | 2023-2030 |
| Historical Data | 2020-2021 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Software Tool (Facial Expression, Emotion Recognition, Gesture, Posture Recognition, Voice Recognition) • By Application (Law Enforcement Surveillance, Monitoring, Entertainment, Consumer Electronics, Marketing, Advertising, Others) • By Technology (Pattern Recognition Network, Machine Learning, Natural Language Processing, Others) • By End User (Commercial, Entertainment, Retail, Others) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]). Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
| Company Profiles | IBM CORPORATION, Noldus Information Technology BV, Affectiva, SkyBiometry, Sentiance NV, Kairos AR, Inc., NVISO SA, Intel Corporation, Realeyes, Sightcorp |
| Key Drivers | • Increasing Adoption of AI and ML • Rising Demand for Human-Computer Interaction |
| Market Restraints | • The use of emotion detection raises privacy and ethical concerns related to data collection and potential misuse of emotional data. • The accuracy of emotion detection systems can be affected by environmental factors leading to challenges in real-world deployment. |
Ans. The Compound Annual Growth rate for Emotion Detection and Recognition Market over the forecast period is 16.8 %.
Ans. USD 131.2 Billion is the Company's projected Emotion Detection and Recognition Market size by 2030.
Ans. The Emotion Detection and Recognition Market is a market that focuses on the development and implementation of technology that can detect and recognize human emotions. This technology is used in various industries, including marketing, healthcare, and security.
Ans. Emotion Detection and Recognition technology has many applications in different fields, including market research, surveillance and monitoring, marketing and advertising, robotics and E-learning, medical emergency, and others.
Ans. The Emotion Detection and Recognition Market is segmented by technology into the following categories. Feature Extraction and 3D Modeling, Bio-Sensors and Wearables, Natural Language Processing, Machine Learning and Artificial Intelligence.
TABLE OF CONTENT
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Research Methodology
3. Market Dynamics
3.1 Drivers
3.2 Restraints
3.3 Opportunities
3.4 Challenges
4. Impact Analysis
4.1 Impact of Ukraine- Russia War
4.2 Impact of Recession
4.2.2.1 US
4.2.2.2 Canada
4.2.2.3 Germany
4.2.2.4 France
4.2.2.5 United Kingdom
4.2.2.6 China
4.2.2.7 Japan
4.2.2.8 South Korea
4.2.2.9 Rest of the World
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. Emotion Detection and Recognition Market Segmentation, by Software Tool
8.1 Facial Expression
8.2 Emotion Recognition
8.3 Gesture
8.4 Posture Recognition
8.5 Voice Recognition
9. Emotion Detection and Recognition Market Segmentation, by Application
9.1 Law Enforcement Surveillance
9.2 Monitoring
9.3 Entertainment
9.4 Consumer Electronics
9.5 Marketing
9.6 Advertising
9.7 Others
10. Emotion Detection and Recognition Market Segmentation, by Technology
10.1 Pattern Recognition Network
10.2 Machine Learning
10.3 Natural Language Processing
10.4 Other
11. Emotion Detection and Recognition Market Segmentation, by End-Use
11.1 Commercial
11.2 Entertainment
11.3 Retail
11.4 Others
12. Regional Analysis
12.1 Introduction
12.2 North America
12.2.1 North America Emotion Detection and Recognition Market by Country
12.2.2North America Emotion Detection and Recognition Market by Software Tool
12.2.3 North America Emotion Detection and Recognition Market by Application
12.2.4 North America Emotion Detection and Recognition Market by Technology
12.2.5 North America Emotion Detection and Recognition Market by End-Use
12.2.6 USA
12.2.6.1 USA Emotion Detection and Recognition Market by Software Tool
12.2.6.2 USA Emotion Detection and Recognition Market by Application
12.2.6.3 USA Emotion Detection and Recognition Market by Technology
12.2.6.4 USA Emotion Detection and Recognition Market by End-Use
12.2.7 Canada
12.2.7.1 Canada Emotion Detection and Recognition Market by Software Tool
12.2.7.2 Canada Emotion Detection and Recognition Market by Application
12.2.7.3 Canada Emotion Detection and Recognition Market by Technology
12.2.7.4 Canada Emotion Detection and Recognition Market by End-Use
12.2.8 Mexico
12.2.8.1 Mexico Emotion Detection and Recognition Market by Software Tool
12.2.8.2 Mexico Emotion Detection and Recognition Market by Application
12.2.8.3 Mexico Emotion Detection and Recognition Market by Technology
12.2.8.4 Mexico Emotion Detection and Recognition Market by End-Use
12.3 Europe
12.3.1 Eastern Europe
12.3.1.1 Eastern Europe Emotion Detection and Recognition Market by Country
12.3.1.2 Eastern Europe Emotion Detection and Recognition Market by Software Tool
12.3.1.3 Eastern Europe Emotion Detection and Recognition Market by Application
12.3.1.4 Eastern Europe Emotion Detection and Recognition Market by Technology
12.3.1.5 Eastern Europe Emotion Detection and Recognition Market by End-Use
12.3.1.6 Poland
12.3.1.6.1 Poland Emotion Detection and Recognition Market by Software Tool
12.3.1.6.2 Poland Emotion Detection and Recognition Market by Application
12.3.1.6.3 Poland Emotion Detection and Recognition Market by Technology
12.3.1.6.4 Poland Emotion Detection and Recognition Market by End-Use
12.3.1.7 Romania
12.3.1.7.1 Romania Emotion Detection and Recognition Market by Software Tool
12.3.1.7.2 Romania Emotion Detection and Recognition Market by Application
12.3.1.7.3 Romania Emotion Detection and Recognition Market by Technology
12.3.1.7.4 Romania Emotion Detection and Recognition Market by End-Use
12.3.1.8 Hungary
12.3.1.8.1 Hungary Emotion Detection and Recognition Market by Software Tool
12.3.1.8.2 Hungary Emotion Detection and Recognition Market by Application
12.3.1.8.3 Hungary Emotion Detection and Recognition Market by Technology
12.3.1.8.4 Hungary Emotion Detection and Recognition Market by End-Use
12.3.1.9 Turkey
12.3.1.9.1 Turkey Emotion Detection and Recognition Market by Software Tool
12.3.1.9.2 Turkey Emotion Detection and Recognition Market by Application
12.3.1.9.3 Turkey Emotion Detection and Recognition Market by Technology
12.3.1.9.4 Turkey Emotion Detection and Recognition Market by End-Use
12.3.1.10 Rest of Eastern Europe
12.3.1.10.1 Rest of Eastern Europe Emotion Detection and Recognition Market by Software Tool
12.3.1.10.2 Rest of Eastern Europe Emotion Detection and Recognition Market by Application
12.3.1.10.3 Rest of Eastern Europe Emotion Detection and Recognition Market by Technology
12.3.1.10.4 Rest of Eastern Europe Emotion Detection and Recognition Market by End-Use
12.3.2 Western Europe
12.3.2.1 Western Europe Emotion Detection and Recognition Market by Country
12.3.2.2 Western Europe Emotion Detection and Recognition Market by Software Tool
12.3.2.3 Western Europe Emotion Detection and Recognition Market by Application
12.3.2.4 Western Europe Emotion Detection and Recognition Market by Technology
12.3.2.5 Western Europe Emotion Detection and Recognition Market by End-Use
12.3.2.6 Germany
12.3.2.6.1 Germany Emotion Detection and Recognition Market by Software Tool
12.3.2.6.2 Germany Emotion Detection and Recognition Market by Application
12.3.2.6.3 Germany Emotion Detection and Recognition Market by Technology
12.3.2.6.4 Germany Emotion Detection and Recognition Market by End-Use
12.3.2.7 France
12.3.2.7.1 France Emotion Detection and Recognition Market by Software Tool
12.3.2.7.2 France Emotion Detection and Recognition Market by Application
12.3.2.7.3 France Emotion Detection and Recognition Market by Technology
12.3.2.7.4 France Emotion Detection and Recognition Market by End-Use
12.3.2.8 UK
12.3.2.8.1 UK Emotion Detection and Recognition Market by Software Tool
12.3.2.8.2 UK Emotion Detection and Recognition Market by Application
12.3.2.8.3 UK Emotion Detection and Recognition Market by Technology
12.3.2.8.4 UK Emotion Detection and Recognition Market by End-Use
12.3.2.9 Italy
12.3.2.9.1 Italy Emotion Detection and Recognition Market by Software Tool
12.3.2.9.2 Italy Emotion Detection and Recognition Market by Application
12.3.2.9.3 Italy Emotion Detection and Recognition Market by Technology
12.3.2.9.4 Italy Emotion Detection and Recognition Market by End-Use
12.3.2.10 Spain
12.3.2.10.1 Spain Emotion Detection and Recognition Market by Software Tool
12.3.2.10.2 Spain Emotion Detection and Recognition Market by Application
12.3.2.10.3 Spain Emotion Detection and Recognition Market by Technology
12.3.2.10.4 Spain Emotion Detection and Recognition Market by End-Use
12.3.2.11 Netherlands
12.3.2.11.1 Netherlands Emotion Detection and Recognition Market by Software Tool
12.3.2.11.2 Netherlands Emotion Detection and Recognition Market by Application
12.3.2.11.3 Netherlands Emotion Detection and Recognition Market by Technology
12.3.2.11.4 Netherlands Emotion Detection and Recognition Market by End-Use
12.3.2.12 Switzerland
12.3.2.12.1 Switzerland Emotion Detection and Recognition Market by Software Tool
12.3.2.12.2 Switzerland Emotion Detection and Recognition Market by Application
12.3.2.12.3 Switzerland Emotion Detection and Recognition Market by Technology
12.3.2.12.4 Switzerland Emotion Detection and Recognition Market by End-Use
12.3.2.13 Austria
12.3.2.13.1 Austria Emotion Detection and Recognition Market by Software Tool
12.3.2.13.2 Austria Emotion Detection and Recognition Market by Application
12.3.2.13.3 Austria Emotion Detection and Recognition Market by Technology
12.3.2.13.4 Austria Emotion Detection and Recognition Market by End-Use
12.3.2.14 Rest of Western Europe
12.3.2.14.1 Rest of Western Europe Emotion Detection and Recognition Market by Software Tool
12.3.2.14.2 Rest of Western Europe Emotion Detection and Recognition Market by Application
12.3.2.14.3 Rest of Western Europe Emotion Detection and Recognition Market by Technology
12.3.2.14.4 Rest of Western Europe Emotion Detection and Recognition Market by End-Use
12.4 Asia-Pacific
12.4.1 Asia Pacific Emotion Detection and Recognition Market by Country
12.4.2 Asia Pacific Emotion Detection and Recognition Market by Software Tool
12.4.3 Asia Pacific Emotion Detection and Recognition Market by Application
12.4.4 Asia Pacific Emotion Detection and Recognition Market by Technology
12.4.5 Asia Pacific Emotion Detection and Recognition Market by End-Use
12.4.6 China
12.4.6.1 China Emotion Detection and Recognition Market by Software Tool
12.4.6.2 China Emotion Detection and Recognition Market by Application
12.4.6.3 China Emotion Detection and Recognition Market by Technology
12.4.6.4 China Emotion Detection and Recognition Market by End-Use
12.4.7 India
12.4.7.1 India Emotion Detection and Recognition Market by Software Tool
12.4.7.2 India Emotion Detection and Recognition Market by Application
12.4.7.3 India Emotion Detection and Recognition Market by Technology
12.4.7.4 India Emotion Detection and Recognition Market by End-Use
12.4.8 Japan
12.4.8.1 Japan Emotion Detection and Recognition Market by Software Tool
12.4.8.2 Japan Emotion Detection and Recognition Market by Application
12.4.8.3 Japan Emotion Detection and Recognition Market by Technology
12.4.8.4 Japan Emotion Detection and Recognition Market by End-Use
12.4.9 South Korea
12.4.9.1 South Korea Emotion Detection and Recognition Market by Software Tool
12.4.9.2 South Korea Emotion Detection and Recognition Market by Application
12.4.9.3 South Korea Emotion Detection and Recognition Market by Technology
12.4.9.4 South Korea Emotion Detection and Recognition Market by End-Use
12.4.10 Vietnam
12.4.10.1 Vietnam Emotion Detection and Recognition Market by Software Tool
12.4.10.2 Vietnam Emotion Detection and Recognition Market by Application
12.4.10.3 Vietnam Emotion Detection and Recognition Market by Technology
12.4.10.4 Vietnam Emotion Detection and Recognition Market by End-Use
12.4.11 Singapore
12.4.11.1 Singapore Emotion Detection and Recognition Market by Software Tool
12.4.11.2 Singapore Emotion Detection and Recognition Market by Application
12.4.11.3 Singapore Emotion Detection and Recognition Market by Technology
12.4.11.4 Singapore Emotion Detection and Recognition Market by End-Use
12.4.12 Australia
12.4.12.1 Australia Emotion Detection and Recognition Market by Software Tool
12.4.12.2 Australia Emotion Detection and Recognition Market by Application
12.4.12.3 Australia Emotion Detection and Recognition Market by Technology
12.4.12.4 Australia Emotion Detection and Recognition Market by End-Use
12.4.13 Rest of Asia-Pacific
12.4.13.1 Rest of Asia-Pacific Emotion Detection and Recognition Market by Software Tool
12.4.13.2 Rest of Asia-Pacific APAC Emotion Detection and Recognition Market by Application
12.4.13.3 Rest of Asia-Pacific Emotion Detection and Recognition Market by Technology
12.4.13.4 Rest of Asia-Pacific Emotion Detection and Recognition Market by End-Use
12.5 Middle East & Africa
12.5.1 Middle East
12.5.1.1 Middle East Emotion Detection and Recognition Market by Country
12.5.1.2 Middle East Emotion Detection and Recognition Market by Software Tool
12.5.1.3 Middle East Emotion Detection and Recognition Market by Application
12.5.1.4 Middle East Emotion Detection and Recognition Market by Technology
12.5.1.5 Middle East Emotion Detection and Recognition Market by End-Use
12.5.1.6 UAE
12.5.1.6.1 UAE Emotion Detection and Recognition Market by Software Tool
12.5.1.6.2 UAE Emotion Detection and Recognition Market by Application
12.5.1.6.3 UAE Emotion Detection and Recognition Market by Technology
12.5.1.6.4 UAE Emotion Detection and Recognition Market by End-Use
12.5.1.7 Egypt
12.5.1.7.1 Egypt Emotion Detection and Recognition Market by Software Tool
12.5.1.7.2 Egypt Emotion Detection and Recognition Market by Application
12.5.1.7.3 Egypt Emotion Detection and Recognition Market by Technology
12.5.1.7.4 Egypt Emotion Detection and Recognition Market by End-Use
12.5.1.8 Saudi Arabia
12.5.1.8.1 Saudi Arabia Emotion Detection and Recognition Market by Software Tool
12.5.1.8.2 Saudi Arabia Emotion Detection and Recognition Market by Application
12.5.1.8.3 Saudi Arabia Emotion Detection and Recognition Market by Technology
12.5.1.8.4 Saudi Arabia Emotion Detection and Recognition Market by End-Use
12.5.1.9 Qatar
12.5.1.9.1 Qatar Emotion Detection and Recognition Market by Software Tool
12.5.1.9.2 Qatar Emotion Detection and Recognition Market by Application
12.5.1.9.3 Qatar Emotion Detection and Recognition Market by Technology
12.5.1.9.4 Qatar Emotion Detection and Recognition Market by End-Use
12.5.1.10 Rest of Middle East
12.5.1.10.1 Rest of Middle East Emotion Detection and Recognition Market by Software Tool
12.5.1.10.2 Rest of Middle East Emotion Detection and Recognition Market by Application
12.5.1.10.3 Rest of Middle East Emotion Detection and Recognition Market by Technology
12.5.1.10.4 Rest of Middle East Emotion Detection and Recognition Market by End-Use
12.5.2. Africa
12.5.2.1 Africa Emotion Detection and Recognition Market by Country
12.5.2.2 Africa Emotion Detection and Recognition Market by Software Tool
12.5.2.3 Africa Emotion Detection and Recognition Market by Application
12.5.2.4 Africa Emotion Detection and Recognition Market by Technology
12.5.2.5 Africa Emotion Detection and Recognition Market by End-Use
12.5.2.6 Nigeria
12.5.2.6.1 Nigeria Emotion Detection and Recognition Market by Software Tool
12.5.2.6.2 Nigeria Emotion Detection and Recognition Market by Application
12.5.2.6.3 Nigeria Emotion Detection and Recognition Market by Technology
12.5.2.6.4 Nigeria Emotion Detection and Recognition Market by End-Use
12.5.2.7 South Africa
12.5.2.7.1 South Africa Emotion Detection and Recognition Market by Software Tool
12.5.2.7.2 South Africa Emotion Detection and Recognition Market by Application
12.5.2.7.3 South Africa Emotion Detection and Recognition Market by Technology
12.5.2.7.4 South Africa Emotion Detection and Recognition Market by End-Use
12.5.2.8 Rest of Africa
12.5.2.8.1 Rest of Africa Emotion Detection and Recognition Market by Software Tool
12.5.2.8.2 Rest of Africa Emotion Detection and Recognition Market by Application
12.5.2.8.3 Rest of Africa Emotion Detection and Recognition Market by Technology
12.5.2.8.4 Rest of Africa Emotion Detection and Recognition Market by End-Use
12.6. Latin America
12.6.1 Latin America Emotion Detection and Recognition Market by Country
12.6.2 Latin America Emotion Detection and Recognition Market by Software Tool
12.6.3 Latin America Emotion Detection and Recognition Market by Application
12.6.4 Latin America Emotion Detection and Recognition Market by Technology
12.6.5 Latin America Emotion Detection and Recognition Market by End-Use
12.6.6 Brazil
12.6.6.1 Brazil Emotion Detection and Recognition Market by Software Tool
12.6.6.2 Brazil Africa Emotion Detection and Recognition Market by Application
12.6.6.3 Brazil Emotion Detection and Recognition Market by Technology
12.6.6.4 Brazil Emotion Detection and Recognition Market by End-Use
12.6.7 Argentina
12.6.7.1 Argentina Emotion Detection and Recognition Market by Software Tool
12.6.7.2 Argentina Emotion Detection and Recognition Market by Application
12.6.7.3 Argentina Emotion Detection and Recognition Market by Technology
12.6.7.4 Argentina Emotion Detection and Recognition Market by End-Use
12.6.8 Colombia
12.6.8.1 Colombia Emotion Detection and Recognition Market by Software Tool
12.6.8.2 Colombia Emotion Detection and Recognition Market by Application
12.6.8.3 Colombia Emotion Detection and Recognition Market by Technology
12.6.8.4 Colombia Emotion Detection and Recognition Market by End-Use
12.6.9 Rest of Latin America
12.6.9.1 Rest of Latin America Emotion Detection and Recognition Market by Software Tool
12.6.9.2 Rest of Latin America Emotion Detection and Recognition Market by Application
12.6.9.3 Rest of Latin America Emotion Detection and Recognition Market by Technology
12.6.9.4 Rest of Latin America Emotion Detection and Recognition Market by End-Use
13 Company profile
13.1 IBM CORPORATION
13.1.1 Company Overview
13.1.2 Financials
13.1.3Product/Services/Offerings
13.1.4 SWOT Analysis
13.1.5 The SNS View
13.2 Noldus Information Technology BV
13.2.1 Company Overview
13.2.2 Financials
13.2.3Product/Services/Offerings
13.2.4 SWOT Analysis
13.2.5 The SNS View
13.3 Affectiva
13.3.1 Company Overview
13.3.2 Financials
13.3.3Product/Services/Offerings
13.3.4 SWOT Analysis
13.3.5 The SNS View
13.4 SkyBiometry
13.4.1 Company Overview
13.4.2 Financials
13.4.3Product/Services/Offerings
13.4.4 SWOT Analysis
13.4.5 The SNS View
13.5 Sentiance NV
13.5.1 Company Overview
13.5.2 Financials
13.5.3Product/Services/Offerings
13.5.4 SWOT Analysis
13.5.5 The SNS View
13.6 Kairos AR, Inc
13.6.1 Company Overview
13.6.2 Financials
13.6.3Product/Services/Offerings
13.6.4 SWOT Analysis
13.6.5 The SNS View
13.7 NVISO SA
13.7.1 Company Overview
13.7.2 Financials
13.7.3Product/Services/Offerings
13.7.4 SWOT Analysis
13.7.5 The SNS View
13.8 Intel Corporation
13.8.1 Company Overview
13.8.2 Financial
13.8.3Product/Services/Offerings
13.8.4 SWOT Analysis
13.8.5 The SNS View
13.9 Realeyes
13.9.1 Company Overview
13.9.2 Financials
13.9.3 Product/Service/Offerings
13.9.4 SWOT Analysis
13.9.5 The SNS View
13.10 Sightcorp
13.10.1 Company Overview
13.10.2 Financials
13.10.3 Product/Service/Offerings
13.10.4 SWOT Analysis
13.10.5 The SNS View
14. Competitive Landscape
14.1 Competitive Benchmarking
14.2 Company Share Analysis
14.3 Recent Developments
14.3.1 End-Use News
14.3.2 Company News
14.3.3 Mergers & Acquisitions
15. USE Cases and Best Practices
16. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
The Emotion Detection and Recognition Market size was USD 37.9 billion in 2022 and is expected to Reach USD 131.2 billion by 2030 and grow at a CAGR of 16.8 % over the forecast period of 2023-2030
The Managed Network Services Market size was valued at USD 59.42 Bn in 2022 and is expected to reach USD 112.45 Bn by 2030, and grow at a CAGR of 8.3% over the forecast period 2023-2030.
The App Analytics Market size was USD 5.6 billion in 2022 and is expected to Reach USD 24.5billion by 2030 and grow at a CAGR of 20.3 % over the forecast period of 2023-2030
The Captive Portal Market size was USD 0.89 billion in 2022 and is expected to Reach USD 2.4 billion by 2030 and grow at a CAGR of 13.5% over the forecast period of 2023-2030
The Direct Carrier Billing Market size was valued at USD 54.83 Bn in 2022 and is expected to reach USD 153 Bn by 2030, and grow at a CAGR of 13.69% over the forecast period 2023-2030.
The Network Telemetry Market size was valued at USD 318.52 Million in 2022 and is expected to reach USD 3922.90 Million by 2030, and grow at a CAGR of 36.87% over the forecast period 2023-2030.
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