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情感分析市場－全球產業規模、佔有率、趨勢、機會和預測，按類型、按技術、按最終用戶產業、按地區和競爭細分，2020-2030 年預測

Emotion Analytics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Type, By Technology, By End-User Industry, By Region & Competition, 2020-2030F
出版日期: | 出版商: TechSci Research | 英文 185 Pages | 商品交期: 2-3個工作天內

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簡介目錄

2024 年全球情緒分析市場價值為 27.5 億美元，預計到 2030 年將達到 69.7 億美元，預測期內複合年成長率為 16.58%。

市場概況
預測期 2026-2030
2024年市場規模 27.5億美元
2030年市場規模 69.7億美元
2025-2030年複合年成長率 16.58%
成長最快的領域 機器學習
最大的市場 北美洲

情感分析市場是指專注於利用人工智慧、機器學習、自然語言處理和生物感測技術等先進工具，分析、解讀和測量人類情感的技術和解決方案的行業。這些解決方案收集面部表情、語音語調、肢體語言、生理訊號和文字輸入的資料，從而獲得對人類行為和情緒反應的深刻洞察。情感分析的核心目的是幫助企業了解客戶、員工和目標受眾的情感促進因素，從而實現更有效的決策、個人化互動和更佳的參與度。

隨著零售和電子商務、醫​​療保健和生命科學、銀行和金融服務、資訊科技和電信、汽車以及媒體和娛樂等各行各業的企業擴大採用情感分析來加強客戶體驗管理、銷售最佳化、勞動力管理和精準行銷策略，市場正經歷強勁成長。數位通訊平台的日益普及和客戶接觸點的激增，推動了即時情感分析的需求，從而提升客戶滿意度和品牌忠誠度。此外，企業擴大投資於情感分析解決方案，以分析員工的幸福感、提高員工敬業度和生產力，這進一步推動了情感分析的採用。

人工智慧、深度學習和雲端部署模型等技術進步，使得情感分析解決方案更具可擴展性、準確性和成本效益，進而進一步加速市場成長。此外，線上零售、遠距醫療和客戶服務中心等領域對人性化數位互動的日益關注，也為市場創造了巨大的機會。尤其在亞太地區，由於數位轉型的快速推進、智慧型手機普及率的提升以及客戶分析投資的不斷擴大，該地區正逐漸成為一個高成長市場。

隨著企業努力在數據驅動的商業環境中保持競爭力，情感分析市場預計將大幅成長，這得益於對人類情感更深入洞察的需求、對個人化體驗的需求，以及不斷向重塑客戶和員工參與策略的智慧情感感知系統轉變。

關鍵市場促進因素

人工智慧和機器學習的技術進步推動情感分析市場

主要市場挑戰

情感分析中的資料隱私與道德問題

主要市場趨勢

情感分析與顧客體驗平台的日益融合

目錄

第 1 章：產品概述

第2章：研究方法

第3章：執行摘要

第4章：顧客之聲

第5章：全球情感分析市場展望

  • 市場規模和預測
    • 按價值
  • 市場佔有率和預測
    • 按類型（臉部表情辨識、語音和聲音辨識、生理測量、文字和情緒分析）
    • 按技術（人工智慧、機器學習、自然語言處理、生物感測技術）
    • 按最終用戶產業（銀行、金融服務和保險、零售和電子商務、醫​​療保健和生命科學、資訊科技和電信、政府和公共部門、媒體和娛樂、汽車和運輸、其他）
    • 按地區（北美、歐洲、南美、中東和非洲、亞太地區）
  • 按公司分類（2024 年）
  • 市場地圖

第6章：北美情感分析市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 北美：國家分析
    • 美國
    • 加拿大
    • 墨西哥

第7章：歐洲情感分析市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 歐洲：國家分析
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙

第8章：亞太情緒分析市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 亞太地區：國家分析
    • 中國
    • 印度
    • 日本
    • 韓國
    • 澳洲

第9章：中東與非洲情感分析市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 中東和非洲：國家分析
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非

第10章：南美情感分析市場展望

  • 市場規模和預測
  • 市場佔有率和預測
  • 南美洲：國家分析
    • 巴西
    • 哥倫比亞
    • 阿根廷

第 11 章：市場動態

  • 驅動程式
  • 挑戰

第 12 章：市場趨勢與發展

  • 合併與收購（如有）
  • 產品發布（如有）
  • 最新動態

第13章：公司簡介

  • Affectiva (a Smart Eye company)
  • Realeyes
  • nViso SA
  • Beyond Verbal Communication Ltd.
  • Kairos AR, Inc.
  • CrowdEmotion Ltd.
  • Clarabridge (now part of Qualtrics)
  • IBM Corporation
  • Microsoft Corporation
  • Tobii AB

第 14 章：策略建議

第15章調查會社について,免責事項

簡介目錄
Product Code: 30644

Global Emotion Analytics Market was valued at USD 2.75 billion in 2024 and is expected to reach USD 6.97 billion by 2030 with a CAGR of 16.58% during the forecast period.

Market Overview
Forecast Period2026-2030
Market Size 2024USD 2.75 Billion
Market Size 2030USD 6.97 Billion
CAGR 2025-203016.58%
Fastest Growing SegmentMachine Learning
Largest MarketNorth America

The Emotion Analytics Market refers to the industry focused on technologies and solutions that analyze, interpret, and measure human emotions by leveraging advanced tools such as artificial intelligence, machine learning, natural language processing, and bio-sensing technologies. These solutions gather data from facial expressions, voice intonations, body language, physiological signals, and textual inputs to derive meaningful insights into human behavior and emotional responses. The core purpose of emotion analytics is to help organizations understand the emotional drivers of their customers, employees, and target audiences, enabling more effective decision-making, personalized interactions, and improved engagement.

The market is witnessing strong growth as businesses across diverse industries, including retail and e-commerce, healthcare and life sciences, banking and financial services, information technology and telecommunications, automotive, and media and entertainment, increasingly adopt emotion analytics to strengthen customer experience management, sales optimization, workforce management, and targeted marketing strategies. The rising use of digital communication platforms and the proliferation of customer touchpoints are driving the need for real-time emotion analysis to enhance customer satisfaction and brand loyalty. Moreover, organizations are increasingly investing in emotion analytics solutions to analyze workforce well-being, improve employee engagement, and enhance productivity, which is further boosting adoption.

Technological advancements such as integration with artificial intelligence, deep learning, and cloud-based deployment models are making emotion analytics solutions more scalable, accurate, and cost-efficient, further accelerating market growth. Additionally, the growing focus on humanizing digital interactions in sectors like online retail, telemedicine, and customer service centers is creating significant opportunities for the market. The Asia Pacific region, in particular, is emerging as a high-growth market due to rapid digital transformation, increased smartphone penetration, and expanding investments in customer analytics.

As organizations strive to remain competitive in a data-driven business environment, the Emotion Analytics Market is expected to rise substantially, driven by the need for deeper insights into human emotions, the demand for personalized experiences, and the ongoing shift towards intelligent, emotion-aware systems that reshape customer and employee engagement strategies.

Key Market Drivers

Technological Advancements in Artificial Intelligence and Machine Learning Driving the Emotion Analytics Market

In the rapidly evolving landscape of the Emotion Analytics Market, technological advancements in artificial intelligence and machine learning stand as pivotal forces propelling growth and innovation, enabling organizations to harness sophisticated algorithms that decode human emotions from diverse data sources such as facial expressions, voice tones, text sentiments, and physiological signals, thereby transforming customer interactions, employee engagements, and market research methodologies into more intuitive and responsive frameworks that drive competitive advantage and operational efficiency.

These advancements facilitate the development of real-time emotion detection systems that integrate seamlessly with existing business infrastructures, allowing companies in sectors like retail, healthcare, and finance to personalize experiences, mitigate risks, and optimize strategies based on granular emotional insights, which in turn enhances customer loyalty, reduces churn rates, and boosts revenue streams through targeted interventions that resonate on a deeper psychological level. Machine learning models, particularly deep learning architectures like convolutional neural networks and recurrent neural networks, have revolutionized the accuracy and scalability of emotion analytics by processing vast datasets with unprecedented speed and precision, adapting dynamically to cultural nuances and contextual variations that traditional methods could not address, thus opening new avenues for global market expansion and cross-cultural applications.

The convergence of artificial intelligence with Internet of Things devices and big data analytics further amplifies this driver's impact, as it empowers businesses to collect multimodal data from wearable technologies, smart cameras, and social media platforms, feeding into predictive models that forecast emotional trends and behavioral patterns, enabling proactive decision-making that anticipates consumer needs before they are explicitly voiced. Moreover, the integration of natural language processing within these systems allows for sentiment analysis of unstructured data from customer reviews, call center interactions, and social media feeds, providing actionable intelligence that informs product development, marketing campaigns, and crisis management protocols, all while ensuring compliance with data privacy regulations through advanced anonymization techniques.

As organizations increasingly prioritize empathetic branding and human-centered design, these technological strides in artificial intelligence and machine learning not only streamline internal processes but also foster innovation in emerging fields like affective computing, where virtual assistants and chatbots evolve to respond empathetically, enhancing user satisfaction and fostering long-term relationships that translate into sustained market share gains. The democratization of these technologies through cloud-based platforms and open-source frameworks has lowered barriers to entry, allowing even small and medium-sized enterprises to leverage emotion analytics for strategic gains, such as refining user interfaces in e-commerce or improving patient outcomes in telemedicine by detecting distress signals early.

Furthermore, the continuous refinement of algorithms through transfer learning and federated learning approaches ensures that models remain robust against biases and adaptable to diverse populations, addressing ethical concerns and promoting inclusive growth within the Emotion Analytics Market. Investments in research and development by leading tech firms are accelerating this momentum, with breakthroughs in edge computing enabling on-device emotion processing that reduces latency and enhances privacy, critical for applications in autonomous vehicles where driver emotional states influence safety protocols, or in virtual reality environments where immersive experiences are tailored to user moods for maximum engagement.

The synergy between artificial intelligence and blockchain technology also promises secure, transparent data handling in emotion analytics, building trust among stakeholders and facilitating collaborative ecosystems where shared insights drive industry-wide advancements. As regulatory landscapes evolve to accommodate these innovations, businesses that adopt cutting-edge artificial intelligence and machine learning solutions in emotion analytics are positioned to lead in customer-centric paradigms, where emotional intelligence becomes a core competency rather than an afterthought, ultimately reshaping competitive dynamics and unlocking new revenue potentials through hyper-personalized offerings that align with evolving consumer expectations.

The proliferation of 5G networks complements these advancements by enabling high-fidelity data transmission for real-time analytics, crucial for live events or customer service scenarios where immediate emotional feedback loops can turn potential dissatisfaction into delight, thereby fortifying brand reputation and market positioning. Collaborative efforts between academia and industry are yielding hybrid models that combine supervised and unsupervised learning, improving the interpretability of emotion predictions and allowing for more nuanced business applications, such as sentiment-driven stock trading algorithms or employee wellness programs that preempt burnout through proactive interventions.

The ethical deployment of these technologies, guided by principles of fairness and transparency, ensures sustainable growth in the Emotion Analytics Market, mitigating risks associated with misinterpretation of emotions and fostering a ecosystem where innovation serves societal good. As quantum computing looms on the horizon, its potential to process complex emotional datasets at speeds unattainable today promises to further elevate the capabilities of artificial intelligence and machine learning, positioning the Emotion Analytics Market at the forefront of the fourth industrial revolution, where emotional data becomes as valuable as financial metrics in strategic planning and execution, driving holistic business transformations that prioritize human elements in digital strategies.

Recent academic studies report that transfer learning approaches in facial emotion recognition achieve an average accuracy of 96%, demonstrating the high effectiveness of advanced AI models in human-computer interaction.

Recent studies highlight impressive advancements in AI-driven emotion recognition, with convolutional neural network models achieving a test accuracy of 95% across seven basic emotions including anger, disgust, fear, happiness, sadness, surprise, and neutral. Transfer learning techniques have proven highly effective, yielding an average accuracy of 96% in facial emotion recognition for human-computer interaction applications. These accuracies underscore the robustness of machine learning and deep learning methods in analyzing facial expressions, eye movements, and biosignals, enhancing real-time emotion detection in educational and interactive environments while addressing challenges in accuracy, privacy, and cross-cultural validity.

Key Market Challenges

Data Privacy and Ethical Concerns in Emotion Analytics

One of the most critical challenges restraining the growth of the Emotion Analytics Market is the issue of data privacy and ethical concerns associated with the collection, storage, and processing of sensitive emotional data. Emotion analytics solutions rely heavily on the analysis of personal and behavioral information such as facial expressions, vocal tones, physiological signals, and textual sentiments, which are deeply private and can reveal an individual's psychological state, preferences, or vulnerabilities.

This raises serious concerns about the misuse of data, particularly when individuals are unaware that their emotions are being tracked or analyzed. Businesses adopting these solutions must comply with strict regulatory frameworks such as the General Data Protection Regulation in Europe or the California Consumer Privacy Act in the United States, which impose stringent guidelines on how consumer data should be managed, stored, and protected. Non-compliance with such regulations not only exposes companies to legal penalties but also damages brand reputation and consumer trust. Beyond regulatory compliance, ethical concerns are also intensifying, as many critics argue that analyzing human emotions without explicit consent crosses boundaries of personal autonomy and creates opportunities for manipulation in marketing, advertising, or political campaigns.

Furthermore, the integration of emotion analytics in workplaces to monitor employee engagement and productivity has sparked debates around employee rights and the psychological consequences of continuous monitoring. If employees or consumers perceive emotion analytics solutions as intrusive, it can result in backlash, resistance, or outright rejection of these technologies, thereby limiting their market adoption. Additionally, the risk of cyberattacks and data breaches creates another dimension of challenge, as emotional datasets are highly sensitive and valuable to malicious actors.

Companies must therefore invest heavily in advanced security systems and transparent data handling practices, which increases operational costs and slows down large-scale implementation. Collectively, these issues create a substantial challenge for the Emotion Analytics Market, as maintaining a balance between innovation, compliance, and ethical responsibility is extremely complex and can significantly restrict widespread adoption, particularly in highly regulated or sensitive industries.

Key Market Trends

Growing Integration of Emotion Analytics with Customer Experience Platforms

A significant trend shaping the Emotion Analytics Market is the increasing integration of emotion analytics solutions with customer experience platforms to enhance personalization and engagement. Organizations across industries are prioritizing customer-centric strategies, recognizing that consumer loyalty is not only influenced by product quality and price but also by the emotional connection a brand establishes with its customers. Emotion analytics technologies enable businesses to capture and analyze real-time emotional responses across various digital and physical touchpoints such as websites, mobile applications, call centers, and in-store interactions.

This integration allows businesses to develop a more profound understanding of customer behavior, motivations, and emotional triggers, which can then be leveraged to deliver highly tailored experiences. For instance, in retail and e-commerce, emotion analytics embedded within customer relationship management systems can help businesses detect consumer frustration during online navigation and offer immediate solutions, thereby reducing cart abandonment rates. Similarly, in the telecommunications industry, call centers equipped with voice-based emotion detection tools can identify dissatisfaction in a customer's tone and escalate the issue to specialized agents for quicker resolution.

The adoption of this trend is also being driven by advancements in artificial intelligence and natural language processing, which enable emotion analytics tools to analyze not just words but also the underlying tone and intent, providing deeper insights into customer sentiment. Businesses are increasingly investing in cloud-based customer experience management systems that seamlessly incorporate emotion analytics, as these solutions offer scalability and cost efficiency. Furthermore, industries such as banking, financial services, and insurance are deploying emotion analytics to build trust with clients by identifying emotional stress during financial interactions and offering empathetic solutions.

This trend reflects a broader shift towards humanizing digital interactions, as businesses recognize that personalization powered by emotional insights can significantly strengthen brand loyalty and long-term customer relationships. As companies continue to prioritize customer retention and satisfaction, the integration of emotion analytics into customer experience platforms will become a cornerstone of competitive differentiation in the market.

Key Market Players

  • Affectiva (a Smart Eye company)
  • Realeyes
  • nViso SA
  • Beyond Verbal Communication Ltd.
  • Kairos AR, Inc.
  • CrowdEmotion Ltd.
  • Clarabridge (now part of Qualtrics)
  • IBM Corporation
  • Microsoft Corporation
  • Tobii AB

Report Scope:

In this report, the Global Emotion Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Emotion Analytics Market, By Type:

  • Facial Expression Recognition
  • Speech and Voice Recognition
  • Physiological Measurement
  • Text and Sentiment Analysis

Emotion Analytics Market, By Technology:

  • Artificial Intelligence
  • Machine Learning
  • Natural Language Processing
  • Bio-Sensing Technology

Emotion Analytics Market, By End-User Industry:

  • Banking, Financial Services, and Insurance
  • Retail and E-commerce
  • Healthcare and Life Science
  • Information Technology and Telecommunication
  • Government and Public Sector
  • Media and Entertainment
  • Automotive and Transportation
  • Others

Emotion Analytics Market, By Region:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain
  • South America
    • Brazil
    • Argentina
    • Colombia
  • Asia-Pacific
    • China
    • India
    • Japan
    • South Korea
    • Australia
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • South Africa

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Emotion Analytics Market.

Available Customizations:

Global Emotion Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Key Industry Partners
  • 2.4. Major Association and Secondary Sources
  • 2.5. Forecasting Methodology
  • 2.6. Data Triangulation & Validation
  • 2.7. Assumptions and Limitations

3. Executive Summary

  • 3.1. Overview of the Market
  • 3.2. Overview of Key Market Segmentations
  • 3.3. Overview of Key Market Players
  • 3.4. Overview of Key Regions/Countries
  • 3.5. Overview of Market Drivers, Challenges, and Trends

4. Voice of Customer

5. Global Emotion Analytics Market Outlook

  • 5.1. Market Size & Forecast
    • 5.1.1. By Value
  • 5.2. Market Share & Forecast
    • 5.2.1. By Type (Facial Expression Recognition, Speech and Voice Recognition, Physiological Measurement, Text and Sentiment Analysis)
    • 5.2.2. By Technology (Artificial Intelligence, Machine Learning, Natural Language Processing, Bio-Sensing Technology)
    • 5.2.3. By End-User Industry (Banking, Financial Services, and Insurance, Retail and E-commerce, Healthcare and Life Sciences, Information Technology and Telecommunications, Government and Public Sector, Media and Entertainment, Automotive and Transportation, Others)
    • 5.2.4. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
  • 5.3. By Company (2024)
  • 5.4. Market Map

6. North America Emotion Analytics Market Outlook

  • 6.1. Market Size & Forecast
    • 6.1.1. By Value
  • 6.2. Market Share & Forecast
    • 6.2.1. By Type
    • 6.2.2. By Technology
    • 6.2.3. By End-User Industry
    • 6.2.4. By Country
  • 6.3. North America: Country Analysis
    • 6.3.1. United States Emotion Analytics Market Outlook
      • 6.3.1.1. Market Size & Forecast
        • 6.3.1.1.1. By Value
      • 6.3.1.2. Market Share & Forecast
        • 6.3.1.2.1. By Type
        • 6.3.1.2.2. By Technology
        • 6.3.1.2.3. By End-User Industry
    • 6.3.2. Canada Emotion Analytics Market Outlook
      • 6.3.2.1. Market Size & Forecast
        • 6.3.2.1.1. By Value
      • 6.3.2.2. Market Share & Forecast
        • 6.3.2.2.1. By Type
        • 6.3.2.2.2. By Technology
        • 6.3.2.2.3. By End-User Industry
    • 6.3.3. Mexico Emotion Analytics Market Outlook
      • 6.3.3.1. Market Size & Forecast
        • 6.3.3.1.1. By Value
      • 6.3.3.2. Market Share & Forecast
        • 6.3.3.2.1. By Type
        • 6.3.3.2.2. By Technology
        • 6.3.3.2.3. By End-User Industry

7. Europe Emotion Analytics Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Type
    • 7.2.2. By Technology
    • 7.2.3. By End-User Industry
    • 7.2.4. By Country
  • 7.3. Europe: Country Analysis
    • 7.3.1. Germany Emotion Analytics Market Outlook
      • 7.3.1.1. Market Size & Forecast
        • 7.3.1.1.1. By Value
      • 7.3.1.2. Market Share & Forecast
        • 7.3.1.2.1. By Type
        • 7.3.1.2.2. By Technology
        • 7.3.1.2.3. By End-User Industry
    • 7.3.2. France Emotion Analytics Market Outlook
      • 7.3.2.1. Market Size & Forecast
        • 7.3.2.1.1. By Value
      • 7.3.2.2. Market Share & Forecast
        • 7.3.2.2.1. By Type
        • 7.3.2.2.2. By Technology
        • 7.3.2.2.3. By End-User Industry
    • 7.3.3. United Kingdom Emotion Analytics Market Outlook
      • 7.3.3.1. Market Size & Forecast
        • 7.3.3.1.1. By Value
      • 7.3.3.2. Market Share & Forecast
        • 7.3.3.2.1. By Type
        • 7.3.3.2.2. By Technology
        • 7.3.3.2.3. By End-User Industry
    • 7.3.4. Italy Emotion Analytics Market Outlook
      • 7.3.4.1. Market Size & Forecast
        • 7.3.4.1.1. By Value
      • 7.3.4.2. Market Share & Forecast
        • 7.3.4.2.1. By Type
        • 7.3.4.2.2. By Technology
        • 7.3.4.2.3. By End-User Industry
    • 7.3.5. Spain Emotion Analytics Market Outlook
      • 7.3.5.1. Market Size & Forecast
        • 7.3.5.1.1. By Value
      • 7.3.5.2. Market Share & Forecast
        • 7.3.5.2.1. By Type
        • 7.3.5.2.2. By Technology
        • 7.3.5.2.3. By End-User Industry

8. Asia Pacific Emotion Analytics Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Type
    • 8.2.2. By Technology
    • 8.2.3. By End-User Industry
    • 8.2.4. By Country
  • 8.3. Asia Pacific: Country Analysis
    • 8.3.1. China Emotion Analytics Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Type
        • 8.3.1.2.2. By Technology
        • 8.3.1.2.3. By End-User Industry
    • 8.3.2. India Emotion Analytics Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Type
        • 8.3.2.2.2. By Technology
        • 8.3.2.2.3. By End-User Industry
    • 8.3.3. Japan Emotion Analytics Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Type
        • 8.3.3.2.2. By Technology
        • 8.3.3.2.3. By End-User Industry
    • 8.3.4. South Korea Emotion Analytics Market Outlook
      • 8.3.4.1. Market Size & Forecast
        • 8.3.4.1.1. By Value
      • 8.3.4.2. Market Share & Forecast
        • 8.3.4.2.1. By Type
        • 8.3.4.2.2. By Technology
        • 8.3.4.2.3. By End-User Industry
    • 8.3.5. Australia Emotion Analytics Market Outlook
      • 8.3.5.1. Market Size & Forecast
        • 8.3.5.1.1. By Value
      • 8.3.5.2. Market Share & Forecast
        • 8.3.5.2.1. By Type
        • 8.3.5.2.2. By Technology
        • 8.3.5.2.3. By End-User Industry

9. Middle East & Africa Emotion Analytics Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Type
    • 9.2.2. By Technology
    • 9.2.3. By End-User Industry
    • 9.2.4. By Country
  • 9.3. Middle East & Africa: Country Analysis
    • 9.3.1. Saudi Arabia Emotion Analytics Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Type
        • 9.3.1.2.2. By Technology
        • 9.3.1.2.3. By End-User Industry
    • 9.3.2. UAE Emotion Analytics Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Type
        • 9.3.2.2.2. By Technology
        • 9.3.2.2.3. By End-User Industry
    • 9.3.3. South Africa Emotion Analytics Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Type
        • 9.3.3.2.2. By Technology
        • 9.3.3.2.3. By End-User Industry

10. South America Emotion Analytics Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Type
    • 10.2.2. By Technology
    • 10.2.3. By End-User Industry
    • 10.2.4. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Emotion Analytics Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Type
        • 10.3.1.2.2. By Technology
        • 10.3.1.2.3. By End-User Industry
    • 10.3.2. Colombia Emotion Analytics Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Type
        • 10.3.2.2.2. By Technology
        • 10.3.2.2.3. By End-User Industry
    • 10.3.3. Argentina Emotion Analytics Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Type
        • 10.3.3.2.2. By Technology
        • 10.3.3.2.3. By End-User Industry

11. Market Dynamics

  • 11.1. Drivers
  • 11.2. Challenges

12. Market Trends and Developments

  • 12.1. Merger & Acquisition (If Any)
  • 12.2. Product Launches (If Any)
  • 12.3. Recent Developments

13. Company Profiles

  • 13.1. Affectiva (a Smart Eye company)
    • 13.1.1. Business Overview
    • 13.1.2. Key Revenue and Financials
    • 13.1.3. Recent Developments
    • 13.1.4. Key Personnel
    • 13.1.5. Key Product/Services Offered
  • 13.2. Realeyes
  • 13.3. nViso SA
  • 13.4. Beyond Verbal Communication Ltd.
  • 13.5. Kairos AR, Inc.
  • 13.6. CrowdEmotion Ltd.
  • 13.7. Clarabridge (now part of Qualtrics)
  • 13.8. IBM Corporation
  • 13.9. Microsoft Corporation
  • 13.10. Tobii AB

14. Strategic Recommendations

15. About Us & Disclaimer