PUBLISHER: QYResearch | PRODUCT CODE: 1866644
PUBLISHER: QYResearch | PRODUCT CODE: 1866644
The global market for Emotion Analytics was estimated to be worth US$ 1225 million in 2024 and is forecast to a readjusted size of US$ 2633 million by 2031 with a CAGR of 12.2% during the forecast period 2025-2031.
Emotion Analytics (EA) is a new field that analysis of a person's verbal and non-verbal communication in order to understand the person's mood or attitude, then can be used in CRM (Customer Relationship Management) area, such as to identify how a customer perceives a product, the presentation of a product or an interaction with a representative.
Emotion Analytics (also known as Emotion AI or Affective Computing) is a field of technology that uses artificial intelligence, machine learning, and advanced sensors to recognize, interpret, and respond to human emotions. The market is experiencing rapid growth, driven by demand across numerous industries.
Market Drivers
1. Technological Advancements
This is the foundational driver enabling all others. The accuracy and feasibility of emotion analytics have skyrocketed recently.
AI and Machine Learning (ML): Advanced ML algorithms, particularly deep learning, can now process vast datasets (images, audio, text) to detect subtle, complex emotional cues with high accuracy.
Natural Language Processing (NLP): Sophisticated NLP goes beyond keyword spotting to understand sentiment, sarcasm, intent, and emotion in written and spoken language.
Improved Sensor Technology: The proliferation of high-resolution cameras, high-fidelity microphones, and even specialized sensors (like infrared for heart rate) provides richer data inputs for analysis.
Computing Power & Cloud Storage: The availability of affordable cloud computing and storage allows companies to process massive amounts of emotional data without massive upfront investment in infrastructure.
2. The Rising Demand for Enhanced Customer Experience (CX)
This is arguably the single largest driver, especially in competitive B2C sectors. Companies are obsessed with moving beyond simple NPS scores to understand the why behind customer feelings.
Real-Time Feedback: Analyze customer calls, live chats, and in-person interactions to gauge frustration, satisfaction, or confusion in real-time, allowing for immediate intervention.
Personalization at Scale: Emotion data allows brands to tailor product recommendations, marketing messages, and support interactions based on a user's current emotional state, creating a deeply personalized experience.
Product Development: By analyzing emotional responses to products, ads, or user interfaces, companies can refine their designs to better resonate with their target audience.
This report aims to provide a comprehensive presentation of the global market for Emotion Analytics, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Emotion Analytics by region & country, by Type, and by Application.
The Emotion Analytics market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Emotion Analytics.
Market Segmentation
By Company
Segment by Type
Segment by Application
By Region
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Emotion Analytics company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Emotion Analytics in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Emotion Analytics in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.