Pune, Maharashtra, Jul 04, 2019 (Wired Release) Prudour Pvt. Ltd. – Emotion analytics, also known as emotional analytics, is a technology used for analysis of expressions and emotions of customers towards a product, a brand, or any services. Emotion analytics is mainly implemented to know what a customer feels about a particular product, whether they like the product or not. Emotion analytics software is used for this purpose which helps collect data about how a customer communicates verbally and non-verbally in order to understand the customers’ mood and attitude. These technologies are mainly used by certain departments of companies such as sales, marketing, after sales services, including other departments who communicate with customers on daily basis.
Emotion analytics can prove very important to the human resources department as well. It will help them understand a candidate better in terms of the candidate’s motive towards joining the company, and if the candidate is a culture fit for the company. Moreover, timely analysis of employees can aid in getting data regarding reviews from the employees about the work culture and other important factors which will help in managing workforce and take necessary corrective measures.
Emotion analytics can be done in various ways such as facial analytics, speech analytics, video analytics, and others. Out of these types, generally, facial analytics is most preferred, and demand and adoption of facial analytics will increase in the years to come. In call centers, customer service departments, or in desk sales department, speech analytics is in high demand. This helps the companies to understand the customers’ issues and preference for their products and services by analyzing their way of talking, mood, or reactions and quantify accordingly.
Emotion analytics are mainly used in various industries such as media and entertainment, retail and education, financial services and health-care. Apart from these industries, it is used in defense sector, BPOs, and various other industries where the company needs to get feedback or know what the person on the other end thinks about products or services offered to them by reading between the lines and analyzing non-verbal communication, along with verbal communication.
Video analytics are mostly used in media and entertainment. Development of software for emotion analytics requires a huge amount of labeled emotional data. This data comes from cameras that help capture all the facial expressions, and microphones support in collecting data on voice tones. This huge amount of data is then fed into MLA (machine learning algorithms). Machine learning algorithms recognize and learn expressions, vocal tones, and other vital characteristics. Typically, emotion recognition software or other technologies categorize an individual’s emotions as either anger, disgust, frustration, contempt, fear, joy, confusion, sadness, surprise, anxiousness, etc.
Early adoption of new and advanced technologies by various companies in North America can lead to high demand for emotion analytics to a significan extent. In Asia Pacific, awareness regarding such technologies and it benefits in inclining and will result in high adoption rate in the years to come.
Some of the major players operating and profiled in the global emotion analytics market report include Microsoft, IBM, IMotions, Kairos, Beyond Verbal, Affectiva, Eyeris (EmoVu), NViso, Realeyes, Yuyidata, Adoreboard, Heartbeat AI, Deloitte, SAS Institute, Clarabridge, Crimson Hexagon, Berkshire Media, and Dentsu.
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