Sentiment analysis refers to the contextual mining of text, which identifies and extracts subjective information in the source material. Such emotional analytics reads feelings, while sentiment analysis reads intent.

The value of technology and the business it can generate is directly proportional to the ease that technology brings into human society. Thus the world is currently in the quantification of emotional data, and this is expected to reach extremes in the next decade before it consolidates.

All three fundamental forms of communication, i.e., visual, verbal, written, are input to analytics tools and lead to quantified data, i.e. sentiment analysis, primarily used for the mining of text, emotion analysis via means of verbal and visual communication. New-age marketers are relying on this quantified data to identify new targeted customer segment, to retain the customers, and to get quantified inputs for new product lines, and to implement the 7Ps of marketing.

The information gathered so far points to the fact that the Emotion Analytics market itself is growing at a CAGR of 39.4%. The emotion recognition and detection market size is estimated to grow from current USD 6.72billion in 2016 to USD 36.07billion by 2021, as per MarketsandMarkets.

Emotional Analytics is valuable in metrics for measuring the outcome out of advertisements. With emotional analytics embedded into the advertising industry, a sample of visitors viewing choices help in generating the sample data for predictive analysis. Sentiment analysis of customer comments on Twitter, Facebook, and other social media platforms helps in the realization of satisfaction, brand positioning, dissatisfaction level of product lines, etc. While emotional analytics is more related to brand equity, it also leads to more actionable processes.

In the era of e-commerce, emotional analytics plays a vital role. Companies like Amazon can improve their services via customer satisfaction index, led by emotion analytics. In fact, for the entertainment and the animation industry – companies like Disney and Pixar are processing emotional analytics to evaluate animation scenes for better user feedback and to improve the overall impression.

Such experiences offered to customers primarily drive the service and hospitality industry. Onboarding of customers and customer service till check-out time is critical. In the healthcare industry, services offered, i.e., food, doctors, medicine, treatment from employees, are personalized based on prescriptive analytics, to ensure accuracy of medicine prescriptions in hospitals. Likewise, in hotels, personalized food orders can be delivered this way. But when something goes wrong, diagnostic analysis is taken up.

Companies have always been initiating employee engagement surveys to gather data and draft future strategies for human resources. Now, along with the surveys, emotional analytics also plays a significant role. Analytics has always been a part of human civilization since ages; a person predicting the behavior of others, to make guided decisions. But, in this age when data is organized, re-usable analytics has taken shape, helping industries to grow in the future.