It Is High Time to Integrate Data-Driven Analytics with Emotional Analytics for Better Customer Experience (CX)
As our intrinsic nature, we humans are likely to form an opinion about a particular commodity or person even before we have shared any real-life experience with them. The same thing happens for a business brand; we tend to have developed some sort of subconscious thoughts regarding the brand prior to using its products and services. This bias severely impacts how businesses perform in the market and their sales figures. So it is safe to assume that how brands present themselves or appeal customers play a decisive role in determining their success. Now one may wonder how companies can figure out what the customers feel or react to their products; well, this is where emotional analytics comes in.
What is Emotional Analytics?
Though data-driven Analytics provides a quick shorthand to businesses, without emotional insights, brands are a handicap. Emotional analytics, also called affective computing, play a pivotal role by identifying and analyzing the full human emotional spectrum, including mood, attitude, and emotional personality, in relation to their brand perception and preferences. They are a means through which companies can measure brand loyalties. Unlike sentiment analytics, which only assigns responses into broad positive, neutral, or negative categories, emotional analytics tells brands what people are feeling and why. This is crucial as, without deeper contextual understanding and insights, the brands can’t solve any problems nor discover if there was any in the first place. Hence, it helps businesses tailor their products and services to meet specific demands.
Why do we need it?
In a 2016 study, the Tempkin Group found that when individuals have a positive emotional association with a specific brand, they are 8.4 times more likely to trust the company, 7.1 times more likely to purchase more and 6.6 times more likely to forgive a company’s mistake. Besides, though sales figures, surveys, social media posts, ratings may help brands get a general idea about customer views, it does not provide the finer, granular insights regarding what goes unsaid. And existing conventional measures cannot intercept brand bias since they focus on measuring the probability of specific customer reactions while the customer is already having a biased outlook towards the brand.
Also, it is essential to note that emotions also have the ability to boost an advertisement or brand social media posts virality online. This is the reason why Google Android’s “Friends Furever” received massive success in 2015 as the most shared ad. The ad uses animals in its adverts to evoke a strong feeling of warmth and welling.
How can emotional analytics help?
Brands can leverage emotional analytics to identify what are the unique expectations of the customers and create a customized and personalized experience for them. For e.g., EasyJet used emotional analytics to discover what its customers felt about previous journeys they had taken, as part of its 20-year anniversary celebrations. Then it used insights based on the customer information and data to send customers personalized emails featuring their history with the airline. These emails were opened 100% more than regular email campaigns, with the word “love” being the most common word used by recipients to describe how they felt about it.
Disney uses emotion analysis to capture the real response of audiences for their movies. The practice involves capturing the viewers’ facial expressions during the course of the movie using infrared cameras placed at various angles in the theater. Then the data is fed to an artificial intelligence algorithm, which helps Disney to determine if the audience is enjoying the movie or not. Meanwhile, Bloomberg allows its clients to track the emotion in text and voice communications, helping them prevent market abuse and remain compliant. Businesses can apply this technology to their own internal communications and identify irregularities before they become problems.
Apart from that, brands can employ emotional analytics to measure the emotional reactions to different campaigns or individual advertisements and identify and repeat the successful elements in future campaigns.
Emotional analytics also helps to boost customer experience (CX). For instance, a health insurance company, Humana, has partnered with emotional intelligence solution expert Cogito Corporation to help their call-center agents deliver an improved emotional experience to the customers. They utilize voice emotion analytics to understand what the customer is feeling during the calls by analyzing the way the customer speaks. This analysis helped to boost the company’s first-call resolution as well as the Net Promoter Score (NPS). Further, it helped agents with useful suggestions like to change their vocal tone, alter the speed of speaking, and display empathy if needed, in order to turn the call positive and provide a better customer experience.
It is evident that technology could quickly become an avenue for companies to gather an even higher volume of data on users. But concentrating on the emotional aspect of customers can ensure better loyalty and lead generation and retention. This is what differentiates a leading business brand in customer and client services than others. Customers need to feel connected with a brand for a long term relationship with the brand. According to Markets and Markets, the global market of emotional analytics is expected to grow from USD 2.2 billion in 2019 to USD 4.6 billion by 2024, at a Compound Annual Growth Rate (CAGR) of 15.8% during 2019–2024. So, it is high time to start incorporating emotional analytics into business plans.