Emotional Analytics: From Personalisation To Individualisation
Emotional analytics is helping brands build richer customer profiles and tailor their experiences .
Posted on 01-08-2020
Emotions steer many decisions—both business and personal.
And in the marketing world, according to Forrester, emotion has a bigger impact on brand loyalty than how effective a product is or ease of use.
But there has been little way of measuring emotional input into consumer decision-making. As Ian Healey, enterprise marketing manager at social media management platform Hootsuite, explained: Data analytics, in its current form, only goes so far.
“Ones and zeros can only tell you so much. An incredible 93% of communication is nonverbal in nature, and that’s something that simple data analytics cannot pick up on,” Healey told CMO by Adobe.
Enter emotional analytics. Geared at better understanding how people communicate both verbally and nonverbally, emotional analytics is helping brands build richer customer profiles and tailor their experiences based on how people feel at any given moment.
“Once you gain insight into a customer’s emotional response, you can adjust your marketing collateral and brand experiences in completely new ways,” Healey said.**“**You can change the messaging, the language, or the overall tone to make it resonate deeper based on these new understandings.”
Defining Emotional Analytics
The ability to measure emotion can lead to better customer experiences, according to Bronwyn van der Merwe, managing director of Fjord Accenture Interactive Asia Pacific.
With consumers’ ever-changing expectations, emotional analytics provide insights driven from tangible data, creating an enhanced capability to deliver positive and valuable experiences.
Some insights are gathered through text analytics, which examine word choices in comments or messages to determine different sentiments about a product or service. Others, at a more advanced level, come from biometrics, vocal tones (audio analytics), and facial expressions gathered by microphones and video cameras contained within a particular device, be that a phone, computer, or even an ATM.
While widespread use of emotional analytics is still in its infancy, it’s becoming an increasingly common consideration for gaining an even deeper understanding of the customer.
Honda is one brand already on the move with emotional analytics. The Japanese automotive company partnered with Hitachi in 2018 to develop a “Sentiment Analysis Service” that collects data from publicly available word-of-mouth information. The intent was to go beyond direct customer feedback, such as what’s given over the phone at contact centres, and tap into what customers are saying about the brand in places like personal blogs and on social media.
The service uses artificial intelligence to categorise customer voices into approximately 1,300 types of topics, emotions, and intentions. It also breaks down the more classic positive, negative, and neutral categories of sentiment into 81 specific subcategories, such as “satisfaction” and “disappointment,” to build a better understanding of what’s being said.
According to Ryo Uchida, manager, social analysis promotion, at Honda, the company’s corporate communications division is already using the system to analyse reactions to announcements of new vehicles and exhibits at motor shows. He said Honda hopes to use this data for global product development, marketing strategies, and brand value enhancements.
Some in the global marketing community refer to emotional analytics as the catalyst in the move from personalisation to individualisation—a deeper, richer way of understanding and targeting customers.
Emotional analytics do this by giving marketers unprecedented insights into what their customers really want, Fjord’s van der Merwe said, citing work being done by the University of Southern California’s Institute for Creative Technologies as an example of the technology powering individualised experiences. The Institute has developed a virtual therapist to guide veterans through a Post-Deployment Health Assessment.
The artificial intelligence-powered bot therapist, known as “Ellie,” is designed to monitor micro-expressions, respond to facial cues, perform sympathetic gestures, and build rapport. In a test group of American soldiers who returned from deployment, they reported more symptoms of Post-Traumatic Stress Disorder to Ellie than when they filled out assessment forms—even when they did so anonymously.
Australia’s shopping centre giant Westfield is also experimenting with emotional analytics. The company installed small cameras fixed atop advertising screens that detect individual faces and can record the age, gender, and mood of shoppers.
“We collect data primarily to effectively manage and operate our Westfield centres,” a Westfield spokeswoman told news.com.au. “Our intention with any data that we collect is to be able to better understand our customers’ needs and connect them with retailers in a more meaningful way.”
The key to emotional analytics’ success will be the ability to tap into customers’ key characteristics in a noninvasive way where they trust the content they are exposed to, van der Merwe said.
One way to do that is by making the content relevant to the individual. Hootsuite’s Healey said consumers are tired of skin-deep personalisation.
“Say I bought a gift for my tennis-loving wife. Based on this purchase, I’d start to receive ‘personalised’ ads for tennis. I like tennis, but I don’t want my feeds being inundated with tennis ads,” he said. “That becomes tedious. Instead, the shift to individualisation takes a fuller look at me. It can recognise that perhaps I’m not that interested in tennis after all based on my more holistic online interactions.”
Concluded van der Merwe: “The next generation of consumers will be digitally mature, and they expect not just personalised, but individualised experiences. By understanding consumer characteristics, emotional analytics can help organisations make an individualised interaction with each customer.”
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