Dwayne Charrington
Did you know people with damage in the brain parts that trigger emotions find it difficult to make decisions? According to studies by neuroscientist Antonio Damasio, this is true. For businesses, this means that if their content/product/services are not evoking emotions, then customers will not be easy buyers. This realization has culminated in the worldwide popularity of emotion recognition technology, which is set to grow into a whopping $65 billion industry by 2023.
Value of emotions
For every business, nowadays, figuring out how customers feel has become a top priority. And, this is only because the technology of today has enabled and empowered businesses to do so. Fueled by computer vision and advanced face analysis algorithms, emotion recognition technology is now used to measure emotions and facial expressions. It can recognize feelings like those of anger, fear, disgust, confusion and happiness.
It is invaluable in deciphering what a business’ target audience is feeling and wanting. With such insights, product development, marketing campaigns and customer support can be tailored to provide customers with the value that they actually want. And, this emotionally focused modus operandi succeeds more than the rational one.
Take the example of Dove’s ‘Real Beauty’ campaign or how Nike positions all of its marketing and content. They appeal to our emotions of beauty and personal potential, respectively- something which all of us have felt strongly about at least once. And so, these campaigns are recorded in the annals of history as being big hits.
Even B2B ventures can also succeed with this shift in focus. According to a research report, titled ‘From Promotion to Emotion: Connecting B2B Customers to Brands’, by CES and Google, the impact of B2B companies shot up 2x when they appealed to the emotions of customers.
How are Companies Already Using Emotion Recognition Technology?
As unfamiliar as the name might sound to some, emotion detection is already being leveraged in certain domains and businesses. And this is yielding very interesting and positive results. Here are a few examples:
Video games: What if the sequences in video games could change in real-time? What if a one-size-fits-all experience does not need to be created? Wouldn’t that make video games more interesting? Certainly, it will.
Nevermind uses a webcam to keep tabs on a player’s emotions. Depending on the level of fear/anxiety/tension, it alters the difficulty level. So, if the game becomes easier when the player is calm, it will direct the player to control his/her stress reactions. Not only will this positively affect the player’s EQ, but also create a personalized experience for them that they can alter by will.
Market research: Most market research involves customers recalling certain encounters, emotions, moments and reactions. While they are useful, they are not accurate. Our brain is a complex maze of information. Even after an awful customer support experience, if a person was to receive the news of their promotion, the experience wouldn’t bug them so much. In fact, they might just forget about it.
Alternately, if they had kept experiencing a string of annoying circumstances, they might remember the support experience differently. The recognition technology helps to drastically reduce this variability by capturing the reactions and emotions of customers in real-time.
Disney recognized this advantage and has been using the technology to determine audience reactions to its movies – whether they enjoyed it, hated it or felt okayish about it. The AI-powered algorithm, which involves Factorised Variation Auto Encoders (FVAE), is used to recognize complex facial expressions and even predict upcoming emotions. Infrared cameras laced with this technology were set up during the movie screenings of ‘The Jungle Book’ and ‘Star Wars: The Force Awakens.’
Digital ads: Kellogg’s used Affectiva’s emotion detection technology to test audience reaction to its cereal. The company ran multiple ads for the same cereal.
For one of the ads, it was found that while it evoked laughter when watched for the first time, the engagement rate on the second watch was very low. This led Kellogg’s to intelligently decide to go with the ad version that produced steady levels of engagement instead of one-time explosive ones. This opens up major opportunities to improve customer support, experience and sales by deciphering what customers are positively responding to over a consistent period of time.
Candidate interviews: Using HireVue’s AI-powered technology, Unilever has managed to increase the efficiency and quality of its hiring process. The technology detects a candidate’s body language, facial expression and other non-verbal cues that would combine to form the person’s personality. The algorithm can also predict how the candidate will behave in certain situations. This helps the hiring team to get an overall picture of the candidate and assess whether s/he is a good fit for the company and its culture.
Future of Emotion Recognition Technology
It’s not only the B2B and B2B companies that can benefit from using this technology. Here are other domains where it can be used:
Automotive industry: With the emotion detection technology, car drivers won’t have to worry about feeling sleepy and then inviting accidents because of this. With the advent of smart cars, automobile manufacturers are working to leverage facial analysis algorithms that can detect when the driver is getting drowsy, and then alert him to wake up and rest for some time.
The service can also be extended to switch on particular lights to alert other drivers to a drowsy driver on the road. Likewise, distracted drivers can also be detected to become alert on the road again.
Healthcare: In the healthcare domain, emotion detection can help doctors and the help desk ticketing system decide which patients to see first, and to detect signs prematurely when special attention or medicine would be needed.
As with any technology, though, privacy concerns loom. There is the question of using the facial data unethically to manipulate users into making certain decisions. Emotions are extremely powerful, and as the recognition technology improves, the brands who use it will know how to trigger customers the way they want. Increased regulations will be needed and an inborn sense of morality will also have to be kept in mind.
Thus, all in all, emotion detection technology is a huge game-changer, no matter the industry employed in. It is maturing in some industries whereas in others it is still in its nascent stage. The only challenge lies in refining it so as to achieve maximum accuracy and create ethically-driven positive outcomes for businesses and their involved customers.
