What is Emotions Analytics (EA) & How AI is Improving Customer Experience
As designers of advanced customer experience programmes for national and international clients, it’s inevitable that talk often turns to innovation and new technology.
As we’ve all seen, Artificial Intelligence (AI) has the potential to improve almost every aspect of our lives. Few could have predicted the impact that AI would have on customer service. But in recent years, we’ve seen sophisticated systems capable of delivering a high quality experience service that leaves customers feeling valued and delighted.
Chatbots and self-service systems are means of delivering a faster and more convenient customer service experience through automating certain basic processes. However, it doesn’t always follow that a customer’s experience is more positive for it.
But beyond this, sophisticated AI systems have begun to make it possible for businesses to connect with their customers like never before. Rather than making the customer experience cold and impersonal, often an issue cited with chatbots and older technology, more recently AI has been designed to make customer interactions warmer, and more human.
We’re going to explore how this change is taking place and what it might mean for businesses and customer experience.
First up, how are AI systems able to appear more human. Emotions Analytics is key here.
What is Emotions Analytics?
Google describes emotions analytics (EA) as “a powerful tool to augment gut instinct.” In short, it’s a means of measuring people’s emotional reactions to certain things: whether it’s an advertising campaign, a piece of music, or a customer experience. EA gives businesses insights into what customers are feeling, and why.
There are many levels to communication. In the customer experience world, a lot of the time all we have to work with are words. But words don’t tell the whole story. What emotions really lie beyond that one-line, one-star customer review? What sort of feelings are intertwined with the facts? What’s the wider context of this customer’s unhappiness?
Can EA Improve Customer Experience?
Let’s take a look at just some of the ways businesses have used EA to improve their customer experience.
Using EA to Build Trust
Imagine you’re having an argument with a close friend, or a family member. They’re upset with you because of something you said. As far as you’re concerned, what you said was perfectly inoffensive. But they tell you: it’s not what you said, it’s the way you said it.
This sort of disconnect between what someone says and what someone means can be a challenge for businesses. But with EA, businesses can track the emotions underlying text and voice communications to get a measure of how people really feel.
Many companies are looking at how they can use this technology to protect their customers and build trust in their brand. A new driving app, Drive Safely by FRUCT is using facial recognition to spot signs of drowsiness or distraction in drivers. Some transport and logistics as well as private driving companies have begun to employ similar technologies.
Using EA to Address Pain Points
One area where EA has the potential to truly make waves in the world of retail. Retailers can get a very good impression of how their customers are feeling just by looking at them and listening to them. But again, these clues don’t tell the whole story. So, to get a deeper understanding of how their customers really feel, some retail businesses have turned to EA.
In 2016, eBay launched a pop-up store. Using biometric wearable devices, they found that 88% of their customers experienced a higher heart rate while shopping. What does this suggest? It might suggest that shoppers are excited by their shopping experience. But more likely, it means that most of their shoppers are stressed.
As an emotion, stress is often invisible. A person can have all the appearance of being calm and in control. But underneath it all, they could be struggling with stress and anxiety. If businesses are able to draw from EA, they might be able to identify what aspects of their customer experience are leaving their customers feeling stressed. Then they can make improvements. It could be something as simple as changing the colour of the carpets. But the point is, if they know how their customers really feel, they can address their pain points like never before.
Using EA to Create an Optimised Experience
Facial Recognition Systems (FRS) has been widely used in the security industry for some time now. Border forces and police forces use FRS to match people caught on camera with a central database of identities. This can help them catch criminals, but it can also help in the search for missing people.
As FRS got more advanced, it became capable of reading emotions. They’re now capable of registering micro-expressions – which essentially means that they can tell how a person’s feeling potentially before the person’s even registered their emotion.
These innovations may soon make it to the world of retail. Retailers may soon be able to map customer journeys through their store in real-time. They’ll be able to analyse the routes customers took through their stores, the products they looked at, and the products they ignored. And crucially, they’ll be able to tell how customers felt at every step of the way – all through reading their facial expressions.
With all the data this system will generate, it will be possible for retailers to fine-tune their stores to deliver a positive experience for every customer, from the moment they step through the doors to the moment they leave.
On top of this, if retailers have a full picture of what’s happening in the store at any given point, they can respond to staffing levels as and when they’re needed. They’ll be able to spot potential customer service issues before they become problems. They can send more staff to busy areas to help relieve long queues. All the old headaches of the shopping experience could become a thing of the past.
Even the sport and entertainment industry have been using emotions analytics to optimise viewer experience. Formula 1, for example, used biometric surveys to better understand the experiences of views watching the sport.
What Does this Mean for Business?
Emotions analytics certainly isn’t going away. But it’s not something to rush into either. While it can allow us to delve a little deeper and, in some cases, allow us to get a bit more honesty from customers, it’s essential that emotions analytics is used as part of a wider customer experience programme. To improve customer experiences we need the whole story – what are customer expectations and how does that match the reality? To really understand and listen to your customers, we can’t forget the importance of them telling us how they feel.
A customer-centric culture is key to delivering the types of experiences which not only meet your customers expectations, but exceed them.