Customer service starts when the customer experience breaks down. If brands can perfect the customer experience (CX) they deliver, then the demand for customer service should go down as a result. And the best leaders realize that every interaction a consumer has with their brand will form an emotional impression. Is it a positive, neutral, or negative one? Will they be buying from you again or cursing your name on Twitter?
The importance of CX is quite obvious. People will remember how a company makes them feel long after the interaction is over. Emotions are typically running high in customer service interactions from the get-go, as most people only reach out once their issue clearly becomes unsolvable via self-service methods. Understanding, tracking, and evaluating the emotions of your customers can be an amazing way to improve the service being delivered. This is why contact centers should be leveraging emotion detection technology.
Emotion detection measures a person’s verbal and nonverbal communication to understand their mood, feelings, or attitude. If a contact center’s tech platform has this feature, they can uncover whether a customer was satisfied with a company or its agents, loved or hated a product, and even identify repeat problems that need to be addressed such as a product defect or supply chain issue. Emotion detection is key to learning from your mistakes…to turning every interaction into a learning experience for your brand.
Emotion Detection Directs Customer Care
Our contact center solution - Edify Huddle CX - is powered by machine learning (ML) to leverage both Natural Language Understanding (NLU) and sentiment analysis, which is basically just another way to recognize and categorize emotion detection. These features enable bots to understand human language, both spoken and written, to gather information about customers’ emotions automatically. This allows for a deep dive into previously analyzed data with a simple query. For example, a salesperson might ask a customer whether or not s/he was happy with their trip after returning from a vacation. This question is asked during the interaction, answered, and then the sentiment can be drawn with a high level of precision by the NLU/sentiment engine in milliseconds.
Here’s another example: If a customer begins a webchat and says, “I’m frustrated that I can’t log into my account,” the ML-powered bot can serve up FAQs regarding accessing their account. It will also detect a tone that signals displeasure and the word “frustrated” itself. Edify's bots identify intent and suggest response options so agents can act quickly and work to mitigate any negative emotions the customer is feeling at the start of the interaction. So if the chat is then escalated to a live agent, that person will be better able to engage in a productive dialogue going in knowing how the customer feels.
With the ability to detect the emotions of customers on all channels, Huddle CX engages in emotion-based call routing. Imagine incoming calls with negative sentiments being directly routed to your most expert call handlers. Whether the customer was angry the minute they were greeted by an automated prompt or a call escalated quickly while being serviced by a live agent, our ML knows when - and where - to reroute someone. ML-driven solutions use deep learning and sentiment analysis to help improve interactions with customers over time as it continually learns from human language and behavior.
All of the customer data collected goes into a single source for easy reporting, too, transforming your business into an effective customer-centric company.
Empathy Can Be Mastered by Live Agents
An article by CustomerThink titled Will Emotion Detection Change Customer Experience Forever? advises:
Real-time insights into customers’ emotions can help agents engage with them in a highly personalized manner and deliver empathetic service, a vital quality in today’s customer-centric business environment. For example, agents providing instructions for setting up a smart TV can see confusion registering on a customer’s face, enabling them to repeat or simplify the steps.
Voice analytics may help an agent detect high levels of frustration and provide personalized service that addresses the customer’s specific issue. When there’s a language barrier or a noisy environment, a voice-to-text app will enable agents to benefit from sentiment analysis, providing insights into a customer’s mood when speech or facial analysis is not possible.
Emotions drive behavior, brand loyalty, and, consequently, customers’ likelihood of churning. Brands that do the best at monitoring customer sentiment through emotion detection will be the ones who win the customer experience war. So agents must recognize and respond accordingly to various sentiments, guided by the technology discussed above, as it has become quite easy for companies to tune into their customers’ feelings and analyze what makes them tick.
Combine the power of advanced bots with the empathy only real people can provide and you have a recipe for customer satisfaction.
Leslie O’Flahavan put together a list of 20 empathy statements to show customers that you care. Share this with your frontline customer service agents and embark on some old-fashioned coaching and training to better deliver the level of empathy your customers want and deserve. As Leslie writes, “[Customers] need our empathy. They need us to infuse our emails, chats, and social media responses with words that demonstrate we understand what they are feeling, we see things from their point of view, and we care…While sincere empathy comes from the heart, practical expressions of empathy in customer service situations can come right from this article.”
Put Your Technology And Your People to Work Caring for Customers
Emotion detection and genuine empathy are a CX secret weapon for businesses. Find a technology partner with built-in ML, NLU, sentiment analysis, speech analysis, and more. And train your agents with practical statements and ways to demonstrate empathy to your customers. Together, the combination of caring people and smart technology will drive better experiences, increase agent productivity, reduce operational costs, solve issues more quickly, and - most importantly - make your customers feel truly cared for.