5 components of emotional intelligence in a human-AI customer service
Emotional intelligence is an essential skill in the customer service functions with the productivity and efficiency of the role is directly tied to the quality of conversations. The personal dynamics of emotionally cognisant customer service agents play an important role in empathetically resolving any queries or concerns, impacting customer churn and increasing brand loyalty by leaving customers with a positive impression of an organisation.
However, rapid adoption of automation technology within customer-facing roles presents new challenges to organisations that want to harness its benefits, without impacting the service that it delivers to its customers.
A hybrid workforce
Already helping many companies increase customer service availability, reduce wait times and improve resolution rates, Gartner has predicted that a quarter of all customer service operations will use artificial intelligence (AI)-powered virtual assistants by 2020. In many organisations, this has resulted in the creation of a hybrid workforce of human and digital agents.
While some organisations are still using basic chatbots, businesses that prioritise giving high quality customer service are opting for more sophisticated digital colleagues, that can respond to more complex and nuanced requests. In addition to handling simple customer queries directly, they can also act as a whisper agent to human customer service representatives to help them provide faster and more accurate responses. For instance, at insurance firm Allstate, virtual colleague Amelia has collaborated with live agents on more than three million calls. Employees are able to access her knowledge to augment their own.
A common view of emotional intelligence
However, as digital colleagues play a greater role in customer-facing workplaces, a key challenge for businesses is to ensure that both human and digital agents are delivering the same emotionally cognisant service. While the leading digital colleagues can understand and react to customers’ emotional state, how can this be productively combined with human experience and intelligence to deliver a truly superior and consistent service?
To establish a common view between digital and human colleagues on emotional intelligence, we should consider how the symbiotic relationship can support the five components of emotional intelligence, as outlined by psychologist Daniel Goleman.
Self-awareness, self-regulation, motivation, empathy and social skills: these five original components of Goleman’s theory help us create a blueprint for emotional intelligence within the hybrid workforce. While human and digital agents don’t all excel in the same areas, it does show us the opportunity for augmenting human experience and expertise with AI, without losing the “human touch”.
So, how do the five components apply to hybrid customer services?
Self-awareness and self-regulation
When dealing with customers, it’s important to be aware of your own emotional state and how it will impact your actions. This is tough for human agents – especially when dealing with particularly frustrating or aggressive customers.
Working in symbiosis, digital colleagues can assist human agents in these situations by acting as a whisper agent. The intelligent system records and analyses the reactions to all responses previously given by customer service agents, enabling it to consider the emotional aspect of the dialogue when suggesting what the best response is for that customer in the given situation.
For instance, when working on a cancellation line, where the majority of interactions are negative, it can be tough for human agents to keep their cool. However, you’re less likely to get an emotional outburst from AI, because rules dictate how they act when seeing certain behaviour or emotions. This doesn’t make digital colleagues alone the best agent to deal with cancellations, as there is no opportunity for reconciliation and already-frustrated customers may feel fobbed off. However, they can provide the human agents the responses that best serve the customers’ emotional state, while helping them self-regulate their response.
As times have changed, the motivation for customer service roles has shifted from merely churning through calls as quickly as possible, to increasing the value of interactions and making sure that each has a positive outcome. While this is a welcome shift for customers, being engaging and personable for hours on end can be exhausting for customer service representatives, leading to lapses in concentration and less than ideal outcomes for customers.
A digital colleague is also focused on achieving the outcome and a positive emotional state for the customer when directly handling interactions, but, given its digital nature, doesn’t care if it spends five minutes or five hours handling one query and can scale to any number of conversations.
Even when working as a whisper agent, the digital colleague helps balance both the organisation’s need for a high amount of resolved queries and deliver a better service and outcome, as it is able to provide the agent with the best response and most relevant information in real time. This helps the agent provide that superior service at the high rate of resolution often welcomed in customer service roles.
Having a customer service agent empathise with our issue and show dedication to resolving it is a key component of delivering emotionally cognisant engagements. Empathy is a key life skill for humans, however, it has been much harder for digital agents to authentically be empathetic, show listening skills and understanding.
Even when tracking and responding to a person’s emotional state, digital agents could still sound cold and robotic when using empathetic language. So, digital colleagues need an additional aspect of self-awareness, which recognises conversations that require empathy and sympathy, so they can pass them on to a human agent.
That said, in their role as whisper agent, digital colleagues can help human customer service representatives build better relationships. Using their analysis of the emotional state and previous interactions, they can advise agents on how to best engage with any customer.