Customer Service Teams and Mental Wellbeing: The Role of AI-Driven Call Recording and Speech Analytics

Customer service teams

Simon Peters, Managing Director at CallCabinet UK

In recent times, employee wellbeing has been on the top of the agenda for both employees and employers, and the pandemic has brought it even further into the spotlight. As reported by the World Health Organization (WHO), poor health reduces national GDP by 15%, almost twice the 8% hit to GDP that the pandemic itself has had. Therefore, it’s unsurprising that improving mental health has become a key focus for senior leaders.

While various schemes to tackle burnout and stress are commonplace at many businesses, they still continue to play a prevalent role in the working environment. For example, recent research revealed that 58% of employees have experienced some sort of stress at work, while 69% experience moderate to high levels of stress in general. These struggles are undoubtedly prominent among those working in customer service.

The pandemic has pushed companies to adopt a more customer-centric approach and customer service agents are under more scrutiny than ever before. Agents’ jobs require constant speed and attention to detail, with their every move closely watched by both customers and supervisors. In fact, more than 65% of people have higher expectations for customer service today than they did three to five years ago, which has led to increased stress for many agents. So, what can customer service teams do to help staff cope with this added pressure?

Implementing the right tools in customer service teams is one way, particularly by adopting AI-driven recording and speech analytics. Doing this means companies can not only expect to deliver a better customer experience, but along with it happier, more efficient, and more loyal staff.

 

Utilising AI-driven speech analytics

Through AI-driven speech analytics, businesses gain the ability to rapidly understand and process keywords, phrases, and terms. Advanced acoustic algorithms can now even measure and evaluate voice pace, volume, pitch, tonality, and other factors to determine emotions behind words, accurately capturing the sentiment of each interaction, which can then be used for training. The same sentiment analysis tools that can monitor performance of customer service agents and help supervisors train employees can also work to spot patterns that might signify mental health concerns. These include repeated negative customer interactions, frequent silences, raised voices, and profanity directed at the staff member.

Capturing both sides of a conversation using voice recognition software used to be difficult, but technology has moved on, and is now capable of separating the caller’s voice from the agent’s, enabling more granular analysis and allowing the true potential of AI to come to the fore. By layering screen and video capture into the mix, the organisation can also harness this data to build a complete and accurate profile of interactions between different audiences.

 

Further enhancing the experience with cloud

Using cloud-based call recording for speech and voice analytics means that all calls can be recorded in real time, with custom dashboards to spot these occurrences either for one-off calls – that are flagged to supervisors so they can offer quick support to a staff member – or for longer-term trends that indicate a deeper intervention might be needed.

While recordings of negative interactions can be used to improve performance, it’s vital for businesses to also look at positive interactions, to single out employees for praise and to promote best practice.

 

Happy employees means happy customers

All businesses should focus on applying the right mix of culture and processes first and foremost to support employee wellbeing. However, effective use of technology will make clear the indisputable business and personal benefits that agent wellbeing delivers. It is important for business leaders to keep in mind that employees are the face of the business, especially ones that work in customer-facing roles. It all boils down to this: if employees are happy, this will reflect on the service they provide to customers.