Can AI aid contact centres with whisper coaching?
What is "whisper coaching" and can AI help deliver it to contact centre agents on calls?
The phone is often the medium that matters in moments of truth, whether it’s a service call or an inside sales call making the first contact. To the customer, the ideal interaction often feels like a conversation – just the customer and the company representative, talking through the issues together, person to person.
But well-equipped contact center managers know that those conversations may not be as one-on-one as the customers think – and for a very good reason.
That reason is not nefarious – it’s helpful to both parties involved in the call. “Whisper coaching” enables managers to listen in on agents’ calls, and when it’s appropriate, they can share advice with the agents, coaching them in real time. This advice is audible only to the agent and can help bring calls to more successful conclusions. In the process, the agent receives practical training that can help with future calls.
But there’s one major limitation to whisper coaching: you need people to do the whispering. In a contact center with multiple agents, managers can only listen in on so many calls. Calls that could benefit from the expertise of a manager may miss out because the manager is listening to the wrong call at the key time – meaning that both the caller and the agent miss out on an opportunity for a more optimal experience.
When managers use whisper coaching, they’re mentally matching situations that may arise in the call with the right responses and tactics, based on their experiences. Their own trial-and-error efforts throughout their careers enable them to recognize these circumstances and can quickly suggest the right ways to deal with them.
“Whisper coaching” enables managers to listen in on agents’ calls, and when it’s appropriate, they can share advice with the agents, coaching them in real time.
This represents yet another promising opportunity to use artificial intelligence (AI) in the sales process not to displace people but to augment their expertise. AI is great at doing the basics of what whisper coaching managers are doing today – identifying patterns and suggesting the right responses to them. But there’s a difference: Every agent can have an AI coach whispering in their ears – or popping up useful data on their screens – during a call.
The other benefit of using AI for whisper coaching is that, by being present on every call, it can collect data much more quickly than a manager. While a manager learns over time and through individual calls, AI can learn from all the calls, allowing it to develop conclusions and make suggestions much faster than a human. This, in turn, can help managers learn faster – in other words, AI-enabled whisper coaching can coach the coaches as well.
It can also provide data that forms the basis for ongoing training for agents. Calls will be recorded and their key points identified through analytics (and tools like NewVoiceMedia’s Conversation Analyzer) and then fed to AI, allowing managers to spot areas for improvement, common stumbling blocks, and questions that often result in less-than-satisfactory answers. Agents can hone their abilities and onboarding can be made more valuable and on-target.
The challenge for managers is to evaluate the conclusions that AI reaches. There may be occasions when the AI gets it wrong, because corner cases could give it inappropriate data to learn from. More often, however, it’ll be a matter of nuance: the AI may be on the right path, but it still needs the experience of a manager to adjust its suggestions so they align with the business’s objectives.
Again, it’s a major mistake to think of AI as something that will replace people – think of it as a tool that will allow people to work at a level beyond their current capacity, but which will still depend on humans to provide a reality check. Coaching is still a very human activity, and managers will need to commit themselves to ensuring the suggestions generated by AI are as human as possible.