For many contact center employees, answering an incoming call can be like playing the lottery. When they answer the phone, it’s difficult to quickly assess what issue the customer encountered before he called. And, more importantly, it’s difficult to know how the previous conversations went. Is this a customer who’s generally happy with previous interactions or is it someone who regularly calls to get frustrations off of their chest? Knowing this in advance might allow the employee to brace for the interaction and be prepared to provide better service.
With upcoming advances in artificial intelligence (AI)-based sentiment and emotion analysis, along with the ability to surface information from a knowledge base, you give contact center employees the ability to quickly assess the temperament of a customer and adjust their approach accordingly. And these capabilities can turn your teams into empathetic superheroes for your customers.
When designing an effective AI assistant, start by thinking about how effective human coaches can guide employees during conversations. It’s also important to know what not to do. An ineffective coach will try to talk while the employee is listening to the customer — or send them paragraphs of text through an instant messenger that they need to read through in real time. Less-effective coaches might barge in unannounced and take over the conversation, much to the surprise of both the contact center employee and the customer.
Effective coaches possess the following qualities:
- Make the contact center employee forget that a coach is listening
- Provide most insight and guidance for improvement after the call has occurred
- Condense any real-time information to a handful of words that serve as non-intrusive reminders for the employee
- Send links or references to helpful information at the right moment
- Wait for the right time in the conversation to chime in, such as when there’s a long pause or the customer is looking up information
For newer contact center employees, AI-based coaches let them reflect on their performance. For instance, they might point out times when an agent interrupted the customer. If over-talk is detected, it can signal that there has been a disconnect between the two. Likewise, long pauses between when the customer has finished speaking and when the employee has responded might signal that the employee has lost her train of thought. In these scenarios, alerts could refocus the contact center teams or slow down speaking cadence.
You can also design effective AI-assistant systems based on an employee’s preferences. Some might want a constant stream of analysis and feedback in real time. Others might prefer to review items after the interaction — and then glean lessons they can use for the next conversation or as lists of items they need for follow up with the customer. Allowing contact center employees to weigh in on how they receive feedback can empower them and improve work satisfaction.
AI-based analysis of calls can give teams more granular insight into how previous conversations have gone. These tools can determine if the customer was more positive toward the end of the previous calls or if they generally couldn’t be appeased. They also could detect if they become consistently frustrated throughout their calls. Seeing this analysis, at a glance, might help experienced employees hone-in on past interactions that are more critical to understanding where issues have occurred. Overall, this helps them better serve customers — and that leads to happier customers.
Creating an AI-based assistant to empower your contact center employees is a delicate balance. Ultimately, the humans set the direction while AI technology acts as the horsepower. This might mean disappearing altogether when not needed or — being more present only for novice employees. But the end result is the same — contact center teams who appear more relatable, confident and helpful to customers.