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Powering coaching opportunities with the Agent Impact Score

When it comes to the contact center, agent performance is always top-of-mind. The Agent Impact Score (AIS) enables organizations to unlock details on how the specific contributions agents make are tied to business outcomes, addressing many of the problems with traditional QA scorecard-approaches to performance management.

QA scorecards as they stand present limitations to CX and customer service leaders. Innovations in AI and machine learning can help identify specific agent behaviors that need coaching. Rather than checking off criteria such as whether or not an agent used a proper greeting, how many times they said the customer’s name, if they thanked the customer for their loyalty, or if they followed compliance scripts and other arbitrary items, AIS helps highlight agent behaviors that put customers at risk of churn and enables businesses to spotlight critical business transformation opportunities.

Powering agent coaching opportunities

A Fortune 1000 retailer is using AIS to power agent coaching opportunities. Before using AIS, the retailer would have QA managers or supervisors listen in to a small sample of calls and they relied on post-call surveys to highlight opportunities for CX improvement. When a post-call survey was returned with a negative response to the traditional question, “Did the agent fully resolve your issue”, the QA manager would listen to the recording of the call to try and determine the reason for the poor survey result and apply their traditional QA scorecard to the interaction. In one example, the retailer found that an agent showed a lack of empathy and that may have driven the poor showing.

Now, agents aren’t perfect. While this particular rep might show empathy to customers most of the time, the QA manager may have caught the one call where the agent fell short. As a result, the coaching opportunity was lost as the agent believes that this was a one-off, and his performance doesn’t really change. 

By using AIS, the QA manager can use an expanded dataset to color their perspective and provide context to the agent about the entire conversation and where they could improve. They can also see how this particular agent ranks in terms of their overall scores when compared to the entire team or teams of agents. Continuing the example, AIS highlighted that while this particular agent does indeed show empathy most of the time, they also confuse the customer with their language techniques, resulting in a lower AIS score and, importantly, higher customer frustration. 

When coached based on the context provided by AIS, the agent can understand that it is this combination of behaviors–empathy and confusion in this case–that was driving his poor scores. With this understanding, he can be more effectively coached to improve.

Boost agent performance across the spectrum

With AIS, the retailer can now nail down the combinations of factors that play into good and bad customer experiences. And, since AIS scores 100% of the interactions, they don’t have to rely on dwindling post-call survey results or listen to a limited sample size of recordings to flag areas for improvement. Any bad AIS scores are automatically surfaced for the manager so they can coach their agents on skills that will yield impactful and timely improvements. 

AIS also allows businesses to shine a light on exemplary behaviors and to provide objective assessments and reflections on what positive agent interactions look like. Managers can determine which of their reps are performing the best according to the customers. They can take these insights and teach other agents to replicate the behaviors that result in those outstanding customer interactions. 

AIS also helps average performers learn to spot missed opportunities. Sometimes, a customer indicates something that could have led to an upsell or a cross-sell but a lack of training leads the rep to miss out on delivering a pitch specific to that need. AIS can teach managers how to assist their reps on how and when to apply selective guidance or to dig a little deeper on an issue. Teaching these skills not only moves your average performers up the line, it also drives stronger commercial outcomes.

Never miss a chance to save

When it comes to poorly scored interactions that are likely to result in customer churn, encounters that previously flew under the radar will always come to light with AIS deployed. Managers and supervisors can proactively step in to try and prevent disloyalty by hearing the customers out or presenting save offers. These negative scores can be excellent teaching opportunities for all agents on what not to do, and how to ensure situations don’t escalate to that level in the future.

Learn more about using AIS for QA here. Discover the drivers of good and bad Agent Impact Scores here.

Stay tuned for the last post in our series on deploying AIS an an onboarding tool.

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