13 Mar Customer Service Agent Scoring and Actionable Data
“Too much information, running through my brain…” The Police have it right. We’re drowning in the amount of info available to us. However, what use is data that isn’t sifted or that comes too late? In customer service it means loss of clients and thereby loss of revenue. Customer service agent scoring and actionable data is valuable when targeted. It is finding the sweet spot of just the right information at the right time that improves KPIs.
How Much is Too Much?
Customer Service agent scoring information isn’t like points – quantity isn’t the goal.
Warning! Customer service agent overload imminent:
“Imagine you’re a customer service representative. Every morning, your manager shares your numbers with you: a printout of 30 separate metrics evaluating your performance during yesterday’s shift. How long would it take you to look them over? How long to internalize them? Now, imagine that many of those metrics have to do with productivity, such as closing more cases in less time. You would likely feel overwhelmed.”
Also, the type and development of an organization influences the manner of scoring. Not every business benefits from a 100 point scale. Sometimes the simpler approach is more effective.
Furthermore, it is the relationship between business and customer, and by extension agent and customer, that promotes profit:
“Look at satisfaction scores for support interactions. Use your metrics to measure both the quantitative and qualitative aspects of delivering customer service, but always stay focused on improving your customer relationships.”
Self-Monitoring for Agent Scoring
There are varying opinions on self-monitoring for agents, but it may not be that it is good or bad, but rather how it is applied that matters. The “Big Brother” style monitoring of agents can come off as oppressive and add to an already challenging job of handling customer complaints. With self-monitoring there is an empowering vibe that is encouraging:
“Too many times, call center agent scoring—as part of the center’s QA initiative—can be perceived as negative and judgmental and can deteriorate the team’s morale. If agents are given the opportunity to self-score, it will open up a world of proactive behavior that will have positive ripple effects for the entire call center.”
Agents are still a vital part of the customer service experience. Empowering them to handle the important interactions that go beyond what a machine can manage effectively is investing in customer care. From McKinsey:
“… more than 60 percent of customer-care leaders we surveyed are skeptical about eliminating inbound voice calls in the next ten years. Call abatement is likely to be more successful through a dual track that leverages the best of technology while improving performance on human-based interactions that remain in the call center. Some of these calls are just too critical. They wield great influence over customer satisfaction and often over the purchase of goods and services.”
Real Time Data
CSAT surveys are prevalent and often happen post-interaction:
“In the world of customer support, CSAT surveys are commonly asked after a support conversation is completed, as a ‘rating’ mechanism. This is an example where interaction-based CSAT surveys work well: customers are asked their explicit level of satisfaction with their support experience.”
Though useful, this satisfaction level is gauged after the interaction is completed.
What if an interaction was scored in real time?
With proactive scoring an agent sees how well (or not) an interaction is proceeding. In addition, if the agent is given actionable data they have the opportunity to improve the interaction before it concludes.
This is possible with CSAT.AI.
CSAT.AI bridges the juncture of AI power and human nuance to provide an elevated level of customer experience.