Using Interaction Analytics to Push Agents to the Top Performance Stage
Both new and tenured supervisors and managers are eager to transform their staff into efficient workers who understand the business and how to drive revenue. To reach these lofty goals, these managers should understand how workers fit into the four “performance stages.” And they need to understand the tactics they can use to push staff towards the final most productive stage known as “unconscious competence.” This is the ideal state for any worker, and it’s especially valuable for front-end customer service staff who must work quickly and intelligently to help the customers. For managers within the typical customer service/call center environment, it’s especially important to cultivate high-performing agents. These staff are the linchpins of a quality customer experience, and directly impact the company’s success.
Understanding the Four Performance Stages
The baseline of the four performance stages is known as “unconscious incompetence” where the worker is unaware of their shortcomings. New workers are unsure of their role and expectations coming in, but new agent onboarding should quickly move them to the next stage. Agents move into “conscious incompetence” where the person understands the role but recognizes they are in need of skills improvement. The third stage is “conscious competence,” a state where the worker performs well but is lacking the “second nature” aspect – their actions require a considerable amount of time and thought.
The fourth stage of “unconscious competence” means the worker performs their duties very well and does so without too much conscious thought. This of course does not mean they are not “thinking,” it simply means through training and effort they’ve developed the talents to perform things by second nature. So they know the right words to say on a customer call or how to route a complex inquiry to the right person. Call center agents within this stage use the right tone and phrasing, and will also have a deep understanding of the company’s products and any applicable regulatory or compliance language.
Using Analytics to Progress through the Stages
Consider the average call center supervisor and their ability to access information about agent performance. They might listen in to a few calls a month and then try to extrapolate their opinions about the call to judge the agent’s overall skill. It’s an antiquated and unreliable approach that only captures a fraction of the agent’s calls and does not likely reflect their true capabilities.
Thankfully, new interaction analytics platforms are available that can monitor, transcribe, categorize and score 100% of call data, as well as chat transcripts, email content, and other sources. Armed with this data, supervisors can jump right into reviewing individual agent performance. They can also immediately see problems with overall processes and gain insights into common customer pain points. These platforms can identify phrases, so a supervisor has data on which agents are using empathy-focused language, or which ones are sticking to regulatory language scripts.
Managers can then leverage this near real-time data to provide continuous coaching to the whole team and individual staff, helping them to correct issues that will help them reach the final performance stage. They can also identify positive behaviors and use them as coaching examples to further accelerate the agents’ growth and talents. Call centers typically employ a 60-day training period for new hires, during which time managers will scramble together some rudimentary metrics and observations about the agent’s progress. With interaction analytics, supervisors can see which agents are suited for the role, and which ones should likely be let go before the training period ends. Such moves can cut down on attrition, as the crop of agents that stays with the company are simply better fits for the role, which improves their engagement with the company and their interactions with the end customer.
As a boss responsible for the development of your team, you should embrace your role as a coach, not a disciplinarian. Within a call center, quality coaching is imperative for motivating agents through the performance stages. In the traditional approach to reviewing performance within customer service, managers had very little reliable data to work with, especially in regards to the agent’s tone and specific knowledge. This led to unhappy agents who felt (often justifiably) that their assessments were inaccurate and unfair.
Agents who are consistently upset with management’s ability to conduct assessments will not progress through the performance stages. They’ll either sit stagnant in their role or look elsewhere for employment. To prevent either scenario, managers should embrace context-based coaching that is backed by analytics. Advanced monitoring tools can track a myriad of phrases or speech patterns, including those that indicate stress or impatience from the agent or customer. They can track empathetic language usage, which gauges if the agent is truly listening to the customer’s grievance and how engaged they are in finding a solution.
With this level of feedback, managers can provide personalized coaching that’s based entirely on actual call data. It’s an entirely new level of context that gives supervisors the chance to demonstrate how the agent performed in the past and guidance on future actions. Constant and positive coaching that is backed by data means bad agent behaviors are corrected, and positive actions are reinforced –which is the path towards unconscious competence. And nothing is missed because the analytics platform captures 100 percent of all interactions, so the coaching can reflect every facet of the agent’s job.
Used in tandem, interaction analytics and context-based coaching gives both new and experienced managers the opportunity to lead their team with confidence. They can turn efficiency-killing agent actions into “second nature” tasks that improve customer satisfaction and ultimately revenues.