How analytics can push call centre agents towards "unconscious competence"by
The linkages between employee engagement levels and revenue growth are well established by studies and reports from companies that have committed resources to improving that engagement. Companies with poorly engaged employees see declines in revenue and customer satisfaction metrics.
Within customer service departments, the need for engagement is exceedingly high, as these staff are essentially the face of the company. For staff working in call centres and performing other customer care, it’s important for agents to develop the right skills so they can connect with customers with empathy and politeness.
Reaching a more engaged state requires service members to reach “unconscious competence”, a state of performance where functions are performed effectively without conscious thought. So the agent performs the optimal action or gives the best response essentially “on the fly” without needing to waste time reviewing their notes or searching for best practices.
The “unconscious” part of this performance stage does not mean the staff person is not concentrating on the task at hand. They are, it’s just their training and practice have allowed them to present a trusted and competent persona, one that understands the business’ products and the customer’s point of view.
This is the fourth stage in the employee’s journey, which follows the progression through the “unconscious incompetence” stage where a worker does not know the skills they are lacking, “conscious incompetence” where they at least understand they have things to work on, and then “conscious competence”, a state that allows the worker to perform, but only at a moderately efficient level of concentration.
Source: Jake Poinier
Moving staff members into the fourth stage should be a goal of every customer service centre manager. Agents only reach this stage if they’re invested in the work, the company, and truly want to help the customers. Moving agents towards this stage requires several technology-based practices.
Utilising in-depth speech analytics
Agents in a call centre can only improve their skills if they understand their shortcomings. Perhaps they’re not empathetic enough with customers, or they lack knowledge of the proper regulatory language specific to their industry. Whatever the case, the agents must receive accurate and consistent feedback.
In a call centre, agent performance reviews are typically conducted by looking at metrics such as sales or hold times, and then listening to a sampling of calls. However, it’s only realistic for a firm to review 1% (or less) of an agent’s calls. This reality means there’s an enormous gap between what the sampling says about performance compared to the actual.
An elegant solution to this problem is to leverage analytics platforms that monitor and transcribe 100% of call, chat, and email conversations and turn them into searchable text. Call centre managers and their agents can then have insights into actual performance, so they can adjust their training to reach the goal of unconscious competence.
Armed with actual data, agents can see for example that they do not use enough language that evokes empathy.
Armed with actual data, agents can see for example that they fall out of compliance language guidelines 10% of the time, or they do not use enough language that evokes empathy. When agents are given this information, the top performers (those with the potential to reach the fourth stage) will see it as a golden opportunity for improvement. They’ll start to self-correct their behaviours during calls because they have the context from speech analytics. And these actions will start to become second nature, as the analytics consistently points them towards areas that need improvement, so there’s repetition in their positive actions.
Leveraging speech analytics can push new hires through the performance stages quickly. Instead of a resigning themselves to high new hire attrition rates, managers can instead use speech analytics to locate the new agents that show the most promise. And it can identify those that are not a good fit with the organisation or that specific department.
With drilled-down analytics, the managers can spot agents that are very good at compliance language and spot those that are most adept at talking customers through difficult situations. The agents’ roles can then be dynamically shifted to best suit their strengths, which drives their own engagement with the work and ultimately improves customer satisfaction.
Using context to transform coaching and performance
In the typical call centre setting, agents have a strong case for disagreeing with performance assessments, because the managers randomly sample a few calls, and then extrapolate their rating based on that data. Perhaps they caught the agent on one day where they had a string of disgruntled and unreasonable customers. Or the agent just simply had one bad day out of 100. In either case, it paints an unreliable picture of the agent’s prowess and could result in quality performers being let go and poor performers undeservedly rewarded.
Agents that feel their performance assessments were inaccurate or unjust will quickly lose any engagement with their role and the broader company. Without motivation to perform at a high level, they’ll negatively impact the customers and ultimately revenue. If instead they understand their assessments are informed by clean and reliable data, then they do not have a case.
Performance assessments can be improved through coaching, and when that coaching is informed by 100% call monitoring, categorising, tagging and scoring, it’s much more effective. Managers can use call transcript reports to both spot negative behaviors (non-approved language, long conversation pauses, etc.) and to reinforce positive behaviours such as empathy-based language. Since the call transcripts are accurate, managers can tie call metrics to incentives and raises, to show the agents that performance is rewarded. Such a dynamic improves agent retention and their engagement with the company.
Using context-based speech analytics as a coaching and learning tool can lead agents to the elusive fourth performance stage of unconscious competence. Feedback that is informed by 100% accurate data is equitable for all agents and provides them with clear markers for improvement. Agents that feel they are treated fairly are more engaged with their employer and their job, which allows them to offer the very best service to the end customer.