Solving the Problems of Quality Assurance

Charlie Mitchell

Motivate agents, pinpoint CX issues, and ensure compliance by reimagining contact centre QA

Strategy
Solving the Problems of Quality Assurance

First, there was The Great Resignation. Then, The Great Exhaustion. Don’t discount these as one-off trends. Instead, they are largely the results of a weary workforce.  

Recognizing this, 92 percent of employers have made enhancing employee experiences an “important priority” for their organisations over the next three years.  

What will this involve? For contact centres, dusting off the quality assurance (QA) playbook and bolstering performance management is perhaps the most pressing course of action. 

When Auto-QA Wasn’t an Option

QA programmes positively influence agent behaviours, pinpoint customer experience issues, and ensure compliance when implemented well. 

Yet, over the years, many contact centres let their programmes fall flat, and this immense opportunity became – in many cases – a box-ticking exercise.  

To hit their targets, analysts had to score five or six contacts per agent every month. So, what did they do? They picked contacts with low handling times, disregarding the meatier issues, which make or break the customer experience. 

As such, agents rarely received meaningful performance insights that inspired behaviour changes.  

Moreover, they could not ignore one simple truth: the system is unfair. Analysts judged their performance on such a small sample; it could not possibly offer a true reflection of the work efforts. 

As a result, these potluck performance reviews demotivated agents, supervisors overlooked their value, and many regarded the entire exercise as a drain on time.   

Thankfully, automation tools are changing that narrative, pulling insights from every contact centre interaction and attaching metadata for deeper analysis. 

Such a solution is powerful. Yet, remember, it is not a magic wand. Operations must build a better strategy around Auto-QA to extract full value.   

Get Everyone Pulling In the Same Direction

Businesses that draw the most value from QA consider it a team sport. 

Joined at the hip, their coaches and analysts develop shared performance standards, isolate and close performance gaps, and run post-training reinforcement.  

Only with this shared philosophy can businesses create a connected learning strategy that draws the most value out of a modern QA system. 

Such technology not only automates call listening but flags conversations, filters contacts, and spotlights performance trends. Each capability drives significant value when used as part of a connected strategy. 

As Jaime Scott, Founder & CEO of EvaluAgent, adds:  

“With everyone pulling in the same direction, the contact centre can become more methodical in how it identifies performance improvement opportunities, applies appropriate training, and follows-up to measure the impact.”

In developing such connected workflows and fully involving agents in the process, operations may ensure agents receive personalized performance insight, relevant coaching, and a clear-cut view of how their performance is improving.   

With such an approach, the contact center lays the foundations for success. Yet, one problem persists: spotting the most significant agent improvement opportunities.  

Here is where Auto-QA enters the fray. 

Let’s Focus Our Efforts In the Best Places

QA automation tools – integrated into other contact centre systems – evaluate every customer conversation against particular criteria and attach metadata to it.  

Such metadata allows contact centres to categorise each interaction by call queue or workgroup. 

With this information, analysts can prioritize high-risk conversations – focusing on the cancellation queue, as an example – for evaluation.  

Another way to inspect high-risk scenarios is to look back through interactions that resulted in particular survey results.  

Also, contact centres can target contacts that failed the Auto-QA processes for manual evaluation.  

According to Scott, each example demonstrates how: 

“These tools laser focus the QA team to concentrate human interventions – such as manual QA, coaching, and feedback – where it will have the biggest impact on business performance.”

Yet, the next generation of Auto-QA goes further. Harnessing conversational analytics, the system may lift conversations that include particular keywords for manual review. 

Combining all these sources allows businesses to dig into particular aspects of contact centre operations, gain new insight, and continually improve. 

Driving Change With Auto-QA

Engaging reports are a significant driver for change. Yet, even more so, operations must develop the proper workflows that connect results to actions. 

Without this connection, Auto-QA will churn out lots of data that goes amiss.  

As such, coaches and analysts must use the technology to develop people-focused workflows. These take Auto-QA results and metadata to inform conversation selections for manual reviews. 

From these, analysts can spot improvement opportunities, give feedback, and recommend coaching or e-learning modules. 

After, analysts may track the results of that coaching, praising any improvement while testing the impact of the type of training applied.  

Such a workflow can transform contact centre performance. Yet, remember, there is more to QA than fixating on improvement opportunities.  

With a view of all agent interactions, supervisors can create workflows to look for exceptional customer conversations, repeated high scores, and significant performance gains. 

Leaders may then recognize these achievements, praise agents publicly, and refuel agent enthusiasm to do their best for customers.  

Coupling this positive reinforcement with chances for development will maximize the potential of QA and keep agents engaged. 

To learn more about Auto-QA systems, visit: www.evaluagent.com

 

 


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