Remember the episode of Friends when Chandler sits on Joey’s recliner, it falls apart, and he immediately assumes he has broken it?
During the episode - “The One Where Rosita Dies” - Chandler panics and rushes to replace Joey’s chair with his own.
However, Chandler fails to consider that the chair was already broken – as it indeed was. Instead, he jumps to a conclusion.
As a result, he loses a prized possession in replacing the chair with his own, experiences lots of unnecessary stress, and perplexes Joey in the process.
Indeed, Joey thinks Rosita magically healed by her/itself.
Yet, if only Chandler had stopped, considered why the chair fell apart with such little force, and gathered a bit more info – he could have saved all that time, frustration, and his beloved chair.
Within that story lies a lesson for every contact center quality assurance (QA) team.
A Lesson for Contact Center QA Leaders
Like Chandler, contact center teams can sometimes be guilty of jumping to assumptions, quality assurance teams especially.
Still, many take a small snapshot of an agent’s performance – based on just one or two percent of their customer conversations – and use this as the basis of their evaluations.
As Chandler’s predicament proves, this can lead to analysts drawing the wrong conclusions.
After all, such a wafer-thin percentage of contacts cannot offer a fair representation of agent performance. Yet, analysts will use this to monitor agents – and sometimes even reward them.
The result is that QA becomes a game of potluck, agents fail to buy into the initiative, and broader performance trends go amiss.
From there, agent, business, and customer outcomes suffer.
The lesson: contact centers need a more thorough, consistent, and organized way to monitor their agents' performance.
The One Where a Contact Center Automated Its Quality Assurance
Nowadays, many customer service teams leverage conversational intelligence solutions to score contacts automatically.
Explaining how these work, John Matthew Ortiz, Technology Sales Manager at MiaRec, said:
“The “Auto-QA” module pulls insights from every conversation, auto-fills scorecards, and even attaches metadata for deeper analysis.”
As such, the contact center can assess agent performance at a much more granular level and open the floodgates for vast streams of new insight.
Yet, the solution is no magic wand. For it to drive real change, quality analysts, team leaders, and coaches must all share a connected learning strategy.
For instance, an analyst may identify performance gaps at an individual or team level – which is now much easier with Auto-QA – but something must happen next.
Ideally, a coach will then address the gap with tailored training, a team leader will run post-training reinforcement, and the analysts will use Auto-QA to measure the impact.