Ready to improve your quality assurance (QA) process? Read this first.

Abigail Sims

A solid quality assurance process is one of those needs that transcends industry. Whether you work in technology or marketing, sell a product or service, have a hundred-person customer support call center or it’s just you and a few others answering emails—good quality assurance practices are just, well, essential. But these days, you may be starting to think it’s time for a change in those tried-and-true practices, what with the technology at hand and innovations accelerated by the recent pandemic. (A robot who’ll send these emails for me? Yes, please.)

If you’re looking to improve your quality assurance process, you’re in the right place. But before you dive in, make sure to ask yourself these three questions first: 

Have we invested in the right toolset? 

Today, your business is collecting more data than ever before, and the future only holds more. So, when you look to improve your quality assurance practices, ensure that you’re investing in a tool that will make data easier to access, not harder. It’s essential to invest in a toolset that can handle, process, and parse your data in a way that will benefit your business and provide your leadership with the intelligence they need to make the best possible decisions. 

Are we automating the right things? 

Don’t automate a process that doesn’t work! Before you invest time, money, and effort into implementing expensive cutting-edge solutions, make sure you know what works (and what doesn’t), so that your new QA process will be as successful as possible. This means you can’t just automate your current process and hope for the best. Instead, take a close look at your current processes, and figure out what questions and metrics yield the most actionable results. Keep those during your digital transformation—and toss the rest. 

Are we tracking customer experience (CX) ratings?

Perhaps the most important part of improving quality assurance in this day and age is ensuring that you are tracking the right metrics. While many folks are still attached to the traditional metrics like greeting/closing phrases, call length, and three smiley faces on the post-call survey, these metrics don’t come close to capturing an accurate image of the effort involved in the call. In fact, we’ve found that customer experience questions provide a much more accurate reflection of effort, and are a better indicator of customer loyalty.

Key takeaway: Customer experience metrics should comprise at least 30% of your new QA scorecard for best results. 

It’s tempting to just dive into improving quality assurance processes with spot checks, surveys, and other band-aid fixes—but don’t miss the forest for the trees! Here in the digital age, it’s best to tackle problems like QA with high-octane machine-learning powered technology solutions specifically developed to process large volumes of digital data. (Like the one we built here at Tethr.) To learn more about our quality assurance solution, check out our quick guide, A QA Solution That Actually Works. 

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