Quality Scores and CSAT: The Oil and Water of Contact Center Management

Most every contact center measures both quality scores and CSAT scores. And while ostensibly both of these metrics are designed to improve the caliber of each customer interaction, it’s no secret that in most contact centers these metrics seem to fluctuate wildly and independently from each other, eventually turning into a kind of metrics whack-a-mole—you fix one only to find that the other now needs attention.

An agent can follow all the company policies and still provide a terrible experience and, conversely, an agent might provide a great customer experience but break all the rules while doing so.

But shouldn’t they be closely tied together? Afterall, shouldn’t higher quality scores result in happier customers? And wouldn’t you assume that an agent who delighted a customer would get a higher quality score for handling the call properly? Well, that’s not normally the case. And here’s why.

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Typically a contact center’s quality score reflects the extent to which the agent followed company policies for handling calls. This might involve greeting the customer properly, reading any required compliance language, and adhering to the rules the company has laid out for agents to follow. CSAT scores, on the other hand, reflect how happy a customer is with the service they’ve received. The problem, then, is that an agent can follow all the company policies and still provide a terrible experience and, conversely, an agent might provide a great customer experience but break all the rules while doing so.

Further complicating the utility of both quality scores and CSAT scores is the fact that they’re both a reflection of just a small sample size of calls. Most contact centers don’t audit every call for quality and anyone who has looked at results from CSAT surveys knows the customers who choose to leave feedback tend to be the customers who had the worst experience.

Some contact centers have turned to natural language processing (NLP) to solve the issue of sample size. The rationale in that case is that if you’re able to automatically transcribe every call, you can audit more systematically and better uncover quality issues and perhaps even discern the caller’s mood based on language and tone. But even with recent significant advancements in NLP, it’s difficult to accurately ascertain both call quality and customer satisfaction at scale simply by transcribing what was said.

Further reading: Cure The Cause of a Bad Agent Experience (Not Just the Symptoms)

So how can you use CSAT and quality scores together so that they result in tangible, meaningful, and lasting improvement for the customer experience?

For starters, adopt tools that give agents next-best-action guidance so every call is handled correctly and quality scores improve. This guidance helps agents complete proper call openings and closings, properly authenticate customers, read any compulsory compliance language, and ultimately achieve a high quality score. Then, make sure those tools are used on every call so you can get a more accurate picture of what’s going on in your contact center and so you can uncover quality issues that you otherwise might have missed with sporadic fly-bys and call audits.

When those tools are in place, you are able to establish a baseline for how long a correctly-handled call that meets quality standards should take. This might be longer than you’d like but it is a starting point and it ensures your agents are achieving the requisite quality scores. Afterall, a good call isn’t necessarily the fastest call; it’s the call that resolves the customer’s issue while adhering to company policy.

Then finally, once that baseline is established, then you can focus on the tools, training, and processes that help improve CSAT scores by reducing the time required for your previously-established baseline call. The result is consistently improved CSAT scores without ever cannibalizing quality.

Get straightforward, practical advice on how to get greater control over your contact center performance.

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