Numbers do not lie, so the saying goes.
Customer service has become a defining point of business success, customer satisfaction, and future growth. It is what differentiates businesses and brands that customers care about and remember.
One way of gathering crucial feedback on your customer service is to track customer service metrics, which are a measurable way of checking a business’s vital signs.
But which scores truly matter in improving your business and customer happiness?
Turning metric scores into insight can be challenging. Are the reviews and comments a fair representation of what customers want? How should you read the responses objectively? More importantly, what do these scores mean for your business?
We review the three most common metrics for measuring customer support quality and dive deep into what these scores tell you.
Each of the metrics below has a purpose and a place. Each asks a different question that casts a different light on the customer’s experience. Knowing which metric works best for your business and understanding how to interpret each metric helps you get the most value from implementing these metrics.
Watch the video below and find more content like it on the Influx YouTube channel or simply read on to explore the value of CSAT, CES and NPS :-)
CSAT, or Customer Satisfaction, is a survey-based metric that asks customers if they are happy or satisfied with the service they received. It can be requested at the end of a conversation or in an email signature along the way.
It’s fast, easy, and straightforward for you and the customer. And that ease of use has its advantages. You’ll usually get more responses, which means you’ll have more data about how customers feel. You don’t need to take a vast amount of time to analyze the data, so you’ll get value from your surveys faster.
It’s not always predictive of your customers’ loyalty. Customers can frequently indicate that they are satisfied with the customer service but then churn the following week. Customers will occasionally use the feedback opportunity to share gripes about your product, pricing, and other non-support-related things. While all feedback is valuable, you might be frustrated if you’re trying to measure support quality precisely.
Who should use CSAT?
Everyone. CSAT is a universally helpful tool for quickly hearing what your customers are thinking (more on that later). Even if you choose to use another tool, adding another opportunity for customers to provide feedback is a net positive.
Net Promoter Score, or NPS, is another survey-based metric designed to predict customers’ future loyalty. NPS asks a customer how likely they are to recommend your business to a friend or family member. While not strictly a customer support metric, NPS helps you understand the customers’ experience, of which customer support plays a significant role.
Because NPS surveys offer responses from 1-10, there is more nuance in separating the detractors from the promoters. Customers who respond “9 or 10” are delighted, and companies can utilize these fans for advocacy programs. Customers who respond with “6” or lower are more likely to churn in the future and provide valuable insight into what needs to be improved.
NPS measures the entire customer experience at once, so it’s not specific to customer support quality. While you can undoubtedly segment the responses by customers who have contacted support and those who have not, it won’t provide targeted feedback as other metrics do.
Who should use NPS?
Businesses that are looking to identify advocates and that view the customer experience as a company-wide initiative. If you want big-picture feedback from customers, NPS can be a valuable tool.
Customer Effort Score (CES) is a metric designed to measure the levels of difficulty when customers do business with you.
CES is based on the study that found that friction, or effort, is the leading cause of customers’ disloyalty. The more difficult you make it for customers to achieve their goals or get help, the less likely they will return in the future. CES is measured by sending out a survey to customers after their customer support interaction, asking, “On a scale from one to seven (one being very difficult and seven being very easy), how easy was it to get the help you needed today?”
CES looks at customer support through a very different lens than other surveys, which means the feedback you receive will be different than generic CSAT feedback. Any insights will be specifically around the difficulty or ease of the interaction. Acting on these insights can have a significant impact on how customers perceive your customer service experience.
CES can be more challenging to interpret and rally support around. Because it’s a newer, less-used metric, you may have to educate other stakeholders on the effortless experience’s value. We recommend starting with this article from Harvard Business Review or suggesting The Effortless Experience as your next company’s book club read.
Who should use CES?
Businesses who already see high CSAT rates can benefit from measuring customer effort. When you’re already providing reasonably good support, you may find that your CSAT score plateaus. Measuring CES at the end of interactions will give you different insights about your support’s quality and actionable feedback on where you can make things easier for your customers.
How to interpret customer satisfaction survey responses
No matter which metrics you choose to use, reading the scores can provide more questions than answers. What about the customers who decided not to answer the survey? When only dissatisfied customers leave feedback, are these scores an accurate assessment of your service quality?
Below, we dive deeper into how you can get value out of quality metrics, even if they aren’t always the best statistically significant data.
Real-time service recovery
Perhaps the best use of customer surveys is as a real-time alert system. When a customer indicates that they are displeased with the quality of service they received, it’s time to take action. The issue needs to be addressed promptly, whether the ticket is re-opened with the same agent or escalated to a team lead or supervisor.
Before interpreting or analyzing all the scores together, make sure to read them at face value first. When customers say they’re upset or dissatisfied, you need to jump on it and fix it quickly.
How many responses do you need before your surveys are statistically relevant? Alternatively, how confident are you that your results are accurate and representative of your entire customer base? If you’re making a proposal to your executive team based on survey data, you can expect at least one question around the sample size. (“I don’t believe that NPS is accurate, the sample size isn’t big enough.”)
Calculations and comparisons will help shed light on how sample size impacts your customer satisfaction metrics.
For instance, when we compare two sets of data, we usually want to know how they’ve changed over time (i.e., month over month) or between two demographics (free vs. paying customers).
The temptation is to compare simple averages between the two data sets, but that isn’t accurate when your sample size is different. While we won’t get into the details of using sample sizes to verify trends here, we highly recommend checking out Adam Ramshaw’s guide to using the t-test on customer satisfaction metrics.
Internal quality metrics
Another check that you can use to corroborate quality results is internal quality assurance or conversation reviews. Instead of leaving quality measurement in your customers’ hands with surveys, you can measure quality internally as well.
Start by creating a scorecard that contains all the rating categories you consider part of a “quality” conversation, for example, “personally connected with the customer,” “provided accurate information,” or “shared additional knowledge.” Review some conversations each week to understand the quality of the conversations your agents are having.
We recommend reading Klaus’ guide to conversation reviews as a great starting point.
Measuring the quality of your customer support is essential to providing a great customer experience. Only by listening to your customers, analyzing the metrics, and taking action can you improve your customer support. While all metrics have their quirks, the truth is that each metric provides information - you only need to know how to read the results to get that information.