The Top 7 Customer Satisfaction Metrics You Need to Know + How to Calculate

May 26, 2020
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Monitoring and analyzing customer satisfaction metrics is a critical practice for your business. And the reason why is pretty obvious: not only do unsatisfied customers mean a loss of revenue when they churn, but garnering a bad reputation amongst your key audience can also turn away potential new customers as well.

Paying attention to customer satisfaction metrics can help improve customer trust, loyalty, revenue retention, and brand image. With so many similar-sounding terms out there, it can be difficult to know where to start digging into your data. Below we define the top seven customer satisfaction metrics you should know.

What is Customer Satisfaction?

First things first, let’s get a better look at the big picture. What exactly are you trying to measure with customer satisfaction metrics? Think of it like this: every customer that interacts with your brand has a certain set of expectations, based on their previous experience with your brand, even if that experience is as small as reading an online review or seeing one of your Instagram ads. Customer satisfaction measures how well your brand’s product and services meet those customer expectations.

Though the two terms are often confused with one another, customer satisfaction is not the same thing as customer experience. Customer satisfaction can be thought of as the overarching umbrella term, while customer experience is a factor in creating customer satisfaction. It’s important to measure a variety of factors to get a clear picture of this, as your business may be excelling in one customer satisfaction metric but failing in another.

What Types of Metrics Measure Customer Satisfaction?

Below are the seven most useful metrics used to define your company’s customer satisfaction.

1. Net Promoter Score (NPS)


Definition: Net Promoter Score is a newer school of thought when it comes to measuring customer satisfaction, though its popularity has surged in the last decade and a half since its inception. NPS is specifically concerned with customer loyalty to a brand.

How it Works: NPS is measured on a scale of -100 to 100, with positive 100 being the best possible score. Customer data is gathered using a specific NPS survey, with the question “How likely is it that you would recommend COMPANY/PRODUCT to a friend or colleague?” Respondents are asked to give an answer to this question between 0 (not at all likely) and 10 (extremely likely).

Responses are then categorized into three sections:

  1. Detractors (responses 0-6): These are people who are not loyal to your company
  2. Passives (responses 7-8): These are people who are satisfied but not necessarily loyal
  3. Promoters (responses 9-10): These are people who are extremely satisfied, highly loyal to your company, and likely to recommend you to others

To calculate your NPS, simply subtract the percentage of Detractor responses from the percentage of Promoter responses to get a number between -100 and 100. For example, 50% Promoter responses - 20% Detractor responses = an NPS of 30. You don’t have to do anything with the remaining 30% of Passive responses.

Pros and Cons:

  • Pros: Easy to use, studies have shown it correlates to revenue growth
  • Cons: Narrowed focus doesn’t give the full story on customer satisfaction

2. Customer Satisfaction Score (CSAT)

Definition: Unsurprisingly, CSAT remains one of the most widely-used customer satisfaction metrics. Once again, this data is gathered using a specific question in a customer feedback survey, such as “How satisfied are you with your experience?” Respondents typically answer this question on a scale of 1-5 or 1-10.

How it Works: CSAT is calculated as an overall percentage out of 100. Once you decide on your specific survey question and have gathered your responses, you simply divide to find the percentage of positive respondents. For a scale of 1-5, you’ll want to take just the 4 and 5 responses, and for 1-10 just the 8, 9, and 10 responses. For example, 120 positive responses/200 total responses = 0.6, or 60% CSAT.

Pros and Cons:

  • Pro: Short and easy for customers to complete, easily adaptable to measure different products or services
  • Cons: High potential for response bias, leading to skewed data

3. Customer Effort Score (CES)


Definition: Customer effort score (CES) measures how much effort a customer had to put in to interact with your brand, product, or service. Examples include working with a customer service rep to resolve an issue or setting up newly purchased software. CES has become increasingly popular in the last decade as a way to specifically measure customer loyalty, similar to NPS.

How it Works: Once again, CES is best measured through customer feedback surveys. These types of questions typically look something like “How easy was it to interact with COMPANY/PRODUCT?” or “How easy was it to resolve this issue?” Respondents are asked to answer on a scale of “very difficult” to “very easy.” Using the same method as CSAT above, you can calculate the percentage of “easy” and “very easy” responses, or perhaps more usefully, the percentage of “difficult” and “very difficult” responses to see where things need to be improved.

Pros and Cons:

  • Pros: Easy to identify touchpoints that need improvement, strong direct correlation with conversions
  • Cons: Doesn’t represent a customer’s holistic relationship with a brand

4. Customer Service Satisfaction (CSS)

Definition: As the name would imply, CSS measures how satisfied your customers are with the support provided by your customer service team. You can gather this data through a customer feedback survey, or, more typically through an automated message sent directly after a customer interacts with a representative.

How it Works: CSS can be easily calculated as a percentage, depending on the type of scale you choose to use. For example, after an issue is resolved with the support team via email, you could send the customer a follow up email asking them to rate their experience on a scale of 1-10. Or, after they use a live chat feature on your site, you could give them the option to select great, neutral, or bad customer service. Then, you simply gather all the responses for the specific channel you’d like to measure and calculate the percentages.

Pros and Cons:

  • Pros: Directly measures one of the most important customer satisfaction metrics, easy to break down by channel or team
  • Cons: Obviously, only provides data on this specific metric without giving the full customer satisfaction picture

5. Customer Acquisition Cost (CAC)


Definition: Though CAC is typically used more by sales and business development departments, it can serve as an important benchmark for customer satisfaction as well. CAC measures how much money, on average, your company is spending to gain one new customer.

How it Works: Calculating CAC is straightforward. Take the total amount of money your company spent on marketing efforts for the period, divided by the number of new customers for the period. For example, say in one month 500 people purchased from your website, after you spent $3,000 on social media advertising. Your CAC for this period and channel would be $6.

Pros and Cons:

  • Pros: Understanding CAC’s for specific periods and channels can help you identify issues with your customer satisfaction
  • Cons: CAC can’t help you understand exactly what is going wrong or right, it’s used more as an indicator

6. Customer Churn Rate (CCR)

Definition: Similar to CAC, CCR is typically a metric used more by sales and marketing departments, but it can be an important check for customer satisfaction efforts as well. CCR is the percentage of customers that leave your business over a period of time. If other customer satisfaction metrics are positive, you can reasonably expect that CCR will be positive as well. If not, it is a definite indication to dig deeper into your other metrics.

How it Works: The calculation for CCR is also fairly simple. Take the total number of customers at the beginning of the period, subtract the total number of customers at the end of the period, then divide by the total number of customers at the beginning of the period to get your churn rate. For example, say you started the summer with 1000 customers. By the end of the summer, you had 850 customers. Your CCR would be 1000 - 850 = 150, 150/1000 = 0.15 or 15% CCR.

Pros and Cons: Same as CAC above. This metric is more useful to provide context to your other customer satisfaction metrics than as its own measurement.

7. Customer Health Score (CHS)


Definition: You can think of CHS as a summary of all your other customer satisfaction metrics combined. Basically, how “healthy” is the customer? How likely are they to take a specific action based on that “health”, such as churn, upsell, refer a friend, etc.?

How it Works: CHS is hard to define, because it’s different for every business. On a basic level, it works by first defining a customer health scale. This could be 1-5, very unsatisfied to very satisfied, red, yellow, and green color profiles, or any other type of measurement that’s easy to differentiate. Next, you define the outcomes or actions you want to predict and utilize the rest of your customer satisfaction data to sort customer health. For example, a customer who answered “very difficult” on a recent CES survey might be placed in the “red zone” for CHS, with a prediction that they will churn in the next period. Here is an excellent resource to learn more about this process.

Pros and Cons:

  • Pros: Saves time and effort by combining customer satisfaction metrics for an accurate, holistic view of a customer
  • Cons: Difficult to set up and manage, will likely be time-intensive in the beginning

How CX Tools Can Help Gather Customer Satisfaction Metrics

You’ve probably noticed that most of these customer satisfaction metrics can be time-intensive to gather and analyze. Utilizing CX tools can help cut down on manual research by automating customer feedback surveys, coding the qualitative data you receive from those surveys, tracking sentiment and user intent through text analytics, and more. This all helps to save you time, money, and employee bandwidth while continuing to gather invaluable insights from your customer satisfaction metrics.

Contact Chattermill for a product demo today to see how our AI-backed software can help you make smarter CX decisions.

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