CX Metrics Series: Customer Satisfaction


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This is the second blog post in a series that examines key Customer Experience metrics that every Voice of the Customer (VoC) program should measure to better understand your visitors’ digital experience. In this post, we look at a fundamental Customer Experience metric that provides a great sense of how visitors feel about your website: Customer Satisfaction.


“How are you?”

How often do we say or hear this question every day? When passing by your neighbor in the morning, when greeting your colleagues when you walk in the door at work, when picking up your afternoon coffee at the cafe around the corner. Asking this question to someone is almost a reflex nowadays. 

But why do we ask it?

Of course, we’re generally interested in how others are feeling. But when you really think about it, it’s a surprisingly great conversation starter. When someone says they’re feeling great, and especially when they say they’re feeling terrible, you’re naturally curious to learn ‘why’. As the adage goes: “You don’t know until you ask”.

Customer Satisfaction provides you with a general sense of how your visitors viewed their digital experience. This metric is extremely valuable and acts as a sort of compass that can guide your efforts to better understand and optimize the customer experience.


How do you measure Customer Satisfaction?

Just like how there are many ways you can ask someone how they are doing, there are many ways you can measure digital customer satisfaction. Simply put, how you approach measuring satisfaction depends a lot on what you want to do.

I find this metric serves as a great starting point to begin your analysis and to have a baseline measurement of your website performance. To get this, I find that using a single ‘overall experience’ -type question, like the one below, can be very useful:

“How would you rate your overall experience today?”

This question can serve as the ideal dependent variable for multiple regression analysis of attributes of the experience that can be used to determine independent drivers of satisfaction. I’ll show an example in the Use Case later in this post.

For this type of question, there are countless opinions as to which type of scale is the best, each with their own set of advantages and disadvantages. To measure digital customer satisfaction, I prefer a 0-to-10-point numeric scale with six offset labels for collecting feedback on satisfaction like this one:

 Customer Satisfaction Scale

In addition to the offset of the labels, which reduces text and numeric bias, the extreme positive point, labeled ‘Outstanding’, is set apart to reduce the positive skew associated with scales that use 9 or more points.

iPerceptions research has shown that this scale produces results with closer to normal distribution than scales using 9 to 11 points with end-point labels and scales that use direct 1 to 1 labels. Given that one of the principle assumptions of most statistical analysis is normal distribution of data, statistical results from using this scale produce more reliable and more reproducible results.


Why is Customer Satisfaction Important

1. As much as we hate to admit it, we’re not mind-readers

Imagine an example where two visitors access the same 10 pages during their sessions. One visitor might just be browsing, and is satisfied with the info they’re finding. The other visitor might be completely frustrated with your website navigation and can’t find the info they’re looking for.

But how can you really confirm in which category a visitor falls into?

Asking your visitors to confirm their satisfaction lets you lift the fog and get into the minds of your visitors. Plus, it lets you associate an objective rating to your website, to specific aspects of your customers’ experience, and your other data sources (e.g. web analytics or session replay).

2. Help with your customer retention efforts

Acquiring a new customer can be anywhere from 5 to 25 times more expensive than retaining an existing one. You should always keep track of your customers’ experience in some way, and confirm their satisfaction at a minimum. Tracking your existing customers’ satisfaction can help you identify the ones who might be considering jumping ship, and be able to do something about it if you catch it early enough.

3. Identify the customers who will benefit you the most long-term

Not only are you more likely to retain customers with high satisfaction, but they’re also more likely to spend more – 140 percent more to be exact! Plus, those with high level of satisfaction are significantly more likely to have desirable future customer behaviors, including trusting your brand and recommending your brand to others.

By identifying these high-satisfaction customers, you can look further into their specific experiences to determine the drivers of their high satisfaction. You could then leverage this knowledge to adjust your current CX efforts to bump up your existing and future customers’ satisfaction levels, which would greatly benefit you long-term (see #2). 

4. Identify the key drivers to your customers’ satisfaction

Customer Satisfaction doesn’t measure the experience with specific aspects of the customer experience, like how difficult it was for them to do what they wanted to do on your website. However, it does provide a great holistic view of their experience, and gives you the foundation you need to determine what specific aspects of your digital experience are the biggest key drivers to their satisfaction (or dissatisfaction).

Let’s take a look at an example where measuring Customer Satisfaction can provide you with interesting findings about your customers’ digital experience.

Use Case: Key Drivers of Satisfaction

As mentioned earlier, using a single overall experience-type question provides an ideal dependent variable for multiple regression analysis to gauge the impact that different website attributes can have on a visitors’ overall satisfaction. 

The following customer satisfaction example is based on an analysis we performed in the past for many of our clients that identifies the key drivers of their customers’ satisfaction. For this example, we use the best practice scale and wording we mentioned earlier in this post: 

Customer Satisfaction question example

In addition, we ask visitors to rate the following website attributes on the same 11-point scale, but preface it with the following stem:

Based on today’s visit, how would you rate this site as one that:

Attribute question

Attribute name

Allows you to move rapidly to the information you need?


Enables you to find what you’re looking for?


Is easy for you to navigate?

Ease of Use

Has content that is relevant to the purpose of your visit?


Gives you the amount of detail that you need?


Uses pictures effectively?


Enables you to help yourself?

Self Service

Has effective interactive tools?

Interactive Tools


Plugging this data into our Priority Grid solution, we can perform multiple regression and use Bayesian Model Averaging to determine the influence each attribute listed above has on visitors’ overall satisfaction with their session.

The output looks like this:

Customer Satisfaction Model Table

As we see in the table above, six of the website attributes were found to have had a significant impact on Customer Satisfaction (ranked in order of the average rating these attributes received from customers):

  • Depth
  • Ease of Use
  • Movement
  • Discovery
  • Relevancy
  • Interactive Tools

The Movement attribute was the most influential of these website attributes, followed by Discovery. As such, it appears that the website’s navigational aspects were the strongest drivers of satisfaction (or dissatisfaction) for this website’s visitors.

When you chart each of the significantly influential attributes based on their influence and the ratings they received, you also get a clearer comparison of these attributes. Splitting these attributes into four quadrants provides a great way to determine where you can place your focus during your analysis, and also specific types of issues you can look into that would most likely have the biggest positive impact on customer satisfaction:

Customer Satisfaction Priority Grid

Top-Left Quadrant (Top Priority)

High influence / Low Rating

Top-Right Quadrant

High influence / High Rating

Lower-Left Quadrant

Low influence / Low Rating

Lower-Right Quadrant

Low influence / High rating

In this example, we see that the Movement attribute (blue bubble) falls within our Top Priority quadrant, while the Discovery attribute (light green bubble) comes very close. With these two navigation-related attributes being the most influential website attributes, and both performing below average, you can use this knowledge as a starting point for your analysis.

By seeking out specific insights related to your customers’ confusion and frustration navigating your website, and their inability to find their desired content, you would be focusing your efforts on addressing issues that could have a substantial impact on Customer Satisfaction.


Customer Satisfaction is a compass

Navigating the complex forest that is the customer experience can be dangerous business. You can easily lose your way as you try to find ways to optimize the countless items that fall within the customer experience spectrum. That’s why before you walk too deep into this forest that you make sure you have a compass with you so you can easily find your way through and back. The Customer Satisfaction metric can serve as that compass.

Did you like this post? Make sure to check out Part 1 of our Customer Experience Metrics Series, which looks at the Effort metric.

Banner Image Source: Unsplash

Republished with author's permission from original post.

Duff Anderson
Duff Anderson is a visionary in digital Voice of the Customer research with over 20 years' experience. As SVP and Co-founder at iPerceptions, Duff is responsible for providing expert advice to organizations on how to gain a competitive advantage across the digital customer lifecycle and become more customer-centric.


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