Six Metrics Used to Measure and Optimize Customer Experience
By Emily Bielak
In prior articles, we examined some definitions of various aspects of Customer Experience (CX) research, as well as four methodologies used to measure and optimize the ideal experience for a target audience. Now let’s look at some of the common metrics used to understand customer perceptions as well as to measure whether the actions a brand takes is having a positive impact on those perceptions.
It is important to note that, while all of these measurement approaches are important on their own, none by itself represents the complete and exhaustive measurement of customer opinion. Rather, it is the application of many (or all) of the appropriate tools that will provide the most accurate and holistic measurement of customer perception — including one critical metric that is unique to The Martec Group and the brands we work with.
The Five Most Common Measures of CX (and One Critical Novel Metric Not to be Overlooked)
Following is an overview of the most common metrics used to help brands understand customer perceptions and inform decisions to improve experiences:
1 – Customer Satisfaction (CSAT)
Customer Satisfaction (CSAT) is a very common measurement of — as the name suggests — customer satisfaction with a given brand, product, service or experience. Satisfaction is typically rendered numerically, based on various survey instruments or customer conversations.
While CSAT is a common (and historically valuable) reflection of customer feedback, we stress the importance of measuring satisfaction along multiple discrete touchpoints a customer may experience, in addition to gauging overall satisfaction with the brand, product or service on the whole. In fact, you typically want to pinpoint gaps, challenges, or successes, so the brand can take an informed approach as to what, specifically, needs to be changed or amplified to maximize satisfaction.
2 – Likelihood Metrics
Likelihood Metrics are a category of measurements used to understand the likelihood that a given customer will take various actions going forward. While the most obvious might be to ask how likely the customer is to purchase again, other likelihood metrics include willingness to refer a friend, revisit a website, consider another complementary product line, or leave a positive review.
Such measurements serve to understand the loyalty aspect of the customer experience. In these studies, we are working to understand the relationship that exists between a brand and its constituents, rather than merely measuring a past transaction. You might say that Likelihood Metrics are not just backward-looking, they are forward-projecting as well.
3 – Net Promoter Score (NPS)
Net Promoter Score (NPS) is a widely recognized measurement of a customer’s likelihood to recommend a product or service to someone else. NPS asks respondents to provide feedback numerically, on a scale of 0 to 10, how likely they are to recommend. The instrument identifies:
- Who are a 9 or 10 on that scale, with 10 being the most likely to recommend. These respondents are considered your Promoters.
- Those providing a response from 7 to 8 are considered your Passives.
- Those falling between 0 and 6 are considered Detractors.
The NPS is calculated as the percentage of Promoters minus the percentage of Detractors. So if your survey of 100 respondents reveals 40 Promoters and 15 Detractors, your NPS is 25 (40 minus 15).
The methodology was developed in 2003 by Fred Reichheld, a partner at Bain & Company, who “created this new way of measuring how well an organization treats the people whose lives it affects — how well it generates relationships worthy of loyalty.” It has been adopted and integrated into a great many corporate dashboards over the two decades since. And while the metric is illustrative, it is not without its limitations.
We recommend that brands measuring NPS take a careful approach to understanding who is being surveyed and when. Surveying happy customers within 10 days of a purchase is liable to return a much more favorable-looking NPS than a survey that canvasses existing and past customers within the last year, for example. More on this in the closing section further below.
4 – Customer Churn
Plainly defined, Customer Churn is a measurement of how and when customers fall off and become ex-customers. This is sometimes referred to as “churn rate” or “attrition rate,” such as the number of subscribers who cancel or don’t renew a subscription over the course of a year.
As with all of these methodologies, Customer Churn is a useful component to measuring overall CX performance, but it cannot stand alone. For one, quantitative analysis alone, which only measures the rate of churn, does not completely solve the problem or inform what needs to change in order to reverse trend. Customer Churn is most effective at signaling there is an issue to be addressed. But identifying that precise issue and understanding the various drivers and customers’ preferred alternatives are matters of further study and analysis.
5 – Customer Effort Score
A newer (and perhaps trendier) metric to emerge in recent years is Customer Effort Score. Because technology in general has conditioned customers to expect ease and immediacy in every walk of life, brands are placing greater emphasis on understanding the effort perception of customers to identify opportunities to make various touch points easier, quicker or more seamless.
Typically administered in survey form using a scale of 1 to 5, or from “Extremely Difficult” to “Extremely Easy,” these studies seek to understand customer perceptions along various steps in the journey, such as:
- How difficult was it to enroll in a service?
- How difficult was it to get onboarded?
- How difficult was it to remove an item from your cart?
- How difficult was it for the customer to learn about the product or service?
- How difficult is it to get answers to frequently asked questions?
- How difficult is it to gain access to live customer service or a resource library?
- How difficult is it to find various assets or buttons on a website?
The objective is to make the customer exert as little effort as possible, whether purchasing or simply looking for information. Interactions should be frictionless, immediate, intuitive, and generally pleasant experiences.
What is particularly valuable is to look at virtually every possible experience, and measure Customer Effort in each discrete interaction. Importantly, we advise that brands segment their customers along various personas based on demographics and other considerations. Perhaps most experiences yield the desired Customer Effort Score, but one particular interaction is causing customer distress. Or, perhaps it is one specific customer segment that is having a very specific issue — based on language or comfort with technology, say — that is dragging down an otherwise acceptable score.
As with every metric we researchers rely upon, the more granular you can get when conducting your research, the more informative and actionable the insights will be.
6 – Martec Emotion Score
Proprietary to The Martec Group, The Martec Emotion Score (MES) is a numerical representation of the emotions that are associated with a brand, product, service or experience, including the various experiences along the entire journey — from consideration and beyond the ultimate purchase. Two key attributes of MES make it an invaluable tool in CX measurement. One, it is intuitive and illustrative in that it applies a numerical value to what might otherwise be considered a difficult-to-quantify arbiter of experience: human emotions. Secondly, by its very definition, MES accounts for some of the most powerful drivers of action or inaction: again, human emotions.
What’s important to note is that emotions are complex, and they are not static for any one customer along the various journeys humans take when making purchase considerations. In fact, there are often peaks and valleys, even among those who would express overall satisfaction with an interaction with a brand. Nerves or apprehension may precede relief and excitement. Happiness may be later met with regret. And so on.
By fully understanding these various emotions experienced by various audience segments over time, a brand can take proactive measures to either reverse and neutralize negative emotions or amplify positive emotions and convert them into desired actions and outcomes. It’s been well documented that customers will recall how they felt at their emotional peaks along their unique journeys, as well as the lasting impression the experience left them with at the end (Peak End Theory).
Because this particular methodology is unique to Martec, you may be less familiar with Martec Emotion Score. It is necessarily a complex topic, given that we are dealing with the complexity of human emotions. But Emotion Intelligence research need not be a complex or cumbersome undertaking. In fact, EI and MES can be plugged into virtually any CX research initiative. Learn more about EI and MES with this free guide found here.
Not One or the Other, But Rather All
Again, the point is not to present these as a menu of metrics to choose from, but rather an overview of some of the most common relied-upon ways to measure customer satisfaction, perception and loyalty. Using all of them (as applicable and appropriate) provides a much more holistic view of the customers and prospective customers that are interacting with your brand.
By way of illustration, a customer may be generally satisfied with a given product or service on the whole but could have found a specific interaction with the brand particularly difficult (customer effort), which could cause them to explore other options going forward. To reference another example, Net Promoter Score measured in isolation can be unreliable depending on who is surveyed. In some instances, brands are looking to inflate (and report upon) their NPS numbers, so they may choose to only survey repeat customers or those who write favorable online reviews.
It is generally wise to get as granular as possible when measuring CX and UX, canvassing all audience segments and across the entire customer journey, treating each potential touchpoint as a unique experience to be measured. The objective should be to pinpoint perceptions and emotions experienced with exactitude, as opposed to looking for an “overall feel” of the entire customer population as a monolith.
Understanding the emotional connections between brand and customer is becoming more and more critical. Customer Churn, for example, is often driven by emotions in discrete interactions or touch points, as are perceptions relative to Customer Effort. Identifying, examining and understanding the emotional peaks and valleys customers endure along the entire sentiment journey is key to understanding, not only how to engineer the optimal user experience, but how to apply those insights to marketing messaging, advertising and brand positioning as well.
Lastly, I cannot overstate the importance of taking these temperature readings multiple times. A single snapshot is useful, but it does not speak to how the actions a brand is taking are moving the needle (positively or negatively). Make a commitment to track these metrics over time at some predesignated cadence. Learn if the steps you’re taking to optimize CX are having the desired impact. If they are, double down…if they’re aren’t, it’s time to course-correct.
Measure twice, cut once is an old saw for a reason. Whether it’s carpentry or CX, measuring more than once is the best way to avoid errors and, in the case of CX, keeping customer affinity and loyalty ingrained into your corporate culture permanently.
Want to learn more? Read “How One Dry Cleaning Franchise Harnessed the Power of EI to Optimize the CX and Improve Business Metrics.”
Emily Bielak serves as Director for Martec, with specific emphasis on customer experience research and initiatives. To get in touch, use the Contact Us form below.