Customer experience metrics to track and why

One of the cornerstones of customer experience measurement is the net promoter score (commonly known as NPS). NPS is a metric designed to gauge customer loyalty and advocacy. It does so by asking customers a fundamental question: "How likely is it that you would recommend [the organization, the product, or the service] to a friend or colleague?" 

Clear and straightforward, NPS gets directly to the heart of CX by asking customers whether their experience inspires them to recommend the business, product, or service to others within their circles. Customers are asked to provide a rating on a scale from 0 to 10, with 0 representing "not at all likely" and 10 indicating "extremely likely." Based on their responses, customers are categorized into three groups: 

• ​​Promoters (Score 9–10) 
  These are loyal enthusiasts who are highly likely to recommend the brand to others. 
  

• Passives (Score 7–8) 
  Passives are satisfied customers, but they may not actively promote the brand. They are neither strongly loyal nor strongly disloyal. 
  

• Detractors (Score 0–6) 
  Detractors are dissatisfied customers who are unlikely to recommend the brand and may even share negative experiences with others.

Calculation and simplicity of NPS

What makes NPS particularly attractive is its simplicity. Calculating NPS involves subtracting the percentage of detractors from the percentage of promoters. The result is a numerical score that can range from -100 to 100. A positive NPS indicates a higher number of promoters, while a negative NPS a prevalence of detractors. So, for example, in a survey of 100 customers, 35 of them are promoters, 55 are passives, and 10 are detractors, that would be an NPS of 25.

Clear and straightforward. It’s this simplicity—both in terms of effort and calculation—that makes NPS such a widely used metric. Customers find it effortless to provide a single score, and companies appreciate how easy it is to use for tracking and benchmarking purposes.

NPS as a big-picture view of customer loyalty

NPS offers an overarching perspective on how customers perceive a brand. While NPS alone may not uncover specific pain points or areas for improvement, it acts as an essential benchmarking metric. Tracking NPS over time allows marketers to monitor changes in customer sentiment and assess the impact of CX initiatives. An increasing NPS score indicates improved customer loyalty and advocacy, while a declining score signals potential issues that require attention. This makes it an excellent starting point for evaluating the health of a company's customer experience.

Similar to NPS, the customer satisfaction (CSAT) score takes the issue of CX directly to the people who patronize a business. CSAT asks the question “How would you rate your overall satisfaction with the [product/service] you received?" Customers provide their answers using a scale, typically ranging from 1 (very unsatisfied) to 5 (very satisfied).

CSAT has also gained immense popularity for its simplicity and effectiveness in capturing customer sentiment. It provides a direct line to understanding whether customers are content with their experiences, or if there's room for improvement. 

CSAT calculation and application

Calculating CSAT involves tallying the percentage of customers who provide the two highest ratings on the scale (generally 4 and 5). A CSAT score of 100% indicates that every customer is entirely satisfied, while 0% suggests complete dissatisfaction. This offers businesses a comprehensive image of their customers' contentment—acting as a thermometer for gauging satisfaction and helping companies identify whether their efforts are meeting customer expectations or falling short. With these insights, organizations can more effectively identify pain points, guide CX enhancements, and create more targeted strategies for enhancing customer loyalty. 

The customer effort score (CES; also called the Net Easy Score) focuses on measuring the level of effort customers need to exert when interacting with a company. In essence, it seeks to answer the question, "How easy was it to deal with our company today?" Respondents typically have three straightforward options: easy, difficult, or neither. 

Much like NPS and CSAT, CES provides actionable data that organizations can use to streamline their processes, reduce customer effort, and ultimately enhance the customer experience. To calculate CES, simply start by collecting responses from customers who have interacted with the company and have been asked to rate the ease of their experience. Then, it's just a matter of subtracting the percentage of respondents who found the interaction difficult from those who found it easy. 

Potential business impact of CES

Effortless interactions tend to translate into positive reviews and impactful business outcomes. Customers who find it easy to engage with a company are more likely to recommend the brand to others. As such, high CES scores can directly indicate the current state of a company's reputation and the likelihood of word-of-mouth growth. 

Incorporating CES into a suite of customer experience metrics allows for the targeting of specific pain points in the customer journey. Moreover, as CES measures the ease of customer interactions, improvements in this score can have far-reaching consequences—reduced customer churn, increased loyalty, and a more satisfied customer base. Customers appreciate simplicity, and by prioritizing their convenience, it can solidify a brand's reputation as one that values their time and effort.

Customer lifetime value (CLV) is a metric that transcends individual transactions and looks at the broader picture of customer revenue over time. It takes into account not only the money a customer has spent but also factors in the costs associated with acquiring, retaining, and serving that customer. At its core, CLV provides insights into the long-term financial value each customer brings to a business, measuring how much money a customer is expected to generate during their entire relationship with the company.

CLV is often calculated on an individual level based on a customer’s historical behavior. Start by identifying the average amount of money the customer has spent with the company per year, and then multiply that by the number of years the customer is expected to continue doing business. This calculation can be extended to groups of customers in a more predictive model using intelligent data analytics.  

CLV, the customer journey, and identifying the highest-value clients

One thing that sets CLV apart from other metrics is its focus on the customer journey as a whole. While metrics like NPS and CSAT gauge specific moments in the customer experience, CLV takes a more holistic view. It acknowledges that a customer's value extends beyond a single interaction or purchase. This insight is vital in modern business, where customers engage with brands through multiple touchpoints (online and offline). CLV allows marketers to track how this journey evolves over time, helping to identify trends, patterns, and opportunities to holistically enhance CX. 

Additionally, when customers exhibit a consistently high CLV, it indicates that they not only make frequent purchases but also are likely to remain loyal to a brand. These customers are the lifeblood of a business, contributing significantly to its growth and sustainability. Identifying and nurturing valuable customers is a strategic imperative for businesses hoping to thrive in a competitive landscape. High CLV customers are more likely to become brand advocates, spreading positive word-of-mouth and attracting new customers. They also often require less marketing spend to retain, making them a cost-effective asset for a company.

Customer churn rate (often referred to as attrition rate), is a pivotal customer experience metric that reflects customer loyalty and retention. This metric measures the percentage of customers who end their relationships within a specified time frame, typically over a month or a year. In essence, it quantifies the rate at which customers are churning—falling away and leaving a company to do business elsewhere. 

A high churn rate is a clear indicator that customer experience is falling short in some way. It suggests that customers are not finding enough value or satisfaction in a business's products or services to continue their patronage. Monitoring churn rate allows a business to begin pinpointing areas of concern, identifying potential issues in the customer journey, and taking corrective actions to improve customer retention.  

To calculate the churn rate, simply identify the number of customers lost over a predetermined time period by the number of customers at the beginning of that time period, and then multiply that number by 100 to get the churn-rate percentage.

Tracking churn to prevent customer attrition 

Analyzing churn rate is not just for measuring customer departures; it's about proactively preventing them. High churn can be costly for businesses, as acquiring new customers generally requires more resources and investment than retaining existing ones. Additionally, a high churn rate can signal reputational damage if dissatisfied customers share negative experiences with others. 

By closely examining churn data, marketers can gain valuable insights into customer behaviors and pain points. Are customers leaving after a single bad experience, or is there a gradual decline in satisfaction over time? Are there common patterns among departing customers that reveal specific issues to address? With this knowledge, a company can implement targeted strategies to enhance the customer experience, mitigate churn, and build longer-lasting customer relationships. 

Taking a break from some of the sentiment-based metrics we’ve been focusing on thus far, average response time (ART) looks at the operational aspects of customer interactions. This metric measures the average time it takes for customer support teams to respond to customer queries, issues, or requests across various channels, including phone, email, live chat, social media, etc.

ART is a direct representation of how customers perceive the responsiveness and efficiency of a company's support services. Customers expect timely assistance when they encounter problems or have inquiries, and a prolonged response time naturally leads to frustration and dissatisfaction. Therefore, understanding and managing average response time is pivotal in delivering a positive customer experience.

How to calculate average response time

Calculating a company’s ART means monitoring individual customer service and support interactions. By tracking the amount of time it takes agents to respond to customer tickets, a company can then determine the total amount of time spent responding and then divide that number by the total number of tickets to get the average response time. 

ART serves as a clear reflection of a business's ability to address customer needs promptly. Monitoring this metric makes it easier to identify bottlenecks, inefficiencies, or resource shortages in support processes. It also enables more informed decisions, such as optimizing staffing levels, streamlining communication channels, or implementing automated responses to reduce waiting times. Combined with sentiment-based metrics (NPS, CSAT, and CES), average response time provides a high-altitude view of the customer experience landscape, helping a business create a more seamless and responsive service environment.

Much like average response time (and even sharing the same acronym, which we will avoid in this section to limit confusion), average resolution time focuses on the time it takes customer support teams to successfully resolve customer issues or requests. In essence, average resolution time is a critical operational metric that gauges the efficiency and effectiveness of support processes throughout the customer journey.

Quick issue resolution is often synonymous with a positive interaction. When customers encounter problems, they desire not only prompt attention but also swift and satisfactory solutions. Average resolution time is the metric that sheds light on how a company is meeting (or not meeting) these expectations. A shorter resolution time implies that support teams are adept at addressing customer concerns, leading to higher levels of satisfaction.  

The correlation between quick resolutions and high customer satisfaction

Customer satisfaction is intrinsically linked to the speed and effectiveness with which customer issues are resolved. Customers who experience swift resolutions are more likely to feel valued and pleased with the service they receive. On the contrary, prolonged resolution times can leave customers frustrated and dissatisfied, tarnishing their overall perception of a brand. Thus, efficiently managing average resolution time can have a profound impact on the customer experience strategy. 

Optimizing support processes, streamlining workflows, and empowering teams with the necessary tools and knowledge can reduce resolution times and elevate customer satisfaction levels. This, in turn, fosters customer loyalty and positive word-of-mouth, contributing to the growth and success of a business.

In addition to the fundamental customer experience metrics discussed above, there are many more granular metrics that cater to specific business needs and nuances. These metrics delve deeper into various aspects of the customer journey, providing a comprehensive understanding of customer sentiment and behavior. While the list is too extensive to include here in full, let's touch on a few categories of these metrics and their significance:

• Retention loyalty 
  This category of metrics gauges the likelihood of customers remaining loyal to a brand. Understanding the factors that influence customer retention is crucial for businesses aiming to sustain long-term relationships with their clientele. 
  

• Purchase loyalty 
  Purchase loyalty metrics reveal how likely customers are to continue buying from a brand. These are essential for businesses wanting to foster repeat purchases and grow their customer base. 
  

• Meeting expectation 
  Measuring how well customer experience aligns with customer expectations is vital. These metrics help identify areas where a brand exceeds or falls short of customer anticipations, guiding improvements.