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The Pros and Cons of the Top 7 Customer Service Metrics

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Top Customer Service Metrics: Which one to use and why 

Customer service metrics are a contentious issue. All businesses understand their importance in measuring exceptional customer service, but each metric has its strengths and weaknesses. And much like sports, each has a devoted fan base that is hard to shake from their existing beliefs. This blog will help you better understand which customer service metrics are the right fit to help you gauge performance, identify areas for improvement, and ultimately enhance the customer experience. We’ll also take a look at the pros and cons of each, as well as which industries where they’re most relevant.


Understanding the Role of Customer Service Metrics

You can’t improve the customer service metrics that you don’t measure

Before we debate the top customer service metrics, it’s crucial to understand their significance. Metrics not only act as the compass guiding businesses toward a customer-centric approach, they also gauge how well the organization is progressing toward that goal. By quantifying various aspects of the customer experience, companies can make informed decisions, optimize processes, and build strategies that resonate with their customer base. 


Top Customer Service Metrics: A Deep Dive

1. Customer Satisfaction Score (CSAT)

What is CSAT? CSAT is a metric that measures the overall satisfaction of customers with a company’s product or service. Typically collected through surveys, customers are asked to rate their satisfaction on a scale, often ranging from 1 to 5.

CSAT Pros:

  • Simplicity: CSAT is straightforward and easy to understand, making it accessible to both customers and employees.
  • Real-time feedback: It provides immediate insights into customer sentiment, allowing for timely adjustments.
  • Benchmarking: CSAT scores can be compared across different time periods to gauge improvements.

CSAT Cons:

  • Lack of depth: CSAT might not provide detailed insights into specific aspects of the customer experience.
  • Subjectivity: Interpretation can vary as satisfaction is a subjective measure. 
  • Low participation rate: Customers tend to respond to surveys when they are very pleased or displeased. As a result, survey participation has historically been low (anywhere from 5% to 33%).

Industries that use CSAT:

  • Retail: CSAT is widely used in retail to gauge customer satisfaction with purchases and overall shopping experience. One of the reasons is its simplicity and how familiar consumers are with the concept.
  • Hospitality: Hotels and restaurants also leverage CSAT to evaluate guest satisfaction with their stay or dining experience for much the same reasons as Retail.
2. Net Promoter Score (NPS)

What is NPS? Net Promoter Score measures the likelihood of customers recommending a company’s product or service to others. Customers are asked to rate this likelihood on a scale from 0 to 10. One advantage of NPS, at least in theory, is that it removes temporary factors, such as a recent bad experience, to gauge whether the customer would recommend the brand, as in the overall experience of the brand. 

NPS Pros:

  • Loyalty predictor: NPS is often seen as a predictor of customer loyalty and business growth.
  • Simplicity: Like CSAT, NPS is easy to administer and understand.
  • Benchmarking: NPS allows for benchmarking against industry standards since it is widely used.

NPS Cons:

  • Limited context: NPS alone may not provide sufficient context to address specific issues, especially for long-time customers. It also suffers from the same low participation rate issues as CSAT.
  • Cultural bias: Cultural variations can impact the interpretation of NPS scores.
  • Misunderstanding of NPS as CSAT: The nuance of NPS as an overall experience metric is often lost on consumers, who regard it the same way as CSAT. 

Industries that use NPS:

  • Technology: Many tech companies use NPS to measure customer loyalty and satisfaction with software or services.
  • Telecommunications: Commonly used to assess customer satisfaction in the telecom industry.
3. First Response Time (FRT)

What is FRT? First Response Time measures exactly what the name describes – the time it takes for a customer service representative to respond to a customer query or issue from the moment it is received. One important note is that this metric will vary by channel, as will customer expectations of FRT (e.g. FRT over email can be multiples longer than chat or voice). 

FRT Pros:

  • Customer engagement: Fast responses can contribute to positive customer experiences and satisfaction.
  • Simplicity: This metric doesn’t take any complex computation or require customer input. It’s also universal across any contact center, CCaaS, or customer experience platform.
  • Efficiency: FRT can be a key indicator of how efficiently a support team operates.
  • Problem resolution: Quick responses often lead to faster problem resolution.

FRT Cons:

  • Quality trade-off: Emphasizing speed may sometimes compromise the quality of responses. For example, an agent may cut short conversations to improve FRT at the expense of fully resolving the issue or offering additional products and services.
  • Incomplete picture: FRT alone does not capture the overall resolution time, or really whether the issue was properly resolved.

Industries that use FRT:

  • E-commerce: Crucial in online retail where customers expect prompt assistance with order-related queries. The scale needed to address retail and eCommerce customers makes this efficiency metric insightful.
  • Financial Services: Banking and financial institutions use FRT to enhance customer support for transactions and account inquiries. Like retail, metrics that impact scalability are important with a large customer base. 
4. Average Resolution Time (ART)

What is ART? Average Resolution Time measures the average time it takes to resolve a customer query or issue from the moment it is received. This may vary depending on the complexity of issues and across industries.

ART Pros:

  • Comprehensive: ART provides a holistic view of the time taken to resolve customer issues. It’s not subjective and can easily be benchmarked across channels and industries.
  • Quality focus: Emphasizes the importance of delivering thorough and effective solutions.
  • Root cause analysis: Longer resolution times can prompt investigation into systemic issues.

ART Cons:

  • May not reflect urgency: Some issues require more time due to complexity, and a longer resolution time does not necessarily indicate poor service. In fact, higher ART may result in fewer repeat calls or inquiries by the customer.
  • Customer frustration: Prolonged resolution times can lead to customer dissatisfaction, but shorter times may not adequately resolve the issue.

Industries that use ART:

  • Healthcare: Crucial in healthcare settings where resolving patient inquiries promptly is essential.
  • IT Services: Companies offering technical support use ART to measure the efficiency of problem resolution.
5. Customer Effort Score (CES)

What is CES? Customer Effort Score measures the ease with which customers can resolve their issues or complete a task. Customers are typically asked to rate the effort required on a scale.

CES Pros:

  • Focus on ease: CES emphasizes the importance of providing a seamless customer experience.
  • Can predict loyalty: Lower effort scores can be correlated with increased customer loyalty.
  • Actionable: Identifies pain points that need improvement.

CES Cons:

  • Limited context: CES may not capture the full spectrum of customer emotions, since it may be very easy to resolve a task, but the customer can still find the inquiry unnecessary (e.g. the product should just do that instead of making me create an inquiry).
  • Interpretation challenges: The perception effort can vary among customers due to factors such as familiarity, technical prowess, and more.

Industries that use CES:

  • SaaS (Software as a Service): Frequently used in the SaaS industry to gauge how easily customers can navigate and use software platforms.
  • Utilities: Companies providing utility services use CES to measure the ease of bill payment and issue resolution.
6. Customer Sentiment

What is Customer Sentiment? Customer Sentiment provides an understanding of how the customer is reacting emotionally by analyzing the customer interaction. This can be used in live agent-customer interactions as well as after the fact as a means of agent performance review and issue identification.

Customer Sentiment Pros:

  • Works without customer feedback: By using the conversation itself, sentiment does not require a survey or other customer input, making the participation rate higher than other metrics. 
  • Can be used in the moment: Unlike after-the-fact metrics and surveys, sentiment can be derived in live conversations, so agents can adjust their talk track and resolution plans based on customer emotion.
  • Tracks conversation dynamically: Sentiment can also change during conversations, so this can be a better gauge of agent performance (e.g. taking a low sentiment conversation and increasing it, or vice versa).

Customer Sentiment Cons:

  • Sentiment direction: Many sentiment models do not account for directionality, i.e. is the customer’s sentiment toward the agent or the company, product, policy, etc. (In Loris’ research, more than 80% of customer sentiment is directed toward companies). 
  • Limited context: As a standalone metric, sentiment is limited to customer emotion, without providing enough information about interaction quality. In addition, many conversations lack significant sentiment.

Industries that use Customer Sentiment:

  • Retail/E-commerce: Sentiment is helpful to understand customer frustration, both to pinpoint which elements of the customer experience are causing the biggest issues and to assist agents in offering discounts or other remediation when customers are upset.
  • Telecommunications: Similarly to retail, telecom benefits from knowing where to spot elements of friction in the customer journey.
7. Conversational Quality (CQ) Score

What is CQ? Conversational Quality score is a metric that evaluates the customer’s perspective of their interaction. It takes into account the agent’s conversation management skills as well as factors beyond the agent’s control, such as company policies and products. The goal of CQ is to determine whether the customer feels that their issue has been resolved, and that they have been treated fairly and taken care of.

CQ Pros:

  • Works without customer feedback: Like sentiment, CQ uses the conversation itself as the input, without relying on a survey or active customer participation. This means it can score 100% of interactions.
  • Provides multifaceted assessment: CQ may be tied to individual conversations, but can be aggregated at the agent, team, and organization level. 
  • Objective and highly accurate: Since there is no human input to create a CQ beside the actual customer-agent interactions, the score itself is objective, serving as a benchmark across the CX organization. In addition, the high participation rate (from running on all conversations) makes the score more accurate than other metrics.

CQ Cons:

  • Limited to customer interactions: CQ runs on customer interactions, so organizations with smaller volumes of conversations may take longer to derive insight. 

Industries that use CQ:

  • Customer-experience focused industries: Organizations that prioritize CX, especially those with subscription models and recurring customer purchase activity, find CQ useful as a means to continuously improve. 


The Holistic Approach: Right Mix of Metrics

While each metric provides valuable insights, there are advantages and disadvantages to each. Rather than relying on a single metric, successful organizations often adopt a holistic approach, combining multiple metrics to create a comprehensive view of their customer service performance. 

This is especially important for metrics with low participation rates, since they can skew towards very satisfied and very dissatisfied customers. By balancing customer-provided metrics (e.g. CSAT, NPS, CES), efficiency-focused metrics (AHT, FRT), and automatically-generated metrics (e.g. Sentiment, CQ), organizations can triangulate which issues to focus on first. This can serve as a check to measure how accurate an organization’s understanding of customer feedback is, as well as spot any elements of bias in customer experience surveys. These automatically created metrics also highlight emerging issues before they are reported by customers.

In the end, it’s not just about the numbers. The right metrics should give your CX team insights they can act on – whether that’s an area an agent needs to improve or recurring points of friction in your customer journey. 

Image by Gino Crescoli 

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