The best examples of customer service performance metrics examples for modern teams

Practical examples of customer service performance metrics examples you can actually use

Let’s skip the theory and go straight to the examples of customer service performance metrics examples that show up on real scorecards. The trick is balancing speed, quality, and business impact so you don’t reward agents for rushing through conversations or cherry-picking easy tickets.

Below are core metrics used by support leaders at SaaS companies, banks, healthcare providers, and retail organizations in 2024–2025.

Response and resolution: time-based examples of customer service performance metrics

Time-based metrics are usually the first example of customer service performance measurement leaders adopt, because they’re easy to track and explain.

First Response Time (FRT)

What it measures: How long customers wait for the first human or automated reply after contacting support.

Why it matters: Research from Salesforce and other industry reports consistently shows that customers now expect near-real-time acknowledgment, especially on chat and social channels. Long FRT is one of the fastest ways to tank satisfaction scores.

How to use it in performance reviews:

• For live chat, many teams in 2024 target an average FRT of 30–60 seconds.
• For email or web forms, 4 business hours is a realistic benchmark for many B2B teams.
• In reviews, you might say: “Your average first response time is 2.5 hours against a team goal of 1 hour. Let’s adjust your queue management so you prioritize new contacts sooner.”

Real example: A mid-sized fintech support team reduced FRT on chat from 90 seconds to 40 seconds after adding an AI triage bot and rebalancing shifts. Their CSAT on chat improved from 4.3 to 4.6 out of 5 over one quarter.

Average Handle Time (AHT)

What it measures: Total talk/chat time plus after-contact work, divided by the number of contacts.

Why it matters: AHT is a classic example of a call center metric that can be misused. When it’s the only number agents are judged on, quality suffers. Used correctly, it highlights training gaps and process friction.

How to use it in performance reviews:

• Compare AHT by issue type, not just by agent. Complex billing tickets should take longer than password resets.
• Pair AHT with quality metrics. An agent with slightly higher AHT but excellent quality and high CSAT might be modeling the behavior you want.

Real example: A healthcare insurer found that agents handling claims calls had AHT 40% higher than average. Instead of penalizing them, the team simplified internal tools and knowledge articles. AHT dropped by 18%, and internal QA scores went up.

First Contact Resolution (FCR)

What it measures: Percentage of issues resolved in a single interaction, without the customer needing to follow up.

Why it matters: FCR is one of the best examples of customer service performance metrics examples that connect directly to customer effort and loyalty. Higher FCR usually means fewer frustrated repeat contacts and lower operational costs.

How to use it in performance reviews:

• Track FCR per agent and per issue type.
• Use it to identify where agents need more authority (for example, the ability to issue small credits) or better training.

Real example: A subscription software company raised FCR from 68% to 79% by giving front-line agents pre-approved refund limits and clearer troubleshooting flows. Repeat contacts dropped by 22% in three months.

Quality-focused examples of customer service performance metrics examples

Speed without quality is a fast path to churn. Quality metrics give you a real example of how well agents solve problems, communicate, and follow policy.

Customer Satisfaction Score (CSAT)

What it measures: Customers’ rating of a specific interaction, often on a 1–5 or 1–10 scale.

Why it matters: CSAT is one of the most widely used examples of customer service performance metrics examples because it’s easy to understand and tie to individual interactions.

How to use it in performance reviews:

• Look at CSAT volume as well as average. Ten perfect scores on a tiny sample don’t tell you much.
• Combine CSAT with qualitative feedback. Use comments in coaching sessions.

Real example: A large online retailer noticed that one agent’s CSAT was 0.3 points below the team average on returns-related contacts. Call reviews showed the agent was strictly following policy but sounded inflexible. After coaching on empathy phrases and solution framing, their CSAT on those contacts rose by 0.5 points in one quarter.

For broader context, research on patient satisfaction and communication from organizations like Mayo Clinic shows similar patterns: respectful, clear communication drives higher satisfaction even when outcomes are constrained.

Net Promoter Score (NPS)

What it measures: Customers’ likelihood to recommend your company, usually on a 0–10 scale.

Why it matters: NPS is more of a relationship metric than a pure service metric, but support experiences have a big impact on it. It’s a useful example of customer service performance metrics examples when you want to show leadership how service contributes to loyalty.

How to use it in performance reviews:

• Use NPS more at team or function level than at individual level.
• Discuss how service initiatives (like faster responses or better training) are influencing promoter vs. detractor trends.

Real example: A B2B SaaS company saw NPS improve from 24 to 36 after investing in a dedicated onboarding support team. Support leaders used that data to justify further headcount and training budgets.

Quality Assurance (QA) or Interaction Quality Score

What it measures: Internal reviewers score a sample of interactions against a rubric (accuracy, tone, policy adherence, documentation, etc.).

Why it matters: QA is often the most detailed example of a customer service performance metric because it captures nuance that raw numbers miss.

How to use it in performance reviews:

• Share specific call or ticket examples with agents.
• Focus on patterns, not one-off misses.
• Tie QA criteria directly to your training materials.

Real example: A bank’s support QA program flagged that agents were skipping mandatory disclosures in 7% of calls. After targeted coaching and a script update, this fell below 1%, reducing regulatory risk — something regulators like the Consumer Financial Protection Bureau care about deeply.

Customer effort and experience: modern examples include CES and repeat contacts

In 2024–2025, a lot of organizations are shifting from “How happy are you?” to “How hard was that?” This shift shows up in newer examples of customer service performance metrics examples.

Customer Effort Score (CES)

What it measures: How easy or difficult it was for the customer to resolve their issue, usually on a 1–7 scale.

Why it matters: Research summarized by Harvard Business Review has shown that reducing customer effort can be a better predictor of loyalty than delighting customers with over-the-top experiences. Effort is a powerful example of a metric that blends process design and agent performance.

How to use it in performance reviews:

• Identify journeys with high effort (for example, identity verification or claims submission) and support agents through better tools.
• Coach agents on proactive guidance: sending helpful links, summarizing next steps, and clarifying timelines.

Real example: A telecom provider introduced CES on post-chat surveys and found that password reset flows had low effort, but billing disputes were painful. By redesigning the billing portal and giving agents clearer guidelines, CES improved by 23% on those contacts in six months.

Repeat Contact Rate

What it measures: The percentage of customers who need to contact support again about the same issue within a defined time window (for example, 7 days).

Why it matters: This metric is a practical example of how to quantify customer effort and long-term resolution quality.

How to use it in performance reviews:

• Look at repeat contact patterns by agent and by issue type.
• Use it alongside FCR and QA to see whether agents are solving root causes or just patching symptoms.

Real example: A health-tech company noticed that one workflow change caused repeat contacts on lab results to spike from 9% to 18%. Analysis showed that the new emails were unclear. After rewriting the templates and adding a FAQ link, repeat contacts fell back under 10%. For reference, organizations like the National Institutes of Health emphasize clear communication in health contexts for similar reasons: fewer misunderstandings and better outcomes.

Productivity and capacity: examples of metrics that protect your team

Leaders often lean heavily on productivity-based examples of customer service performance metrics examples because they’re easy to chart. Used thoughtfully, they can protect teams from burnout and help make the case for more headcount.

Contacts Handled per Hour / per Day

What it measures: Volume of interactions an agent handles in a given time period.

Why it matters: It’s a straightforward example of a throughput metric. The risk is turning it into a quota that encourages rushed, low-quality work.

How to use it in performance reviews:

• Normalize by channel and complexity. Ten phone calls are not the same as ten quick chats.
• Use it to identify outliers who might need support: very low volume could signal knowledge gaps; very high volume with low CSAT might indicate cutting corners.

Real example: A retail contact center used contacts-per-hour data to show leadership that ticket volume had grown 35% year-over-year while staffing had only grown 10%. That data helped justify adding weekend coverage and cross-training staff from other departments during peak seasons.

Adherence to Schedule and Occupancy

What they measure:

• Adherence: How closely an agent follows their planned schedule (log-in times, breaks, etc.).
• Occupancy: Percentage of logged-in time spent actively handling contacts.

Why they matter: These are common examples of customer service performance metrics examples in larger operations where workforce management is a priority.

How to use them in performance reviews:

• Focus on patterns over time, not one-off late logins.
• Use occupancy to flag overload. Consistently high occupancy (for example, 85–90%+) can be a red flag for burnout and mistakes.

Real example: A health insurance contact center saw error rates climb when occupancy exceeded 88%. They used this data to adjust staffing models, aligning with broader occupational stress research highlighted by agencies like the CDC. Error rates and sick days both dropped after the change.

Coaching and performance review: combining multiple examples of customer service performance metrics examples

No single metric can carry a performance review. The most effective leaders use a portfolio of metrics — a mix of time, quality, effort, and productivity — plus qualitative feedback.

Here’s how that looks in practice when you’re using several examples of customer service performance metrics examples together.

Example: Performance snapshot for an individual agent

Imagine you’re reviewing quarterly performance for an agent named Jordan. Their dashboard shows:

• First Response Time: 20% faster than team average on email
• Average Handle Time: 15% higher than team average
• CSAT: 4.8/5 on 300+ surveys
• QA Score: 92% (team target: 90%)
• FCR: 81% (team average: 78%)
• Contacts per Day: Slightly below team average

In your performance review, you might say:

“Your customers clearly appreciate the time you take with them — your CSAT and QA scores are excellent, and your FCR is strong. Your handle time is higher than average, which is fine as long as we keep quality and volume balanced. Let’s look at two or three common workflows where we can streamline your process so you can help more customers without sacrificing quality.”

This is a realistic example of how to use multiple metrics to guide coaching rather than punish variance.

Example: Team-level dashboard for leadership

At the team level, you might combine:

• FRT and AHT by channel
• CSAT and CES by journey
• NPS at the business level
• FCR and repeat contact rate
• Contacts per agent and occupancy

When your VP asks for an update, you’re not just listing numbers — you’re telling a story:

• “We cut FRT on chat by 35% this quarter by adding AI triage and shifting staffing.”
• “CES improved on our billing journey after we simplified the process.”
• “FCR is up 6 points, which correlates with a 12% drop in repeat contacts. That’s saving us roughly X hours per month.”

These are the kinds of best examples of data-backed narratives that secure budget and headcount.

2024–2025 trends shaping new examples of customer service performance metrics examples

Customer service in 2024–2025 is not just phone and email. AI assistants, self-service portals, and omnichannel expectations are changing which metrics matter.

AI and automation metrics

As more teams roll out AI chatbots and agent-assist tools, new examples of customer service performance metrics examples are appearing:

• Bot Containment Rate: Percentage of contacts fully resolved by automation without human escalation.
• Deflection to Self-Service: How many customers successfully use help center content instead of contacting support.
• AI-Assisted Handle Time: Comparison of AHT on tickets where agents used AI suggestions versus those where they did not.

These metrics shouldn’t replace human performance metrics, but they’re helpful examples of how to measure the impact of your tech stack.

Omnichannel consistency

Customers move between channels — web, chat, phone, social — and they expect consistency. Forward-looking teams track metrics by channel and compare:

• CSAT by channel
• FRT by channel
• Escalation rate from self-service or bots to humans

Real-world examples include:

• A retailer seeing strong CSAT on phone support but weak scores on social media responses, prompting them to train a dedicated social support team.
• A SaaS company using channel-specific FRT goals (for example, 30 seconds on chat, 60 minutes on email) rather than a one-size-fits-all target.

FAQ: common questions about examples of customer service performance metrics examples

What are some simple examples of customer service performance metrics for small teams?

For a small team just starting with data, practical examples of customer service performance metrics examples include:

• First Response Time on your main channel
• Customer Satisfaction Score (CSAT) after each resolved ticket
• First Contact Resolution (FCR)

These three give you visibility into speed, quality, and effectiveness without overwhelming you with data.

Which example of customer service performance metric is best for performance reviews?

There isn’t a single “best” metric. For individual performance reviews, a balanced mix works better than any one example of customer service performance metric. Many managers rely on:

• QA scores and CSAT for quality
• FRT and AHT for efficiency
• FCR or repeat contact rate for effectiveness

Then they layer in qualitative feedback from peers and customers.

How often should I update my customer service performance metrics examples and targets?

Most teams review targets at least annually, and often quarterly, especially when:

• Ticket volume or channel mix changes
• You launch new products or services
• You add AI or automation that changes workflows

As you gather more data, you’ll refine which examples of customer service performance metrics examples actually correlate with better customer outcomes and which ones are just noise.

Are there industry benchmarks for these metrics?

There are high-level benchmarks from industry reports and research firms, but they vary widely by sector and complexity. Healthcare, finance, and government services, for example, often have longer handle times due to regulation and verification requirements. When in doubt, benchmark against your own historical performance and use external data as directional guidance rather than a hard standard.

The bottom line: the best examples of customer service performance metrics examples are the ones that reflect your real customer journeys, support your agents’ growth, and help you tell a clear story about how service protects and grows the business. Start with a small, meaningful set of metrics, tie them directly to behaviors you can coach, and evolve them as your team and technology mature.