Unlocking success: Customer service metrics you should track
Customer service metrics act like a compass for businesses of all sizes. They point out strengths, expose weaknesses, and provide the actionable insight you need to decide where to tweak or invest.
Below you’ll find why tracking key customer service metrics matters, followed by clear, step by step guidance and concise examples you can use immediately.
Why should you measure key performance metrics for customer service?
1. Improve customer satisfaction
The main reason to track customer service metrics is to identify what satisfies your audience. Our 2024 Customer Service Trends Report shows a steady rise in customer expectations, with 68% of support teams reporting AI’s impact on core metrics such as response times.
Measuring these indicators helps organisations adapt to changing customer needs, streamline service processes, and raise overall satisfaction. Staying focused on customer-centred metrics lets teams act before small issues grow, refine operations, and deliver a more responsive, personalised experience that builds loyalty.
"A service mindset across teams is often the difference between a decent support experience and a great one."
2. Identify areas for improvement
Klaus’ 2023 Customer Service Quality Benchmark found that 30% of service professionals struggle with measuring and improving support quality. By analysing service metrics, teams can pinpoint process pain points and apply targeted, data driven fixes.
3. Optimise resource allocation
If you’ve ever wished you could spend time, budget, or staff more wisely, metrics give you that clarity. With the right data you can make informed choices to boost impact, redesign workflows, or reassign priorities.
4. Meet SLAs
A service level agreement (SLA) is the promise you make to customers about what they can expect, such as response or delivery times.
Monitoring metrics shows whether you meet those expectations or are falling short. Either way, you get a clear picture of where to focus improvement efforts.
Tip: Moving to an automated ticketing system can reduce manual work and improve SLA compliance.
Customer service metrics you should track
1. First Response Time (FRT)
Why it matters
First Response Time measures how quickly a support agent replies to a customer inquiry. Keep this as low as possible.
What it's good for: Reveals how promptly customer concerns are addressed, which influences satisfaction.
Formula:
FRT = Total first response time for all tickets received ÷ Total number of interactions
Example:
If a support team receives 100 queries and the total time taken to respond to all of them is 500 minutes, FRT = 500 ÷ 100 = 5 minutes per query.
2. First Contact Resolution (FCR)
Why it matters
First Contact Resolution Rate measures the share of queries resolved during the initial interaction.
What it's good for: Shows whether agents resolve issues efficiently at first contact.
Formula:
FCR (%) = Number of issues resolved in the first contact ÷ Total number of issues × 100
Example:
If 80 issues are resolved on first contact out of 100 total, FCR = (80 ÷ 100) × 100 = 80%.
3. Average Resolution Time (ART)
Why it matters
Average Resolution Time calculates how long, on average, agents take to handle and close interactions.
What it's good for: Highlights team efficiency in processing and solving tickets.
Formula:
ART = Total handle time for all tickets solved ÷ Total number of interactions
Example:
If a team spends 600 minutes resolving 30 tickets, ART = 600 ÷ 30 = 20 minutes per ticket.
4. Customer Satisfaction (CSAT)
Why it matters
CSAT gauges how happy customers are, typically via a short 1–5 survey. CSAT is the percentage of responses rated 4 or 5.
What it's good for: Highlights strengths and areas for improvement through direct feedback.
Formula:
CSAT (%) = Number of satisfied customers (ratings 4 or 5) ÷ Total responses × 100
Example:
80 out of 100 respondents rate 4 or 5 → CSAT = 80%.
5. Net Promoter Score (NPS)
Why it matters
NPS measures how likely customers are to recommend your product or service. Responses are grouped as detractors, passives, or promoters.
What it's good for: Gauges long term loyalty and word of mouth.
Formula:
NPS = % promoters - % detractors
Example:
40% promoters and 20% detractors → NPS = 20.
6. Open tickets
Why it matters
Open tickets show how many unresolved issues are active and awaiting attention.
What they're good for: Help assess workload and prioritise tasks.
Formula:
Open tickets = number of unresolved tickets
Example:
System shows 50 unresolved issues → open tickets = 50.
If you want to stop requests slipping through the cracks and speed up fixes, read: How ticketing systems are evolving for next generation support.
7. Customer Effort Score (CES)
Why it matters
CES measures how easy it is for customers to reach a goal (getting an answer, tracking an order). Easier interactions tend to yield higher satisfaction.
What it's good for: Gauging the ease of customer interactions.
Formula (common approach):
CES (%) = (Number of favourable responses ÷ Total responses) × 100
Example:
200 responses, 150 favourable → CES = (150 ÷ 200) × 100 = 75%.
Are there specific SaaS customer service metrics?
Yes. Subscription and usage patterns make some KPIs especially important for SaaS businesses. These are the most useful ones to track closely.
1. Customer onboarding completion rate
Formula:
Onboarding Completion Rate (%) = (Number of customers successfully onboarded ÷ Total new customers) × 100
How to interpret:
High completion = more customers move from sign up to active use. Low completion = friction during onboarding.
2. Feature adoption rate
Formula:
Feature Adoption Rate (%) = (Number of customers using the feature ÷ Total new customers) × 100
How to interpret:
High adoption indicates value. Low adoption suggests awareness, usability, or promotion issues.
3. Churn rate
Formula:
Churn Rate (%) = (Number of customers lost during a period ÷ Total customers at the beginning of the period) × 100
How to interpret:
High churn is a warning. Low churn shows healthy retention. Watch for seasonal fluctuations.
4. Customer lifetime value (CLTV)
Formula:
CLTV = average revenue per user × customer lifespan
How to interpret:
High CLTV means customers provide strong long term value. Low CLTV calls for a review of retention and monetisation.
5. Monthly Recurring Revenue (MRR)
Formula:
MRR = sum of monthly subscription fees
How to interpret:
Steady or growing MRR signals healthy acquisition and retention. Declines can indicate downgrades or cancellations.
6. Product uptime and reliability
Formulas:
Uptime percentage (%) = (total uptime ÷ total time) × 100
Reliability = number of successful operations ÷ total number of operations
How to interpret:
Uptime close to 100% is vital for trust. Low uptime harms satisfaction and reputation.
Keep track of your customer service metrics with CustoQ
That's really it. Knowing which metrics to track is valuable. Having a tool that automates gathering and surfacing those metrics saves time and frees your team for higher value work.
With CustoQ you can:
- Deploy an embeddable AI assistant that crawls your documentation and pages and delivers concise, conversion-focused answers.
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- Get set up quickly and tune the assistant with minimal effort.
- Track usage and identify gaps in your help content so you can prioritise improvements.
Ready to test it? Try CustoQ’s quick install and see how much time the assistant can save your team.
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