Customer Service Metrics Calculator

Plug in your real numbers. See where you stand against industry benchmarks. No signup required.

Benchmarks vary by industry and team size. Use these as a starting point, not gospel.

Your Numbers

All conversations: chat, email, phone, social

Tickets closed without followup or escalation

Time from customer message to first agent reply

Time from ticket open to ticket closed

Positive ratings

Total responses

Total spend: salaries + tools + overhead

Your Scorecard

First Contact Resolution (FCR)

% of tickets resolved without followup

70%
Poor <60%Good 70-79%Great >80%

Good - right around average

First Response Time (FRT)

How fast you reply to customers

5m
Great <2mGood 2-5mSlow >10m

Good - right around average

Customer Satisfaction (CSAT)

% of customers who rated you positively

80%
Poor <70%Good 75-85%Great >90%

Good - right around average

Avg Resolution Time

How long to fully resolve a ticket

45m

Good - right around average

Cost Per Ticket

Total support spend / total tickets

$10.00

Industry average: $2-$15 depending on channel and complexity.

What If You Added AI?

Rough estimates based on your numbers. Not promises.

First Response Time
5m → <30s
AI responds instantly to common questions
Tickets Automated
~150/mo
20-40% of simple, repetitive tickets
Estimated Monthly Savings
$1,500
Based on 30% automation at your cost per ticket

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How These Metrics Are Calculated

First Contact Resolution (FCR)

FCR = (Resolved First Contact / Total Tickets) × 100

Measures what percentage of issues get solved without the customer having to reach out again. Higher is better. If yours is below 60%, you likely have a knowledge gap or routing problem.

Customer Satisfaction (CSAT)

CSAT = (Positive Ratings / Total Responses) × 100

The most direct measure of customer happiness. Usually collected via post-interaction survey. Response bias is real - unhappy people are more likely to respond, so 80%+ is actually strong.

Cost Per Ticket

CPT = Total Monthly Support Cost / Total Tickets

Your all-in cost to handle one customer interaction. Include salaries, tools, and overhead. If you're above $15/ticket, automation could save you real money.

First Response Time (FRT)

FRT = Average time from customer message to first reply

Customers care more about acknowledgment speed than resolution speed. Under 2 minutes for live chat, under 1 hour for email. AI can bring this to near-zero for handled queries.

What This Calculator Doesn't Tell You

  • Channel differences: Live chat FRT of 5 minutes is bad. Email FRT of 5 minutes is amazing. Context matters.
  • Ticket complexity: A 70% FCR on simple password resets is terrible. 70% FCR on complex integrations is decent.
  • Customer effort: You can have 90% CSAT and still lose customers if they had to jump through hoops.
  • Volume trends: One month of data isn't a trend. Track these weekly for at least 3 months.
  • Team size: A 2-person team with 45-minute resolution times has a very different problem than a 20-person team with the same number.

Common Questions

What's a good First Contact Resolution rate?

70-75% is average across industries. 80%+ is strong. If you're below 60%, look at your knowledge base coverage and agent training first. Common fixes: better internal documentation, smarter ticket routing, and giving agents authority to resolve without escalation.

What CSAT score should I target?

75-85% is typical for B2B SaaS. E-commerce tends to be lower (60-75%) because shipping complaints drag it down. Don't obsess over the absolute number - track the trend. A CSAT dropping from 82% to 76% over 3 months is a bigger red flag than a steady 74%.

How do I lower my cost per ticket?

Three approaches: automate simple tickets (AI chatbots handle password resets, FAQs), improve self-service (better knowledge base so customers don't need to contact you), or increase agent efficiency (templates, macros, better tools). Don't cut agent headcount and expect quality to stay the same.

What's the most important metric to track?

Depends on your stage. Early-stage startup? Focus on CSAT and FCR - make sure customers are happy and problems get solved. Scaling team? Add FRT and cost per ticket to find efficiency gaps. The metric that matters most is the one that's hurting your business right now.

Can AI really improve these metrics?

For the right tickets, yes. AI drops FRT to near-zero on handled queries, which pulls down your average. It improves FCR on simple questions because it has instant access to your knowledge base. But it won't help with complex troubleshooting or angry customers who want a human. The honest answer: AI improves your numbers on easy tickets so your team can spend more time on hard ones.