Customer Support Metrics
Metrics for measuring support team performance and customer service quality.
Benchmark context: B2B SaaS companies typically spend ~8% of ARR on support and success combined.
Volume Metrics
Ticket Volume
Definition: Total number of support tickets received in a period.
Formula:
Ticket Volume = Count of tickets created in period
Track by channel: email, chat, phone, self-service.
What it tells you: Support demand. Trend matters more than absolute number.
Tickets per Customer
Definition: Average tickets created per active customer.
Formula:
Tickets per Customer = Total tickets / Active customers
Benchmarks:
- Below 0.5/month: Low touch, efficient product
- 0.5-1.0/month: Typical
- Above 1.0/month: High touch, may indicate product issues
What it tells you: Support burden relative to customer base. Rising ratio signals product or onboarding issues.
Ticket Backlog
Definition: Number of open tickets awaiting resolution.
Formula:
Backlog = Count of open tickets
What it tells you: Current support debt. Should be stable or declining.
Ticket Distribution by Type
Definition: Breakdown of tickets by category.
Categories (typical):
- How-to / Usage questions
- Bug reports
- Feature requests
- Billing inquiries
- Account issues
- Outage/incident related
What it tells you: What’s driving support volume. High “how-to” suggests onboarding or documentation gaps.
Response Metrics
First Response Time (FRT)
Definition: Time from ticket creation to first human response.
Formula:
FRT = Median of (First response timestamp - Ticket created timestamp)
Use median, not average (outliers skew averages).
Benchmarks:
| Channel | Target | Reality |
|---|---|---|
| Chat | < 1 minute | Best channel for speed |
| Email (B2B) | 4-6 hours | Industry average is 12+ hours |
| Email (Enterprise) | < 1 hour | Premium SLA expected |
| Phone | < 30 seconds (80% within 20 sec) | “80/20 rule” standard |
Customer expectations: 52% expect email responses within 1 hour, 32% within 30 minutes.
What it tells you: How quickly customers get acknowledged. Impacts satisfaction.
Sources:
First Response SLA Adherence
Definition: Percentage of tickets meeting FRT SLA target.
Formula:
FRT SLA Adherence = Tickets meeting FRT target / Total tickets × 100
Target: >95%
Resolution Metrics
Resolution Time (Time to Resolution)
Definition: Time from ticket creation to final resolution.
Formula:
Resolution Time = Median of (Resolution timestamp - Ticket created timestamp)
Benchmarks:
- Simple issues: < 4 hours
- Moderate issues: < 24 hours
- Complex issues: < 72 hours
What it tells you: How quickly problems are actually solved.
First Contact Resolution (FCR)
Definition: Percentage of tickets resolved in a single interaction.
Formula:
FCR = Tickets resolved without reopening or follow-up / Total tickets × 100
Benchmarks:
- Below 60%: Low, investigate agent training or issue complexity
- 60-70%: Below average
- 70%: Industry average (SQM Group 2024 data)
- 70-80%: Good, competitive for SaaS
- 80%+: World-class
Industry variation: Retail/simple products achieve 73-75%. Complex tech support often 50-65%.
Impact: FCR improvements reduce churn by up to 67% (research shows it’s the #1 support driver of retention).
What it tells you: Support efficiency and agent capability.
Sources:
Resolution SLA Adherence
Definition: Percentage of tickets resolved within SLA timeframe.
Formula:
Resolution SLA Adherence = Tickets meeting resolution target / Total tickets × 100
Target: >90%
Reopen Rate
Definition: Percentage of resolved tickets that are reopened.
Formula:
Reopen Rate = Tickets reopened / Tickets resolved × 100
Benchmarks:
- Below 5%: Good
- 5-10%: Acceptable
- Above 10%: Investigate resolution quality
What it tells you: Resolution quality. High reopen rate means problems aren’t actually being solved.
Quality Metrics
Customer Satisfaction Score (CSAT)
Definition: Customer rating of support interaction.
Formula:
CSAT = Positive responses / Total responses × 100
Typically 5-point or 3-point scale. “Positive” = top 1-2 ratings.
Benchmarks:
- Below 70%: Poor, requires immediate attention
- 70-80%: Below average (B2B SaaS average is ~68-78%)
- 80-90%: Good
- 90%+: Excellent
- 95%+: World-class
By channel:
- Live chat: 87% average (highest)
- Email: 61% average
- Phone: 44% average
Segment variation: Enterprise customers typically rate 72-75% (dedicated support), SMB customers 60-65%.
What it tells you: Customer perception of support quality.
Common mistakes:
- Low response rates (<10% makes data unreliable)
- Survey fatigue
- Not following up on negative feedback
Sources:
Customer Effort Score (CES)
Definition: How easy it was for the customer to get help.
Formula:
CES = Average rating on "How easy was it to resolve your issue?" (1-7 scale)
Or as percentage (when using agree/disagree scale):
CES % = Respondents who agree it was easy / Total respondents × 100
Benchmarks (1-7 scale):
- Below 4: High effort, frustrating
- 4-5: Moderate
- 5-6: Good
- Above 6: Easy, effortless
Benchmarks (percentage):
- Below 70%: Needs improvement (per Gartner)
- 70-90%: Good
- Above 90%: Excellent, strong position
Why CES matters: CES is 1.8x more effective than CSAT at predicting customer loyalty. Reducing friction drives repeat business more than satisfaction.
What it tells you: Support friction. Lower effort correlates with retention.
Sources:
Escalation Rate
Definition: Percentage of tickets escalated to higher tier or engineering.
Formula:
Escalation Rate = Escalated tickets / Total tickets × 100
Benchmarks:
- Below 5%: Well-handled at Tier 1
- 5-15%: Normal
- Above 15%: May indicate training gaps or product issues
What it tells you: Issue complexity and Tier 1 capability.
Efficiency Metrics
Tickets per Agent
Definition: Average tickets handled per support agent.
Formula:
Tickets per Agent = Total tickets handled / Number of agents
Benchmarks:
- Chat: 300-500/month
- Email: 400-600/month
- Phone: 200-400/month
What it tells you: Agent productivity and capacity planning.
Cost per Ticket
Definition: Total support cost divided by tickets handled.
Formula:
Cost per Ticket = Total support team cost / Total tickets resolved
Benchmarks:
- Chat: $3-8
- Email: $5-15
- Phone: $10-25
What it tells you: Support efficiency. Target: decrease over time.
Self-Service Rate (Ticket Deflection)
Definition: Percentage of support needs resolved through self-service.
Formula:
Self-Service Rate = Self-service resolutions / (Self-service + Tickets) × 100
Requires tracking help center views, chatbot resolutions, etc.
Benchmarks:
- Below 20%: Low self-service adoption
- 20-40%: Moderate
- 40-60%: Good
- Above 60%: Excellent
What it tells you: Documentation and tooling effectiveness.
Summary Table
| Metric | Type | Primary Indicator Of |
|---|---|---|
| Ticket Volume | Volume | Support demand |
| Tickets per Customer | Volume | Product/support burden |
| First Response Time | Response | Initial responsiveness |
| Resolution Time | Resolution | Problem-solving speed |
| First Contact Resolution | Resolution | Efficiency |
| CSAT | Quality | Customer satisfaction |
| Escalation Rate | Quality | Issue complexity |
| Cost per Ticket | Efficiency | Support economics |
| Self-Service Rate | Efficiency | Deflection effectiveness |