metrics: 16
computable: 16
breakdowns: 3

Customer Support Metrics

Metrics for measuring support team performance and customer service quality.

Benchmark context: B2B SaaS companies typically spend ~8% of Annual Recurring Revenue (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

Ticket Volume is reported per ticket type. Teams that staff by channel (email, chat, phone) add that split from their help desk. Questions answered without a ticket are counted by Self-Service Rate instead.

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 the customer base. A rising ratio usually points to product or onboarding issues.

Ticket Backlog

Definition: Number of tickets open or pending at the end of the period.

Formula:

Backlog = Count of open tickets

What it tells you: Current support debt. It should hold steady or fall.

Ticket Distribution by Type

Definition: Breakdown of tickets by category.

Formula:

Type share = Tickets of the type created in period / Ticket Volume

Categories (typical):

How-to / Usage questions
Bug reports
Feature requests
Billing inquiries
Account issues
Other (including outage or incident related)

Ticket Distribution by Type is reported per ticket type: one share for each type, with the shares summing to 100%.

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)

Resolution Time is reported per ticket type.

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%.

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

GASP uses a 5-point scale and counts the top two ratings (4 and 5) as positive.

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 the percentage of respondents scoring 5 or above on the same 1-7 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, so cutting friction does more for repeat business than raising satisfaction.

What it tells you: Support friction. Lower effort correlates with retention.

Sources:

Ticket Escalation Rate

Definition: Percentage of tickets escalated to higher tier or engineering.

Formula:

Ticket 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 resolved.

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. It should fall 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

Self-service resolutions are deflections: help center or chatbot sessions that ended without a ticket. Raw help center views overstate the rate.

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
Ticket Escalation Rate	Quality	Issue complexity
Cost per Ticket	Efficiency	Support economics
Self-Service Rate	Efficiency	Deflection effectiveness

Related Metrics

These metrics are connected in the GASP relationship graph.

Upstream: what drives metrics on this page

Uptime drives CSAT (Engineering)

Downstream: what metrics on this page drive

CSAT drives NPS (Core)
First Response Time measures Ticket (Entity)
Ticket Volume measures Ticket (Entity)
Self-Service Rate measures Ticket (Entity)
Self-Service Rate measures Knowledge Article (Entity)