A methodology for systematically designing and analyzing customer satisfaction metrics (CSAT/NPS/CES). Use this skill for 'CSAT analysis', 'NPS design', 'CES measurement', 'CS metrics', 'customer satisfaction system', 'VOC analysis', and other CS performance measurement needs. However, actual survey distribution and statistical software execution are outside the scope of this skill.
A skill that enhances the CS performance measurement capabilities of cs-analyst.
Question: "How satisfied were you with this interaction?" (1-5 scale)
CSAT = (4 + 5 rated responses) / Total responses x 100%
Benchmarks:
Excellent: 85%+
Good: 70-84%
Needs Improvement: 60-69%
At Risk: <60%
Measurement Timing: Immediately after interaction (interaction-based)
Question: "How likely are you to recommend this service to a friend or colleague?" (0-10 scale)
Classification:
Promoter: 9-10
Passive: 7-8
Detractor: 0-6
NPS = Promoter% - Detractor% (Range: -100 to +100)
Benchmarks (B2C SaaS):
Excellent: 50+
Good: 30-49
Average: 0-29
At Risk: <0
Measurement Timing: Quarterly (relationship-based)
Question: "How easy was it to resolve your issue?" (1-7 scale)
CES = Average of all responses
Benchmarks:
Excellent: 5.5+
Good: 4.5-5.4
Needs Improvement: 3.5-4.4
At Risk: <3.5
Measurement Timing: Immediately after interaction (effort-based)
Note: Strongest predictor of repeat purchase behavior
| Metric | Formula | Benchmark |
|---|---|---|
| FCR (First Contact Resolution) | 1st contact resolutions / Total cases x 100 | 70-75% |
| AHT (Average Handle Time) | Total handle time / Number of cases | Chat 5-8 min, Phone 6-10 min |
| ASA (Average Speed of Answer) | Total wait time / Answered cases | Chat 30 sec, Phone 60 sec |
| Escalation Rate | Escalated cases / Total cases | <15% |
| Re-inquiry Rate | Re-inquiries within 7 days / Total cases | <20% |
| Metric | Formula | Purpose |
|---|---|---|
| Cases per Agent | Daily cases / Number of agents | Capacity planning |
| Cost per Channel | Channel cost / Channel cases | Channel optimization |
| Self-Service Ratio | FAQ/bot resolutions / Total inquiries | Automation effectiveness |
Positive Keywords: thank you, fast, friendly, resolved, satisfied, great
Negative Keywords: complaint, slow, inconvenient, repeated, no response, angry
Neutral: inquiry, confirmation, curious, please let me know
Sentiment Score = (Positive count - Negative count) / Total count
1. Category-based Classification:
- Product Feature Issues (40%)
- Billing/Refunds (25%)
- Shipping/Logistics (15%)
- Account/Authentication (10%)
- Other (10%)
2. Trend Analysis:
- Surging topic detection (week-over-week +50%)
- New topic identification
- Seasonal patterns
3. Severity Classification:
- Critical: Service outage, financial loss
- Major: Feature malfunction, recurring issues
- Minor: Inconvenience, improvement requests
Real-Time Monitor (Operations Team):
+------------+------------+------------+
| Queue Count| Avg Wait | Agents |
| [Real-time]| [Real-time]| [Avail/Total]|
+------------+------------+------------+
| Hourly Incoming Volume Graph |
+---------------------------------------+
| Channel Status (Chat/Phone/Email) |
+---------------------------------------+
Weekly/Monthly Report (Management):
+------------+------------+------------+
| CSAT | NPS | FCR |
| [Trend] | [Trend] | [Trend] |
+------------+------------+------------+
| Inquiry Distribution by Topic + WoW |
+---------------------------------------+
| Agent Performance (Volume, CSAT) |
+---------------------------------------+
| Top 5 VOC Issues |
+---------------------------------------+
When CSAT is low:
1. Agent training (response quality)
2. Improve response templates
3. Authority delegation (immediate resolution capability)
When FCR is low:
1. Strengthen FAQ/knowledge base
2. Expand agent authority
3. Redefine escalation criteria
When AHT is high:
1. Provide macros/templates
2. Improve internal tool UX
3. Training + mentoring