Crewhu Surveys (CSAT / NPS)
Surveys are Crewhu's primary product — short CSAT/NPS responses tied to a ticket close, a specific tech, or a project milestone. This skill covers listing surveys, finding a specific one, and isolating the two ends of the curve (detractors and promoters) so MSP managers can react.
API Tools
List & Search
| Tool | Purpose |
|---|---|
crewhu_surveys_list | Paginated list of recent survey responses |
crewhu_surveys_search | Search surveys by keyword / metadata |
crewhu_surveys_get | Pull full detail for one survey response |
Sentiment Slices
| Tool | Purpose |
|---|---|
crewhu_surveys_detractors | Detractor responses (low scores / negative comments) |
crewhu_surveys_promoters | Promoter responses (high scores / positive comments) |
Common Workflows
Pull recent survey trend
- Call
crewhu_surveys_listwith a wide enough window (90 days minimum). - Bucket results by week and compute average score and response count.
- Surface the trend line, not just the latest week — single weeks are noisy.
Detractor follow-up queue
- Call
crewhu_surveys_detractorsto get the negative responses. - For each, call
crewhu_surveys_getto retrieve the full comment and the responsible technician (the responses include user attribution — cross-reference withcrewhu_users_get). - Produce a follow-up list: customer, ticket, tech, score, comment, suggested action (call-back, account-manager hand-off, escalation).
Promoter recognition loop
- Call
crewhu_surveys_promotersto find positive responses. - Use the responsible tech to drive a recognition workflow:
crewhu_badges_user_recognitionto see whether the tech is already trending in recognition.- Consider awarding a badge via the
badgesdomain (seecrewhu_badges_history_list).
Per-user roll-up
- Use
crewhu_users_listto enumerate techs. - For each tech, use
crewhu_surveys_search(keyed on the user) to pull their responses. - Compute average score, response count, and detractor rate per tech for a manager scorecard.
Edge Cases
- Sparse responses — Some techs have few surveys; flag any per-user metrics with N < 10 as low-confidence rather than ranking.
- Comment-only feedback — Some responses have a comment without a score. Surface those separately; do not coerce them into the score average.
- Time zones — Survey timestamps are in the tenant's configured zone; normalize before comparing across tenants.
Best Practices
- Always show denominators (response count) alongside averages.
- Pair detractor lists with promoter lists in a manager dashboard so the picture is balanced.
- Capture the tech for every response in your output so action items are unambiguous.
Related Skills
- api-patterns - Auth and pagination