Crewhu Surveys

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

1. Call crewhu_surveys_list with a wide enough window (90 days

minimum).

1. Bucket results by week and compute average score and response count.
2. Surface the trend line, not just the latest week — single weeks are

noisy.

Detractor follow-up queue

1. Call crewhu_surveys_detractors to get the negative responses.
2. For each, call crewhu_surveys_get to retrieve the full comment

and the responsible technician (the responses include user attribution — cross-reference with crewhu_users_get).

1. Produce a follow-up list: customer, ticket, tech, score, comment,

suggested action (call-back, account-manager hand-off, escalation).

Promoter recognition loop

1. Call crewhu_surveys_promoters to find positive responses.
2. Use the responsible tech to drive a recognition workflow:
3. crewhu_badges_user_recognition to see whether the tech is

already trending in recognition.

• Consider awarding a badge via the badges domain (see

crewhu_badges_history_list).

Per-user roll-up

1. Use crewhu_users_list to enumerate techs.
2. For each tech, use crewhu_surveys_search (keyed on the user) to

pull their responses.

1. 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](../api-patterns/SKILL.md) - Auth and pagination