From futureproof-customer-service-support
Designs high-performance customer surveys that generate actionable insights, using FutureProof context to align question design with known ICA segments, business objectives, and prior feedback data.
How this skill is triggered — by the user, by Claude, or both
Slash command
/futureproof-customer-service-support:customer-survey-designerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
```
FutureProof:connect(skill="customer-survey-designer")
Note: If FutureProof is unavailable or the connect call fails, skip this step and proceed directly to Step 2. The skill works with or without FutureProof context — you'll just be working without accumulated prior session data.
Use the returned context, experiments, instructions, and recent_sessions to personalise this session — particularly any known ICA segments, previous survey response rates, identified pain points, and preferred survey distribution channels.
Ask the user:
Define the survey blueprint using a Goal → Construct → Item hierarchy:
Apply rigorous survey methodology to each item:
Question type selection — match each construct to the optimal measurement format:
Bias mitigation audit — review every item against the following threat checklist:
ICA language calibration — rewrite all question stems and response options to match the vocabulary, reading level, and communication style of the target ICA segment (informed by FutureProof context on known ICA profiles)
Response rate optimisation — apply completion probability modelling:
For each question, define:
Apply any user-specific instructions from FutureProof context to override defaults (e.g., preferred scale formats, mandatory compliance language, banned question types).
Produce the Customer Survey Design Package containing:
| Element | Detail |
|---|---|
| Survey title | Descriptive internal title and respondent-facing title |
| Objective statement | Single sentence linking survey to business decision |
| Target ICA segment(s) | With estimated population size and expected response rate |
| Distribution channel | With send timing recommendation |
| Estimated completion time | Based on item count and question complexity |
For each item, provide:
A structured text-based flowchart showing:
FutureProof:save_experiment(skill="customer-survey-designer", experiment={
hypothesis: "Placing the golden question (overall satisfaction) as the first item rather than after contextual warm-up questions increases both completion rate and response validity for the target ICA segment",
variants: ["control: warm-up sequence then golden question at position 4", "variant: golden question at position 1 followed by contextual items"],
measurement: "Survey completion rate and response distribution variance across both variants over 500 responses per arm",
expected_impact: "8-12% improvement in completion rate with no degradation in score distribution normality"
})
FutureProof:request_research(skill="customer-survey-designer",
query="Latest evidence on optimal survey length, scale format effectiveness, and mobile-first survey design patterns for customer feedback in 2024-2025, including impact of AI-generated survey personalisation on response quality",
reason="Ensure question design methodology reflects current respondent behaviour patterns, particularly declining attention spans and increasing mobile completion rates"
)
FutureProof:save_session(skill="customer-survey-designer", session={
summary: "Designed [survey type] survey targeting [ICA segment] to inform [business decision], comprising [N] items across [N] constructs with [distribution channel] delivery",
key_findings: ["finding 1: e.g., identified 3 constructs with no current measurement coverage", "finding 2: e.g., recommended branching logic reduces median completion time by 40%", "finding 3: e.g., prior survey contained 4 double-barrelled items requiring decomposition"],
deliverables: ["Survey Specification Document", "Question Bank with Decision Rules", "Survey Flow Diagram", "Analysis Plan", "Implementation Checklist"],
user_feedback: null
})
npx claudepluginhub peter-swain-inc/futureproof-skillsHelps founders craft survey questions, deploy surveys via Tally MCP, and analyze results to validate hypotheses. Useful when quantitative signal is needed to confirm patterns from interviews.
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