Skip to content
Back to skills

Res Customer Research

ASecurity

Customer and user research — interview guides, JTBD framing, evidence-based insight synthesis, and bias controls. Use when user says "customer research", "user research", or needs to understand why users buy, stay, or churn.

  • 3 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added October 6, 2026
researchrustgo

Security analysis

A100/100

Scanned October 6, 2026

npx -y skills add meshcode-ai/skills-research --skill res-customer-research --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Res Customer Research?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Res Customer Research
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/meshcode-ai-res-customer-research/badge)](https://www.skillsdirectory.com/skills/meshcode-ai-res-customer-research)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: res-customer-research
description: Customer and user research — interview guides, JTBD framing, evidence-based insight synthesis, and bias controls. Use when user says "customer research", "user research", or needs to understand why users buy, stay, or churn.
license: MIT
metadata:
  source: "alirezarezvani/claude-skills@research/ (MIT)"
  category: research
---

# Customer Research

## Interview design
- **Behavior-only questions**: "Walk me through the specific situation when you last solved {problem}." Opinion/hypothesis questions ("Would you want this feature?") are banned — responses are valid only as past behavior, not attitudes.
- Format: verify recent behavior → deep dive on one actual case (~20 min) → frustration points → current alternatives (competing product, spreadsheets, memory).
- Sampling: 5 people per segment = the pattern-capture threshold. If no common pattern emerges from 5, the segment definition is wrong.

## JTBD framing
Translate feature requests ("make the button bigger") into the higher-level job: "what was I trying to finish when this request came up, and when." A request ≠ a need. Treat requests as clues only, and always label your interpretation.

## Bias checklist
- Familiarity bias (interviewing people you know) · winner bias (current customers only) · recall bias (memory distortion) · hope bias (leading toward the answer you want) · active-user bias (never talking to churned users)
- **Churned-user interviews carry the most information** — aim for at least 3.
- Never state internal figures (frequency, conversion rate) as settled fact without cross-validation.

## Output
```
# Customer Research — {segment} (n={count})
## 3–5 key findings (each: evidence citation | frequency | counterexample)
## JTBD table (situation | definition of done | current alternative)
## Bias limits (who did we not talk to)
## Hypotheses to validate + next actions
```

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…