Product Research
Runs product research as a disciplined method-and-repository practice: pick the right method, size the sample correctly.
Before & after
Same prompt, same agent — the only difference is the skill.
That's a great question. User research is really important for understanding your customers. You'll want to talk to potential users, maybe run some surveys, and gather feedback on your ideas. Some teams do interviews, others prefer online questionnaires. The key is to get a representative sample and document what you learn. You might also consider running a small pilot or beta to see how real users interact with your product. It's helpful to take notes and look for patterns across your conversations. Let me know if you'd like suggestions on specific research methods.
RESEARCH PLAN FOR SAAS LAUNCH STEP 1: METHOD SELECTION • Generative interviews (5-8 users) → understand problem space • Usability test (6 users, 45 min each) → validate core flow • Concept test (20 users, survey) → validate pricing/positioning Timing: Week 1-2 interviews, Week 3 usability, Week 4 concept test STEP 2: SAMPLE SIZE & SATURATION • Generative: 5-8 interviews reach saturation on problem themes (~85% confidence) • Usability: 6 users catch 85% of task-blocking issues (Nielsen curve) • Concept: 20 responses give ±22% margin of error at 95% confidence STEP 3: INSIGHT SYNTHESIS • Code observations by theme (not opinions—count across participants) • Flag single-source anecdotes separately (do not treat as insights) • Threshold: insight requires recurrence across 2+ independent participants OUTPUT: Insight spreadsheet with method, participant count, confidence, action
About this skill
name: product-research description: Use when Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs ...
Product Research
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.
What you get
- Public GitHub repo (alirezarezvani/claude-skills)
- the product-research skill folder with SKILL.md. Part of a 337-skill / 30-agent / 70-command install.
Customize your output
- Fork the repo and adapt the skill's instructions and references to your workflow.
Example output
Activates automatically when your request matches Product Research; chains with the other skills, agents, and commands in the collection.
Best for
Creators, builders, and teams using Claude Code.
SKILL.md preview
---
name: product-research
description: Use this skill when planning or synthesizing product and user research, choosing the right method for the goal, and turning coded observations into insights without fabricating user signal.
version: 1.0.0
category: Research & Data / Research
author: AgentVolt
license: proprietary
tags:
- research-data
- research
---
# Product Research
Runs product research as a disciplined method-and-repository practice: pick the right method, size the sample correctly, and only call something an insight if it recurs across independent participants.
## When to use
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