User Personas
Turn survey, interview, or spreadsheet research into three actionable JTBD personas before you commit to features or positioning.
Overview
User Personas is an agent skill for the Idea phase that creates three research-backed personas with JTBD, pains, gains, and unexpected insights from survey or interview data.
Install
npx skills add https://github.com/phuryn/pm-skills --skill user-personasWhat is this skill?
- Produces exactly 3 refined user personas from provided research inputs
- Five-step method: data collection, pattern recognition, segmentation, enrichment, validation
- Each persona includes jobs-to-be-done, pains, gains, and unexpected behavioral insights
- Reads CSV, Excel, survey responses, and interview transcripts directly when supplied
- Positions personas for downstream product and segmentation decisions
- Outputs 3 refined user personas
- 5-step analysis workflow from collection through validation
Adoption & trust: 1.1k installs on skills.sh; 12.3k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You have survey or interview data but no clear, diverse user segments to guide what to build or whom to target first.
Who is it for?
Indie PMs and solo founders finishing discovery who need structured personas from real CSV, Excel, or transcript inputs.
Skip if: Greenfield products with zero research inputs, or teams that only need fictional personas without data grounding.
When should I use this skill?
Building personas from survey data, creating user profiles from research, or segmenting users for product decisions.
What do I get? / Deliverables
You receive three validated-style persona profiles with JTBD, pains, gains, and insights ready for validate-stage scoping and positioning decisions.
- Three persona profiles with JTBD
- Documented pains, gains, and unexpected insights per persona
Recommended Skills
Journey fit
Canonical shelf is Idea because personas synthesize discovery research into segments that steer what you validate and build next. Research subphase fits synthesis from CSV, surveys, and transcripts into structured profiles—not implementation or launch tactics.
How it compares
Use this synthesis skill instead of one-shot chat personas that ignore uploaded survey patterns.
Common Questions / FAQ
Who is user-personas for?
Solo builders and indie product people who have research artifacts and want three actionable personas tied to jobs-to-be-done and pains—not decorative marketing slides.
When should I use user-personas?
Use it during Idea research when building personas from survey data, creating profiles from interviews, or segmenting users before validate-scope and prototype choices.
Is user-personas safe to install?
It processes documents you provide locally through the agent; review the Security Audits panel on this page before sharing sensitive customer PII in prompts or attachments.
SKILL.md
READMESKILL.md - User Personas
# User Personas ## Purpose Create detailed, actionable user personas from research data that capture the true diversity of your user base. This skill generates research-backed personas with jobs-to-be-done, pain points, desired outcomes, and unexpected behavioral insights to guide product decisions. ## Instructions You are an experienced product researcher specializing in persona development and user research synthesis. ### Input Your task is to create 3 refined user personas for **$ARGUMENTS**. If the user provides CSV, Excel, survey responses, interview transcripts, or other research data files, read and analyze them directly using available tools. Extract key patterns, demographics, motivations, and behaviors. ### Analysis Steps (Think Step by Step) 1. **Data Collection**: Read and review all provided research data and documents 2. **Pattern Recognition**: Identify recurring characteristics, goals, pain points, and behaviors across users 3. **Segmentation**: Group similar users into distinct personas based on shared motivations and jobs-to-be-done 4. **Enrichment**: For each persona, synthesize data into a coherent profile 5. **Validation**: Cross-reference insights to ensure personas are grounded in actual research findings ### Output Structure For each of the 3 personas, provide: **Persona Name & Demographics** - Age range, role/title, company size (if B2B), key characteristics **Primary Job-to-be-Done** - The core outcome the persona is trying to achieve - Context and frequency of the job **Top 3 Pain Points** - Specific challenges or obstacles preventing job completion - Impact and severity of each pain **Top 3 Desired Gains** - Benefits, outcomes, or solutions the persona seeks - How they measure success **One Unexpected Insight** - A counterintuitive behavioral pattern or motivation derived from the data - Why this matters for product decisions **Product Fit Assessment** - How $ARGUMENTS addresses (or could address) this persona's needs - Potential friction points or unmet needs ## Best Practices - Ground all insights in actual data; avoid assumptions - Use direct quotes from research when available - Identify behavioral patterns, not just demographic categories - Make personas distinct and non-overlapping where possible - Flag any data gaps or areas requiring additional research --- ### Further Reading - [User Interviews: The Ultimate Guide to Research Interviews](https://www.productcompass.pm/p/interviewing-customers-the-ultimate) - [Market Research: Advanced Techniques](https://www.productcompass.pm/p/market-research-advanced-techniques) - [Jobs-to-be-Done Masterclass with Tony Ulwick and Sabeen Sattar](https://www.productcompass.pm/p/jobs-to-be-done-masterclass-with) (video course)