User Segmentation
Cluster users into at least three behavior-and-JTBD segments from feedback, tickets, or surveys so you can target roadmap and messaging.
Overview
User Segmentation is an agent skill most often used in Grow (also Idea audience, Validate scope) that clusters users into at least three JTBD- and behavior-based segments from feedback data.
Install
npx skills add https://github.com/phuryn/pm-skills --skill user-segmentationWhat is this skill?
- Five-step workflow: data prep, behavior extraction, needs analysis, clustering, validation
- Requires at least 3 distinct non-overlapping user segments
- JTBD, pain points, and usage modes drive clusters—not demographics alone
- Ingests interviews, support tickets, surveys, and usage logs you provide
- Expert behavioral-research framing for coherent segment definitions
- Identifies at least 3 distinct user segments
- 5 analysis steps: data preparation through validation
Adoption & trust: 1k installs on skills.sh; 12.3k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
Your user feedback sounds like one blob of opinions, so you cannot tell which jobs, pains, or journeys belong to different kinds of customers.
Who is it for?
Founders with piles of interviews, tickets, or survey text who need actionable segments without hiring a research agency.
Skip if: Teams that only need SQL funnel cohorts with no qualitative synthesis, or products with too little feedback to support three distinct groups.
When should I use this skill?
Segmenting a user base, analyzing diverse user feedback, or building a segmentation model.
What do I get? / Deliverables
You get at least three validated segment profiles with behaviors, JTBD, and needs you can use for prioritization, onboarding, and messaging experiments.
- Minimum three named segments with behaviors, JTBD, pains, and validation notes
- Non-overlapping segment definitions suitable for roadmap and messaging
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Canonical shelf is Grow → analytics because segmentation turns raw feedback into measurable cohorts for lifecycle and product decisions after you have users. The skill outputs segment models and validation criteria suited to analytics and cohort thinking, not one-off competitor scans.
Where it fits
Turn messy discovery interviews into three need-based groups before you commit to a niche landing page.
Decide which prototype workflows to cut by seeing which segment’s JTBD your MVP actually serves.
Align lifecycle emails and feature flags to segments derived from tickets and survey open-ends.
Draft segment-specific help docs once clusters explain why different users ask different questions.
How it compares
Use instead of generic “create personas” prompts when you need explicit clustering steps and a minimum of three behavior-based segments.
Common Questions / FAQ
Who is user-segmentation for?
Solo and indie PMs analyzing mixed user evidence who want JTBD-anchored segments rather than demographic stereotypes.
When should I use user-segmentation?
Use it in Grow analytics work when refining lifecycle strategy, during Validate scoping when feedback disagrees, or in Idea audience research when early signals need structure—especially when segmenting a user base or building a segmentation model.
Is user-segmentation safe to install?
It reads user-provided feedback files; avoid uploading PII you should not share with an agent, and review the Security Audits panel on this page for supply-chain risk.
SKILL.md
READMESKILL.md - User Segmentation
# User Segmentation ## Purpose Analyze diverse user feedback to identify at least 3 distinct behavioral and needs-based user segments. This skill surfaces hidden customer groups based on jobs-to-be-done, behaviors, and motivations rather than demographics alone, enabling targeted product strategy. ## Instructions You are an expert behavioral researcher and data analyst specializing in user segmentation and behavioral clustering. ### Input Your task is to segment users for **$ARGUMENTS** based on behavior, jobs-to-be-done, and unmet needs. If the user provides feedback data, interviews, support tickets, product usage logs, surveys, or other user data, read and analyze them directly. Extract behavioral patterns, motivations, and needs across the user base. ### Analysis Steps (Think Step by Step) 1. **Data Preparation**: Read and organize all provided user feedback and data 2. **Behavior Extraction**: Identify key behavioral patterns, usage modes, and user journeys 3. **Needs Analysis**: Map jobs-to-be-done, desired outcomes, and pain points for each user 4. **Clustering**: Group users into distinct segments based on behavior and needs similarity 5. **Validation**: Ensure segments are coherent, non-overlapping, and actionable 6. **Characterization**: Develop rich profiles for each segment with representative quotes ### Output Structure For each identified segment (minimum 3): **Segment Name & Overview** - Clear, descriptive segment identifier - Size: estimated number or percentage of user base - Brief one-sentence characterization **Behavioral Characteristics** - How this segment uses $ARGUMENTS (primary use cases, frequency, depth) - Typical user journey and key touchpoints - Technical proficiency or sophistication level - Integration with other tools or workflows **Jobs-to-be-Done & Motivations** - Core job(s) this segment is trying to accomplish - Underlying motivations and desired outcomes - Context and frequency of the job - What success looks like for this segment **Key Needs & Pain Points** - Unmet needs specific to this segment's behavior - Obstacles preventing effective job completion - Current workarounds or alternative solutions they employ - Severity and frequency of pain points **Current Product Fit** - How well $ARGUMENTS currently serves this segment - Features or capabilities this segment values most - Gaps or limitations most frustrating to this segment - Likelihood to continue using vs. churn risk **Differentiated Value Proposition** - What unique value could be unlocked for this segment - Feature or experience improvements that would maximize fit - Messaging and positioning most resonant with this segment **Segment Prioritization** - Strategic importance: growth potential, revenue impact, alignment with vision - Implementation difficulty: ease of serving this segment's needs - Recommendation: invest, maintain, or de-prioritize ## Best Practices - Ground segmentation in behavioral and motivational data, not just demographics - Use representative quotes and examples from actual user feedback - Ensure segments are distinct and serve different core needs - Consider interdependencies between segments and prioritization tradeoffs - Flag any segments that may be underrepresented in feedback data - Validate emerging segments against product usage or customer data when available - Consider adjacent behaviors and cross-segment patterns --- ### Further Reading - [Market Research: Advanced Techniques](https://www.productcompass.pm/p/market-research-advanced-techniques) - [User Interviews: The Ultimate Guide to Research Interviews](https://www.productcompass.pm/p/interviewing-customers-the-ultimate) - [Jobs-to-be-Done Masterclass with Tony Ulwic