Unified segmentation skill with three modes: market segmentation (identify 3-5 opportunity segments with JTBD and fit analysis), user segmentation (cluster existing users from feedback data by behavior and needs), or beachhead selection (evaluate candidate segments against burning pain, WTP, winnability, and referral potential to pick the best launch segment). Use when exploring market opportunities, building a segmentation model from user data, or choosing where to focus first.
From pm-market-researchnpx claudepluginhub tarunccet/pm-skillsThis skill uses the workspace's default tool permissions.
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Migrates code, prompts, and API calls from Claude Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, updating model strings on Anthropic, AWS, GCP, Azure platforms.
Details PluginEval's skill quality evaluation: 3 layers (static, LLM judge), 10 dimensions, rubrics, formulas, anti-patterns, badges. Use to interpret scores, improve triggering, calibrate thresholds.
Quick reference: Use for segmenting users from existing feedback/survey data (user mode), for strategic market segments (market mode), or for picking your best launch segment (beachhead mode). For detailed individual personas from research, use
research-personas.
Answer the right segmentation question for your current stage — whether you're exploring a market for opportunity sizing, clustering your existing users to target them differently, or picking the single best segment to dominate first at launch.
Segmentation draws on three distinct methodologies depending on the question:
market mode when exploring a new market, sizing TAM/SAM, or evaluating which segments to enteruser mode when you have existing feedback data (interviews, support tickets, surveys, usage logs) and need to understand distinct user groupsbeachhead mode when deciding where to focus limited GTM resources for an initial launchuser-personas skill — it creates narrative persona profiles)ideal-customer-profile skill)gtm-strategy skill)You are a strategic market researcher and behavioral analyst specializing in segmentation, customer clustering, and go-to-market targeting.
Your task is to help with segmentation for $ARGUMENTS.
Ask the user which mode applies:
market — Identify and evaluate 3-5 distinct market segments for opportunity assessmentuser — Analyze existing user feedback data to surface distinct behavioral segmentsbeachhead — Evaluate candidate segments and identify the single best launch segmentIf $ARGUMENTS already signals the mode (e.g., "segment my user feedback" → user; "where should we launch first" → beachhead), proceed directly.
You may also chain modes: after market segmentation, offer to run beachhead selection on the identified segments.
When to use: Exploring a new market, sizing opportunity, choosing strategic targets.
Analysis Steps (Think Step by Step)
Output: For each of the 3-5 segments
Segment Name & Overview
Key Demographics & Firmographics
Jobs-to-be-Done
Key Pain Points & Obstacles
Desired Gains & Success Factors
Product Fit Analysis
Competitive Landscape
After the segment profiles, provide a Segment Prioritization Summary — a table ranking segments by: market size, growth rate, competition intensity, and product fit. Highlight the top 1-2 recommended targets with rationale.
When to use: You have existing user feedback (interviews, support tickets, surveys, usage logs) and want to understand distinct user groups to target them differently.
Analysis Steps (Think Step by Step)
Output: For each identified segment (minimum 3)
Segment Name & Overview
Behavioral Characteristics
Jobs-to-be-Done & Motivations
Key Needs & Pain Points
Current Product Fit
Differentiated Value Opportunity
Segment Priority Recommendation
When to use: Deciding where to focus limited launch resources. Based on Geoffrey Moore's beachhead strategy in Crossing the Chasm.
Core principle: Start absurdly specific. A niche beachhead is better than a vague mass market. Choose the smallest winnable, referenceable market that validates PMF and enables expansion.
Step 1: Enumerate Candidate Segments List all plausible launch segments across: industry verticals, company sizes, job titles/roles, geographic regions, use cases, customer maturity levels.
Step 2: Evaluate Each Candidate Against 4 Criteria
Criterion 1 — Burning Pain Point (Does this segment experience an acute, unmet problem?)
Criterion 2 — Willingness to Pay (Does this segment have budget and motivation to pay?)
Criterion 3 — Winnable Market Share (Can you capture 60-70% in 3-18 months?)
Criterion 4 — Referral Potential (Will customers naturally refer to others?)
Step 3: Score Each Candidate
| Segment | Burning Pain (1-5) | WTP (1-5) | Winnable (1-5) | Referral (1-5) | Total | Notes |
|---|---|---|---|---|---|---|
| [Segment A] | ||||||
| [Segment B] |
Step 4: Select Beachhead and Define Expansion Path
For the recommended beachhead:
Beachhead mode prompt: "Where should we launch our AI contract review tool first?" Expected output excerpt:
Top candidate segments evaluated: In-house legal teams at Series B–D startups, solo practitioners at small law firms, procurement teams at mid-market SaaS companies Recommended beachhead: In-house legal at Series B–D startups — burning pain (reviewing vendor contracts with no legal headcount), clear WTP ($500-2k/mo), winnable (few AI tools built for this niche), strong referral (legal ops community is tight-knit)