market-research-analysis▌
manojbajaj95/claude-gtm-plugin · updated Apr 8, 2026
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Expert market research skill — from market sizing and competitive analysis through consumer research and professional consulting-grade reports with LaTeX formatting and visual generation.
Market Research & Analysis
Expert market research skill — from market sizing and competitive analysis through consumer research and professional consulting-grade reports with LaTeX formatting and visual generation.
Quick Start
Choose your workflow:
- Market Sizing — TAM/SAM/SOM calculations
- Competitive Analysis — Landscape mapping and positioning
- Consumer Research — Surveys, interviews, behavior analysis
- Professional Report — 50+ page consulting-style report with LaTeX + visuals
Market Sizing (TAM → SAM → SOM)
Step 1: Define Scope
- Product/service being analyzed
- Geography (target regions)
- Customer segment (who specifically)
- Time frame (current year or 5-year projection)
Step 2: Calculate TAM (Top-Down)
TAM = Total market demand at 100% market share
= (Total potential customer base) × (avg contract value)
Data sources: Gartner, Forrester, IBISWorld, government statistics, trade associations
Step 3: Calculate SAM
SAM = Portion of TAM you can realistically serve
Apply filters: geographic constraints, product limitations, customer size constraints
Typically 5-20% of TAM
Step 4: Calculate SOM
SOM = Realistic near-term market share (1-3 years)
Conservative benchmarks:
Year 1: 0.1-0.5% of SAM
Year 2: 0.5-2% of SAM
Year 3: 1-5% of SAM
Step 5: Bottom-Up Validation
Bottom-up = (realistic target customers) × (conversion rate) × (ACV)
If top-down SOM / bottom-up > 3x → revisit top-down assumptions
Competitive Landscape Analysis
Competitor Categories
| Type | Definition | Example |
|---|---|---|
| Direct | Same product, same customer | Asana vs Monday.com |
| Indirect | Different product, same problem | Asana vs Excel |
| Substitute | Alternative way to address need | Asana vs consultants |
| Potential | Could enter market easily | Microsoft, Google |
Competitive Intelligence Sources
- Company websites (pricing, features, positioning)
- App store reviews (G2, Capterra — look for "appears X times" keywords)
- Crunchbase (funding, valuation, growth trajectory)
- Job postings (what they're investing in)
- LinkedIn (employee count trends, key hires)
- Gartner Magic Quadrant (market positioning)
Positioning Map Template
Create a 2D matrix:
- X-axis: Price (Low → High)
- Y-axis: Feature complexity / target segment (Simple → Advanced)
Plot all competitors. Look for gaps — unserved or underserved quadrants = market opportunity.
Core Analysis Frameworks
Porter's Five Forces (rate each High / Medium / Low)
- Threat of New Entrants — Barriers to entry, capital requirements, brand loyalty
- Supplier Power — Concentration, switching costs, substitute inputs
- Buyer Power — Concentration, price sensitivity, switching costs
- Threat of Substitutes — Alternatives, switching costs, price/performance tradeoff
- Competitive Rivalry — Number of competitors, industry growth, differentiation
PESTLE Analysis
| Dimension | Key Questions |
|---|---|
| Political | Regulatory environment, trade policies |
| Economic | Growth rates, inflation, currency risks |
| Social | Demographics, consumer behavior shifts |
| Technological | Disruptive technologies, R&D activity |
| Legal | Compliance requirements, IP landscape |
| Environmental | Sustainability trends, regulations |
SWOT + BCG Matrix
For competitive landscape: map competitors on BCG Matrix (market growth vs market share) to identify Stars, Cash Cows, Question Marks, Dogs.
Consumer Research
Survey Design
Van Westendorp Pricing: Ask customers 4 questions to find optimal price point:
- At what price is this too expensive to consider?
- At what price is this so cheap you doubt the quality?
- At what price does this start to feel expensive (but not off the table)?
- At what price is this a great value/bargain?
Plot cumulative % — OPP (Optimal Price Point) = intersection of "too expensive" and "too cheap."
Anti-pattern: Never use leading questions ("Don't you think our innovative product..."). Always include negative response options.
Interview Framework
For qualitative research:
- Define clear research objectives first
- Minimum 5-10 interviews for directional insight, 15-20 for patterns
- Focus on jobs to be done and pain points, not feature preferences
- Capture verbatim language — exact phrases are more valuable than summaries
Quality Checklist
- Research objectives clearly defined and measurable
- Sample is representative of target market
- Mix of qualitative (why) and quantitative (how many) methods
- No leading or biased questions
- Insights are actionable, not just "interesting facts"
- Limitations acknowledged
Professional Market Research Reports
Generates consulting-grade reports (50+ pages) modeled on McKinsey, BCG, Gartner deliverables.
Report Structure (~66 pages target)
Front Matter (~5 pages): Cover page · Table of Contents · Executive Summary (investment thesis, key findings, top 5 recommendations)
Core Analysis (~35 pages):
| Chapter | Pages | Key Frameworks |
|---|---|---|
| Market Overview & Definition | 4-5 | Industry structure |
| Market Size & Growth | 6-8 | TAM/SAM/SOM, regional breakdown |
| Industry Drivers & Trends | 5-6 | PESTLE, driver impact matrix |
| Competitive Landscape | 6-8 | Porter's Five Forces, positioning matrix |
| Customer Analysis | 4-5 | Segmentation, customer journey |
| Technology & Innovation | 4-5 | Technology roadmap, adoption curve |
| Regulatory & Policy | 3-4 | Regulatory timeline |
| Risk Analysis | 3-4 | Risk heatmap, mitigation matrix |
Strategic Recommendations (~10 pages): Opportunity matrix · Implementation roadmap · Investment thesis
Back Matter (~5 pages): Methodology · Data tables · Company profiles · Bibliography
Visual Generation (generate 6 priority visuals first)
# Batch generate all core visuals
python scripts/generate_market_visuals.py \
--topic "[MARKET NAME]" --output-dir figures/
| Priority | Visual | Tool |
|---|---|---|
| 1 | Market growth trajectory | scientific-schematics |
| 2 | TAM/SAM/SOM concentric circles | scientific-schematics |
| 3 | Porter's Five Forces | scientific-schematics |
| 4 | Competitive positioning matrix (2×2) | scientific-schematics |
| 5 | Risk heatmap | scientific-schematics |
| 6 | Executive summary infographic | generate-image |
LaTeX Compilation
# Initialize project structure
writing_outputs/YYYYMMDD_HHMMSS_market_report_[topic]/
├── drafts/v1_market_report.tex ← use assets/market_report_template.tex as base
├── figures/
├── references/references.bib
└── final/
# Compile
cd drafts/
xelatex v1_market_report.tex && bibtex v1_market_report
xelatex v1_market_report.tex && xelatex v1_market_report.tex
Use \usepackage{market_research} (from assets/market_research.sty).
Colored box environments:
\begin{keyinsightbox}[Key Finding]...\end{keyinsightbox} % blue
\begin{marketdatabox}[Market Snapshot]...\end{marketdatabox} % green
\begin{riskbox}[Critical Risk]...\end{riskbox} % orange
\begin{recommendationbox}[Recommendation]...\end{recommendationbox} % purple
See assets/FORMATTING_GUIDE.md for complete LaTeX reference.
See assets/market_report_template.tex for the full report template.
Report Quality Standards
- Data: No older than 2 years; all statistics attributed; projections state assumptions
- Writing: Specific numbers over vague qualifiers; insights first, then data; active voice
- Visuals: 300 DPI minimum; colorblind-friendly palette; all axes/legends labeled; sources in captions
- Length: 50+ pages — if under, expand appendix data tables and add regional breakdowns
Pre-Submission Checklist
- Cover page, ToC, List of Figures, Executive Summary
- All 11 chapters present (no placeholder sections)
- 6 core visuals generated and rendering
- All statistics sourced; projections include assumptions
- PDF compiles without errors; cross-references work
- Page count >50
References & Assets
scripts/generate_market_visuals.py— Batch visual generation for reportsassets/market_research.sty— LaTeX style packageassets/market_report_template.tex— Full report templateassets/FORMATTING_GUIDE.md— Complete LaTeX formatting referencereferences/report_structure_guide.md— Detailed chapter-by-chapter guidancereferences/data_analysis_patterns.md— Analysis patterns and common calculationsreferences/visual_generation_guide.md— Visual creation workflows
Related Skills
product-strategy-and-marketing— Market opportunity within product strategygo-to-market-strategy— Applying market research to launch planningpricing-strategy— Using market research for pricing decisions
How to use market-research-analysis on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add market-research-analysis
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches market-research-analysis from GitHub repository manojbajaj95/claude-gtm-plugin and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate market-research-analysis. Access the skill through slash commands (e.g., /market-research-analysis) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★52 reviews- ★★★★★Omar Brown· Dec 28, 2024
I recommend market-research-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Arya Yang· Dec 24, 2024
market-research-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Nikhil Kim· Dec 8, 2024
market-research-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★James Sharma· Dec 8, 2024
Useful defaults in market-research-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sofia Smith· Nov 27, 2024
market-research-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Mateo Robinson· Nov 23, 2024
I recommend market-research-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Jin Choi· Nov 15, 2024
market-research-analysis reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Rahul Santra· Nov 7, 2024
I recommend market-research-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Oct 26, 2024
Useful defaults in market-research-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Isabella Taylor· Oct 18, 2024
Solid pick for teams standardizing on skills: market-research-analysis is focused, and the summary matches what you get after install.
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