market-research-analysis

manojbajaj95/claude-gtm-plugin · updated Apr 8, 2026

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$npx skills add https://github.com/manojbajaj95/claude-gtm-plugin --skill market-research-analysis
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summary

Expert market research skill — from market sizing and competitive analysis through consumer research and professional consulting-grade reports with LaTeX formatting and visual generation.

skill.md

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:

  1. Market Sizing — TAM/SAM/SOM calculations
  2. Competitive Analysis — Landscape mapping and positioning
  3. Consumer Research — Surveys, interviews, behavior analysis
  4. 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)

  1. Threat of New Entrants — Barriers to entry, capital requirements, brand loyalty
  2. Supplier Power — Concentration, switching costs, substitute inputs
  3. Buyer Power — Concentration, price sensitivity, switching costs
  4. Threat of Substitutes — Alternatives, switching costs, price/performance tradeoff
  5. 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:

  1. At what price is this too expensive to consider?
  2. At what price is this so cheap you doubt the quality?
  3. At what price does this start to feel expensive (but not off the table)?
  4. 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 reports
  • assets/market_research.sty — LaTeX style package
  • assets/market_report_template.tex — Full report template
  • assets/FORMATTING_GUIDE.md — Complete LaTeX formatting reference
  • references/report_structure_guide.md — Detailed chapter-by-chapter guidance
  • references/data_analysis_patterns.md — Analysis patterns and common calculations
  • references/visual_generation_guide.md — Visual creation workflows

Related Skills

  • product-strategy-and-marketing — Market opportunity within product strategy
  • go-to-market-strategy — Applying market research to launch planning
  • pricing-strategy — Using market research for pricing decisions
how to use market-research-analysis

How to use market-research-analysis on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/manojbajaj95/claude-gtm-plugin --skill market-research-analysis

The skills CLI fetches market-research-analysis from GitHub repository manojbajaj95/claude-gtm-plugin and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/market-research-analysis

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

GET_STARTED →

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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.752 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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