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Market research

Skill tuliosousapro/SaaS-blueprint/skills/market-research

BRAINIAC - SaaS Blueprint, NOT an APP. It's a comprehensive playbook and operating system designed for building, launching, and scaling a SaaS APP covering from MVP to Mass Scale. It is structured as a chronological and functional roadmap, containing over 80 specialized directories, each with its own PLAYBOOK.md.

Install
npx -y skills add tuliosousapro/SaaS-blueprint --skill market-research

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Deep web research skill using Firecrawl MCP. Use when estimating market size (TAM/SAM/SOM), analyzing trends, or scraping competitors. For competitor teardowns, see competitor-analysis.

SKILL.md

3.1 KB, as published. Nobody here has run it

Market Research Skill

When to Use

  • During Phase 0 (Idea) → Market Research, Competitor Analysis, Opportunity Mapping
  • During Phase 1 (Validation) → Demand Testing
  • Any time you need structured intelligence about a market, niche, or competitor

Tools Required

ToolPurpose
firecrawl_searchWeb search for market data, trends, competitors
firecrawl_scrapeExtract structured data from specific pages
firecrawl_extractPull pricing, features, positioning from competitor sites
firecrawl_mapDiscover all pages on a competitor's site

Instructions

1. Define Research Scope

Before starting any research, clarify with the user:

  • Market/Industry: What space are we researching?
  • Geography: Global, US, EU, LATAM, specific country?
  • Depth: Quick scan (30 min) or deep dive (2+ hours)?
  • Focus: TAM estimation, competitor landscape, trend signals, or all three?

2. TAM/SAM/SOM Estimation

Execute these searches in parallel:

firecrawl_search: "{industry} market size 2024 2025 report"
firecrawl_search: "{industry} SaaS revenue growth forecast"
firecrawl_search: "{niche} total addressable market"

Structure the output as:

MetricValueSourceConfidence
TAM$X B{source}High/Med/Low
SAM$X M{source}High/Med/Low
SOM$X M{source}High/Med/Low

3. Competitor Landscape

For each competitor identified:

firecrawl_extract:
  urls: ["{competitor_url}"]
  prompt: "Extract: company name, tagline, pricing tiers, key features, target audience, tech stack indicators"
  schema: {
    name: string,
    tagline: string,
    pricing: [{ tier: string, price: string, features: [string] }],
    target_audience: string,
    key_features: [string]
  }

Compile into a comparison matrix:

FeatureCompetitor ACompetitor BCompetitor COur Opportunity

4. Trend Analysis

Search for:

firecrawl_search: "{industry} trends 2025 2026"
firecrawl_search: "{niche} emerging technology"
firecrawl_search: "{industry} pain points users complain"

Categorize trends as:

  • Tailwinds (market forces working in our favor)
  • Headwinds (forces working against us)
  • Wildcards (unpredictable but high-impact)

5. Output Format

Save all research to the relevant PLAYBOOK.md directory as RESEARCH.md with:

  1. Executive Summary (3 sentences max)
  2. TAM/SAM/SOM table
  3. Competitor matrix
  4. Trend analysis (tailwinds/headwinds/wildcards)
  5. Key insight + recommended action
  6. Sources list with URLs

Quality Gates

  • Minimum 3 independent sources for any TAM claim
  • Competitor data must be scraped, not assumed
  • All monetary values must include year and currency
  • Trends must be dated (no stale 2022 data presented as current)

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.