--- name: market-researcher description: 'Use this skill when sizing a market, analyzing competitors, designing customer surveys, segmenting audiences, or synthesizing research into market insights. Trigger phrases: ''size the market for'', ''analyze our competitors'', ''who is our target customer'', ''design a survey to understand'', ''TAM/SAM/SOM for''. Not for building financial models, writing pitch decks, or conducting UX usability research.' version: 1.0.0 author: community tags: - business - market-research - analysis - competitive license: MIT keywords: - market sizing - TAM SAM - customer survey - competitive - market - researcher - market researcher --- # Market Researcher ## Overview This skill guides structured market research—from estimating market size using TAM/SAM/SOM through primary and secondary research design, customer segmentation, survey construction, and competitive landscape analysis. It turns ambiguous market questions into defensible, data-backed conclusions that inform strategic decisions about where to play and how to win. ## When to Use - Sizing a new market opportunity before investing in product development - Analyzing competitor strengths, weaknesses, and positioning - Designing a customer survey to understand needs or validate assumptions - Segmenting a customer base to find the most valuable groups - Preparing market analysis for a pitch deck, board presentation, or strategic plan - Understanding why customers choose or leave a product ## When NOT to Use - Conducting usability testing or user interviews about product UX (use ux-researcher skill) - Building detailed financial models or revenue projections (use a finance skill) - Writing the full pitch deck (use pitch-deck-writer skill) - Real-time social media monitoring or sentiment analysis ## Quick Reference | Research Task | Method | Time Required | |--------------|--------|---------------| | Market sizing | TAM/SAM/SOM (top-down + bottom-up) | 2–8 hours | | Competitor analysis | Framework + web research | 4–12 hours | | Customer needs | 8–12 in-depth interviews | 2–3 weeks | | Hypothesis validation | Survey (n=200+) | 1–2 weeks | | Customer segmentation | Survey + cluster analysis | 2–4 weeks | | Positioning map | Perception survey or desk research | 1–3 days | | Secondary research | Reports, databases, news | 2–8 hours | ## Instructions ### Step 1: Define the Research Question Before gathering data, write a single crisp research question: - "What is the addressable market for AI-powered legal contract review in the US?" - "Why do users cancel within 30 days of signing up for our product?" - "How does our product compare to competitors on features and pricing?" Then list 3–5 sub-questions that, if answered, would answer the main question. ### Step 2: Market Sizing — TAM / SAM / SOM **Definitions:** - **TAM** (Total Addressable Market): Total revenue available if you captured 100% of the market - **SAM** (Serviceable Addressable Market): The portion you can realistically target given your business model, geography, and product - **SOM** (Serviceable Obtainable Market): What you can realistically capture in 3–5 years **Two approaches to triangulate:** **Top-Down (use industry reports):** ``` TAM: Find total industry revenue from analyst reports (Gartner, IDC, Statista) Example: "Global legal tech market: $29B (2024)" → TAM = $29B SAM: Apply your segment filters "AI-specific legal tech, US only, mid-to-large law firms" = 15% of global market SAM = $29B × 15% = $4.4B SOM: Apply your achievable market share "Realistic 3% capture in 5 years" → SOM = $4.4B × 3% = $132M ``` **Bottom-Up (use unit economics):** ``` # Count the buyers × their spend Target customers: US law firms with 50+ attorneys = 8,000 firms Average annual contract value (ACV): $25,000 Total SAM = 8,000 × $25,000 = $200M/year SOM: Win 500 firms in 5 years → 500 × $25,000 = $12.5M ARR ``` > **Best practice**: Use both approaches; if they're within 2× of each other, your estimate is credible. If they diverge more, investigate why. **Data sources for market sizing:** - Gartner, Forrester, IDC, Grand View Research (paid) - Statista, IBISWorld (paid, often available via library) - Census Bureau, BLS, SEC filings (free) - LinkedIn Sales Navigator (estimate company counts) - Crunchbase, PitchBook (funding and revenue signals) - Job posting counts (proxy for company growth in a segment) ### Step 3: Primary vs Secondary Research **Secondary research** (desk research — start here): - Industry analyst reports (Gartner Magic Quadrant, Forrester Wave) - Competitor websites, pricing pages, job postings, press releases - App store reviews of competitor products - Reddit, Twitter, G2, Capterra, Trustpilot — customer voice - Government databases (Census, USPTO, SEC EDGAR) - Academic papers, conference proceedings **Primary research** (you collect — for validation and nuance): | Method | Best For | Sample Size | |--------|----------|-------------| | In-depth interviews | Deep understanding of motivations | 8–15 | | Online surveys | Quantifying preferences, segmentation | 200–1,000+ | | Focus groups | Concept testing, early ideation | 2 groups of 6–8 | | Observational/ethnography | Understanding actual behavior | 5–10 sessions | | A/B tests | Validating specific hypotheses | 1,000+ per variant | ### Step 4: Survey Design A good survey: 1. Takes < 10 minutes (15 questions max) 2. Asks one thing per question 3. Progresses from general to specific 4. Uses consistent rating scales (always 1–5 or always 1–7; never mix) 5. Ends with demographics and open-ended "anything else?" **Question type guide:** - **Multiple choice (single)**: When answers are mutually exclusive ("Which best describes your role?") - **Multiple choice (multi-select)**: "Which of these tools do you use?" (check all that apply) - **Likert 1–5**: Agreement, satisfaction, frequency - **Ranking**: "Rank these features from most to least important" (max 5 items) - **NPS (0–10)**: "How likely are you to recommend us?" - **Open-ended**: "What is the biggest challenge you face with X?" (use sparingly, 1–2 max) **Sample survey structure:** ``` Section 1: Screener (1–2 questions to qualify respondents) Section 2: Current behavior and pain (3–4 questions) Section 3: Product/solution fit (3–4 questions) Section 4: Competitive usage and preferences (2–3 questions) Section 5: Willingness to pay / pricing (1–2 questions) Section 6: Demographics (2–3 questions) ``` ### Step 5: Customer Segmentation Segment your market on dimensions that predict purchase behavior: **B2B segmentation dimensions:** - Company size (employees, revenue) - Industry vertical - Geography - Tech stack / sophistication - Buying process (self-serve vs sales-led) - Use case (primary job to be done) **B2C segmentation dimensions:** - Demographics (age, income, education) - Psychographics (values, lifestyle, attitudes) - Behavioral (usage frequency, purchase history, NPS) - Geography **Segmentation output template:** | Segment | Size | Description | Primary Need | Channel | ACV | |---------|------|-------------|-------------|---------|-----| | Enterprise Legal | 2,000 firms | 500+ attorneys, dedicated IT | Compliance automation | Sales-led | $80K | | Mid-Market Legal | 6,000 firms | 50–500 attorneys, cost-sensitive | Time savings | PLG + inside sales | $20K | | Solo/Small Firm | 50,000 firms | <50 attorneys, price-sensitive | Affordable AI assistance | Self-serve | $2K | ### Step 6: Competitive Landscape Analysis Analyze 5–8 direct and indirect competitors across: **Feature matrix:** | Feature | Your Product | Competitor A | Competitor B | Competitor C | |---------|-------------|-------------|-------------|-------------| | Feature 1 | ✅ | ✅ | ❌ | ✅ | | Feature 2 | ✅ | ❌ | ✅ | ❌ | | Pricing | $X/mo | $Y/mo | $Z/mo | $W/mo | | Target segment | Mid-market | Enterprise | SMB | Mid-market | **Positioning map** (2×2 matrix with two dimensions): - X-axis: Price (budget → premium) - Y-axis: Ease of use (complex → simple) - Plot each competitor as a dot; find whitespace = your opportunity **SWOT analysis per competitor:** - S: What do they do best? (customer reviews, investor narratives) - W: Where do they fall short? (negative reviews, high churn signals) - O: What market trends help them? - T: What could hurt them (you, regulation, substitutes)? ## Examples ### Example 1: Size the US Online Education Market **Research question:** What is the market size for AI-powered corporate learning platforms in the US? **Top-down approach:** ``` Global corporate e-learning market (2024): $50B (Grand View Research) US share: ~35% → $17.5B US market AI-enhanced segment: ~20% of corporate e-learning → $3.5B SAM Target: Mid-to-large enterprises (1,000+ employees) = 40% of market → $1.4B Realistic 4-year market capture at 2% = $28M ARR ``` **Bottom-up approach:** ``` US companies with 1,000+ employees: ~19,000 (BLS data) Estimated 25% currently buying L&D platforms: 4,750 companies Average L&D platform spend: $80K/year Total SAM: 4,750 × $80K = $380M (conservative; AI premium not modeled) SOM at 1.5% capture: ~70 companies → $5.6M ARR in Year 3 ``` **Synthesis:** Top-down gives $28M, bottom-up gives $5.6M—roughly a 5× gap. Investigation reveals the top-down estimate includes training content production budgets, not just platform software. Adjusting the top-down scope brings both estimates to $15–25M TAM for a standalone AI platform. Credible SOM: $5–10M ARR by Year 4. --- ### Example 2: Analyze Competitor Positioning for a Project Management Tool **Research question:** How does our new project management tool compare to Asana, Monday.com, and Linear? **Research methods used:** Competitor websites, G2/Capterra reviews (top 50 for each), App Store reviews, job postings (signal for engineering investment), pricing pages. **Findings summary:** | Dimension | Our Tool | Asana | Monday.com | Linear | |-----------|----------|-------|-----------|--------| | Target user | Developer teams | Marketing/ops | Any team | Engineers | | Core strength | GitHub integration | Workflow automation | Customization | Speed & simplicity | | Pricing (team plan) | $12/user/mo | $13.49/user/mo | $12/user/mo | $8/user/mo | | Key complaint (G2) | "Missing Gantt view" | "Too complex" | "Expensive at scale" | "Too dev-focused" | | AI features | ✅ native | ⚠️ limited | ⚠️ limited | ❌ | **Positioning gap identified:** No competitor strongly serves *mixed teams* (engineering + product + design) with deep GitHub integration + non-developer accessibility. This is the whitespace. **Recommendation:** Position as "the project management tool for product teams that ship software"—bridging engineering (GitHub) and business stakeholders (no-code views, status reports). ## Best Practices - Triangulate market size with two methods (top-down + bottom-up) and explain any large gaps - Primary research validates secondary research; never rely on one source alone - For surveys, pilot test with 5 people before full launch; fix confusing questions - When analyzing competitors, focus on customer reviews for weaknesses—competitor websites only show strengths - Segment by behavior, not just demographics; two people with the same age can have very different buying behavior - Make assumptions explicit: "We assume 15% of the market is addressable given our current integrations" - Research findings should lead to a recommendation, not just a data dump ## Common Mistakes - Reporting TAM as the investment opportunity (it's not; SOM is) - Conflating total industry spending with the addressable software market - Survey bias: leading questions, or surveying only existing happy customers - Treating competitor feature lists at face value without talking to their customers - Doing only secondary research for important decisions (desk research has survivorship bias) - Forgetting to validate willingness to pay—a large market of people who won't pay is worthless - Confusing market size with market demand (a market can be large but already saturated) ## Tips & Tricks - G2 and Capterra reviews are gold mines—read the 3-star reviews for honest trade-offs - LinkedIn company search filters (industry + size) let you count companies in a segment for free - App store reviews sorted by "most recent, 1–2 stars" shows a competitor's current problems - The "jobs to be done" (JTBD) framework is the best mental model for understanding why customers buy - Always ask survey respondents "why?" after a rating—open text explains the number - Job postings reveal where competitors are investing: 10 new ML engineer listings signals an AI product push ## Related Skills - [competitor-analyst](../../business/competitor-analyst/SKILL.md) - [pitch-deck-writer](../../business/pitch-deck-writer/SKILL.md) - [ux-researcher](../../business/ux-researcher/SKILL.md) - [business-analyst](../../business/business-analyst/SKILL.md)