nickcrew/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.

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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
• pitch-deck-writer
• ux-researcher
• business-analyst