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Market Research

Community
shawnpang
market-research

When the user needs to estimate market size, understand market dynamics, or validate that a market opportunity is large enough to pursue.

Overview

Publishershawnpang
Repositorystartup-founder-skills
Skill namemarket-research
Stars
368
Forks
43
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by shawnpang on GitHub. Read the source before you install it.

Installation

Install the Market Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/shawnpang/startup-founder-skills/tree/main/skills/market-research
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/shawnpang/startup-founder-skills.git /tmp/startup-founder-skills
mkdir -p .claude/skills
cp -r /tmp/startup-founder-skills/skills/market-research .claude/skills/market-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Market Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Market Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Market Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Market Research

When to Use

Activate when a founder needs to size a market opportunity using TAM/SAM/SOM, validate market assumptions for a pitch deck, understand growth trends, evaluate market entry, or prepare for investor conversations about addressable market. Trigger phrases include "how big is our market," "TAM/SAM/SOM," "market size," "market opportunity," "is this market big enough," "market trends," "help me with the market slide," or "validate our market assumptions."

Context Required

  • From startup-context: product description, target customer segments, pricing model, geographic scope, business model.
  • From the user: the market or segment to analyze, known data points (industry reports, customer counts, pricing benchmarks), geographic and industry constraints, whether this is for internal decision-making or external presentation (investor deck), and any specific hypotheses about market dynamics.

Workflow

  1. Define market boundaries -- Specify the problem space, customer segments, geography, and constraints. "Project management tools" is a different market than "team collaboration software." Precision determines whether the analysis is useful.
  2. Top-down estimation -- Start from total industry size using industry reports, public company revenues, and government statistics. Narrow to the relevant segment by applying filters for geography, customer type, and product category.
  3. Bottom-up estimation -- Build independently from unit economics: (number of potential customers) x (price per customer) x (purchase frequency). Cross-validate against the top-down estimate.
  4. Scope the SAM -- Identify which portion of TAM is realistically serviceable given current product capabilities, pricing, distribution channels, and geographic reach.
  5. Estimate the SOM -- Project achievable market share in 1-3 years based on competitive position, go-to-market capacity, and current traction.
  6. Project growth -- Forecast how TAM, SAM, and SOM evolve over 2-3 years. Identify key growth drivers, technology shifts, regulatory changes, and demographic trends.
  7. Map assumptions -- Surface every critical assumption underlying each estimate. Rate confidence levels and identify how to validate the most uncertain assumptions.

Output Format

Market Definition

One paragraph defining the problem space, customer need, geographic and segment boundaries, and key scoping decisions.

TAM / SAM / SOM

MetricCurrent Estimate2-3 Year ProjectionMethodConfidence
TAM$X$YTop-down + Bottom-upHigh/Med/Low
SAM$X$YFiltered from TAMHigh/Med/Low
SOM$X$YPenetration modelHigh/Med/Low

Sizing Methodology

Top-Down: Step-by-step calculation from industry totals to target segment. Show every filter and assumption applied.

Bottom-Up: Step-by-step calculation from unit economics up. Show: (number of target customers) x (expected conversion rate) x (annual contract value).

Reconciliation: Comparison of both approaches, explanation of any gaps, and reconciled estimate. If they diverge by more than 3x, investigate the assumptions driving the gap.

Growth Drivers & Trends

Key factors that could expand or contract the market -- technology shifts, regulatory changes, demographic trends, behavioral changes, and emerging adjacent segments.

Key Assumptions & Risks

AssumptionImpact if WrongConfidenceValidation Method
DescriptionWhat changes in the estimateHigh/Med/LowHow to test this

Strategic Implications

Numbered list of what the market data means for product, pricing, and go-to-market decisions.

Frameworks & Best Practices

  • Always do both top-down and bottom-up. Top-down is fast but abstract. Bottom-up is precise but assumption-heavy. The truth is where they converge. Providing both triangulates and builds credibility with investors.
  • Beware vanity TAMs. "The global software market is $500B" is not useful. Define the market narrowly enough that you can name the buyer persona, their budget line item, and what they pay today.
  • The "who writes the check" test. Market size should be based on the actual budget your product replaces or claims. A $50/month tool's market is (number of buyers) x ($600/year), not the total revenue of the industry you serve.
  • Growth rate matters more than current size. A $500M market growing 40% annually is more attractive than a $5B market growing 3%. Investors and founders should optimize for tailwinds.
  • Distinguish value-based from volume-based sizing. Revenue-based (dollars) and volume-based (users/units) tell different stories. Be explicit about which you are using and why.
  • Assumption sensitivity analysis. Identify the 2-3 assumptions that most affect your estimate. Show what happens if each is 50% lower. If the market is still attractive at the pessimistic end, the thesis is robust.
  • Source hierarchy for credibility: (1) Government statistics and census data, (2) Public company filings and earnings calls, (3) Industry association reports, (4) Analyst reports (Gartner, Forrester, IDC), (5) Startup databases (PitchBook, Crunchbase), (6) Your own primary research and customer data.
  • Cite sources for market data. Avoid unsupported numbers. Label what is an estimate vs. what is sourced data. Flag where estimates have wide confidence intervals.
  • Geographic specificity. Global TAMs are meaningful only if you plan to sell globally from day one. Start with the geography and segment you will actually target first.
  • Adjacent market expansion. After sizing the core market, identify 1-2 adjacent markets you could expand into. This shows a growth path beyond the initial wedge.
  • Consider currency and purchasing power parity for international market sizing.

Related Skills

  • competitive-analysis -- Pair market sizing with competitive landscape analysis to understand both the size of the prize and how contested it is.
  • prd-writing -- Use market segment data to ground the Market Segments section of a PRD in real numbers.
  • roadmap-planning -- Use growth trend analysis to time roadmap investments. Build for fast-growing segments first.

Examples

Example 1: Market sizing for a pitch deck

User: "Help me size the market for our developer productivity tool. We need the TAM/SAM/SOM for our Series A deck."

Good output excerpt:

TAM: $[X]B -- Global developer tools market (source: [industry report], includes IDEs, testing, CI/CD, monitoring, and productivity tools).

SAM: $4.2B -- Code review and collaboration segment, filtered to teams of 10-500 developers at companies with >$5M revenue in North America and Europe.

SOM: $85M -- 2% penetration of SAM over 4 years, based on current growth rate of 15% QoQ and average ACV of $18K.

Bottom-up cross-check: 23,000 target companies x 12% expected conversion at maturity x $18K ACV = $49.7M.

Example 2: New segment validation

User: "We're thinking about expanding from SMB to mid-market. Is that market big enough?"

Good output should size the mid-market segment separately, compare unit economics (higher ACV but longer sales cycle), estimate the investment required to serve the segment (enterprise features, sales team), and calculate whether the segment-level SOM justifies the investment within the planning horizon.

Frequently asked questions

What does the Market Research AI skill do?

When the user needs to estimate market size, understand market dynamics, or validate that a market opportunity is large enough to pursue.

Why use Market Research on TypingMind?

Because you install it once and use it with any model. Market Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Market Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/shawnpang/startup-founder-skills/tree/main/skills/market-research. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Market Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Market Research?

As many as you like. As long as a model supports skills, you can use Market Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Market Research AI skill free?

Yes. It is published on GitHub by shawnpang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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