deanpeters/market-landscape-scan
Map a market's segments, players, substitutes, and whitespace with cited evidence. Use when entering or re-evaluating a market before sizing, positioning, or picking competitors to study.
npx skills add https://github.com/deanpeters/Product-Manager-Skills --skill market-landscape-scan
Map a market's structure using a workflow, not a one-shot answer: **search plan → segmentation →
player mapping → dynamics → whitespace → next-step options.** The output is the landscape view that
everything downstream stands on — sizing needs to know the segments, positioning needs to know the
players, and competitor deep-dives need to know who's worth the effort. This skill maps structure,
not magnitude: it tells you who plays where and why, not how big the prize is.
Works best with: the market, segment, or problem space to map — in your words, not an analyst
category — and the decision this landscape should support (market entry, new product line,
re-positioning, build-vs-buy).
Also useful: any boundary narrower than global — geography, buyer size, price band — and players
you already know about, so the scan spends its effort on what you don't.
Input supplied inline with the invocation — text after the skill name, a pasted context dump, or an
appended ARGUMENTS: line — counts as answers already given. Use it against the question budget;
don't re-ask.
Arriving empty-handed? That works too. The skill opens with at most 3 questions (market, decision,
boundary) and proceeds on labeled assumptions if they go unanswered — that's the
autonomous-investigation contract.
Example invocation: `Run a market landscape scan on developer-facing API observability tools,
EU-only — this supports a Q4 market-entry decision.`
autonomous-investigationcontract — question budget of 3, search-plan gate, Fact/Inference/Assumption labels, Just Enough
Mode, stable schema, 4-option Final Step.
GEOINT/DEMOINT for segment reality-checks and FININT for funding signals — see
intelligence-collection-disciplines.
carve it — and note where the two disagree. Analyst quadrants are a map someone else drew for their
own purposes; the disagreement between vendor categories and buyer reality is often where the
opportunity hides.
substitutes and non-consumption as competitors is the most commercially useful habit in market
analysis — the biggest rival is usually the status quo, and it never shows up in a quadrant.
Empty space is either opportunity or evidence of no demand; the honest counter-reading is mandatory,
not optional.
market share, growth rates, customer claims.
If unanswered, proceed with labeled assumptions.
company and pricing pages, funding databases, industry press, trade bodies, practitioner
communities), and how facts will be separated from inference. Continue unless revised.
that quarterly re-scans diff against.
~~~markdown
Market / problem space: | Boundary: | Decision supported: | As-of date:
Cap the full map at 12 players; strongest signal only.
Each bullet: label, confidence, URL where relevant.
~~~
A copy/paste fill-in version of this schema, with quality checks, lives in template.md.
competitive-research-snapshot on the deep-dive playerstam-sam-som-calculator sizing on the most promising segmentpositioning-statement)Accept 1, 2, 3, 4, 1 and 2, Verbose Mode, or a custom path.
Segmentation catching a vendor/buyer disagreement (all names fictional):
> Vendors in this space market three categories: "observability platforms," "APM," and "log
> management." Buyers in practitioner forums segment differently — Fact
> (community thread, Jun 2026): by *who gets paged* (dev-owned vs.
> ops-owned) and by *cost model tolerance* (per-seat vs. per-GB). Two "different" vendor categories
> compete head-to-head for dev-owned/per-seat buyers — Inference (same buyers evaluating both in
> review-site comparisons). The category language is marketing architecture, not market structure.
A whitespace claim surviving the dead-zone test:
> Apparent gap: nobody serves sub-50-employee agencies at self-serve pricing. Opportunity or dead
> zone? Two prior entrants targeted exactly this and pivoted upmarket within 18 months — Fact
> (funding announcements, URLs). Their stated reason was willingness-to-pay,
> not demand — Inference (founder postmortem cites CAC/LTV, not lack of interest). Verdict:
> conditional whitespace — viable only with a radically cheaper acquisition motion. **Assumption to
> validate:** the segment's tooling budget clears $50/month.
See examples/sample.md for a complete worked scan (fictional FSM-software
market) whose output feeds the competitive-research-snapshot example — the chain's schemas
demonstrated end to end. examples/sample-industrial.md runs the
same schema in a fictional industrial market, where the substitutes and freshest signals change
completely.
substitutes, lag emerging entrants, and segment by what's convenient to rank. Use them as one
OSINT source, labeled, never as the frame.
on it and hides the real competitor: inertia.
missing, the analysis is a pitch, not intelligence.
strongest signal each beats it badly. The cap is the discipline.
comparability — a re-scan of a different scope is a new baseline, and should say so.
autonomous-investigation (Workflow) — the governing protocolintelligence-collection-disciplines (Component) — discipline sources and signal chainscompetitive-research-snapshot (Workflow) — deep-dive on the players this scan surfacestam-sam-som-calculator (Component) — sizes the segments this scan mapspositioning-statement (Component) — positions against this landscapemarket-intelligence/market-landscape-scan-prompt.md in thehttps://github.com/deanpeters/product-manager-prompts repo.
Take deanpeters/market-landscape-scan from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.