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.

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name:market-landscape-scanargument-hint:[market or problem space, and the decision it supports]description: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.intent:Autonomous market discovery: map how buyers segment the market, who plays where (direct, adjacent, substitutes, emerging), where the money and momentum are, and whether apparent whitespace is opportunity or dead zone — with labeled evidence, so sizing and positioning start from structure instead of vibes.type:workflowtheme:market-intelligencebest_for:Mapping who plays in a market before committing to enter or re-position,Scoping a new product line with a defensible view of segments and substitutes,Producing the landscape view that feeds TAM/SAM/SOM sizing and competitor deep-divesscenarios:We're considering a move into contract-analytics tooling — map that market for me,My exec team keeps citing an analyst quadrant; show me how buyers actually segment this spaceestimated_time:20-40 min per run

Market Landscape Scan

Purpose

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.

Input

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.

Key Concepts

  • Governing protocol: this skill honors the autonomous-investigation

  • contract — question budget of 3, search-plan gate, Fact/Inference/Assumption labels, Just Enough
    Mode, stable schema, 4-option Final Step.
  • Discipline mix: primarily OSINT (analyst and review coverage, press, communities) with

  • GEOINT/DEMOINT for segment reality-checks and FININT for funding signals — see
    intelligence-collection-disciplines.
  • Buyer-view segmentation. Map the market as buyers experience it, not as vendors or analysts

  • 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.
  • Non-consumption is a competitor. "They use spreadsheets" belongs on the player map. Treating

  • 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.
  • The dead-zone test. Every whitespace claim must survive the question "or is it a dead zone?"

  • Empty space is either opportunity or evidence of no demand; the honest counter-reading is mandatory,
    not optional.
  • Do-not-invent list (this domain's fabrication risks): companies, products, funding rounds,

  • market share, growth rates, customer claims.

    Application

  • Credit inline context, then ask only the unanswered questions (max 3):

  • 1. What market or problem space, in your words?
    2. What decision should this landscape support?
    3. Any boundary — geography, buyer size, price band?
    If unanswered, proceed with labeled assumptions.
  • Show the 3-bullet search plan — what you'll search, source types (analyst and review sites,

  • company and pricing pages, funding databases, industry press, trade bodies, practitioner
    communities), and how facts will be separated from inference. Continue unless revised.
  • Research in Just Enough Mode and emit the schema below exactly — it is the stable base

  • that quarterly re-scans diff against.

    Output schema (do not reorder)

    ~~~markdown

    Market Landscape Snapshot

    1. Scope


    Market / problem space: | Boundary: | Decision supported: | As-of date:

    2. How This Market Segments


  • [3-5 segments as buyers experience them, each 1 bullet]

  • [Where vendor categories disagree with buyer reality: 1 bullet]
  • 3. Player Map


    Direct players


  • [Name]: [who they serve; wedge; 1 momentum signal; URL]

  • Adjacent players (could enter)


  • [Name]: [why adjacency matters; URL]

  • Substitutes and non-consumption


  • [What buyers do instead]: [why it persists]

  • Emerging entrants


  • [Name]: [what bet they're making; funding/traction signal; URL]
  • Cap the full map at 12 players; strongest signal only.

    4. Dynamics


  • Where the money is: [2 bullets, labeled]

  • Where the momentum is: [2 bullets, labeled]

  • Consolidation or fragmentation: [1 bullet]

  • Technology or regulatory shifts in play: [1-2 bullets]
  • 5. Whitespace and Dead Zones


  • [Apparent gap]: opportunity or dead zone? [evidence either way]

  • [2-3 of these, each with the honest counter-reading]
  • 6. So What?


  • 3 implications for the decision named in Scope

  • 2 players to deep-dive next

  • 3 assumptions to validate

  • Each bullet: label, confidence, URL where relevant.
    ~~~

    A copy/paste fill-in version of this schema, with quality checks, lives in template.md.

    Final Step (offer exactly 4 options)

  • Run competitive-research-snapshot on the deep-dive players

  • Run tam-sam-som-calculator sizing on the most promising segment

  • Draft a positioning hypothesis against this landscape (positioning-statement)

  • Schedule-ready version: what should a quarterly re-scan watch?
  • Accept 1, 2, 3, 4, 1 and 2, Verbose Mode, or a custom path.

    Examples

    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.

    Common Pitfalls

  • Adopting the analyst map. Reciting a quadrant is not a landscape scan — quadrants exclude

  • substitutes, lag emerging entrants, and segment by what's convenient to rank. Use them as one
    OSINT source, labeled, never as the frame.
  • Omitting non-consumption. A player map without "what buyers do instead" flatters every vendor

  • on it and hides the real competitor: inertia.
  • Whitespace romanticism. Declaring every empty cell an opportunity. If the counter-reading is

  • missing, the analysis is a pitch, not intelligence.
  • Player-map sprawl. Twenty players with two facts each beats nothing, but twelve with the

  • strongest signal each beats it badly. The cap is the discipline.
  • Scope drift between re-scans. Changing the boundary or schema between runs silently breaks

  • comparability — a re-scan of a different scope is a new baseline, and should say so.

    References

  • autonomous-investigation (Workflow) — the governing protocol

  • intelligence-collection-disciplines (Component) — discipline sources and signal chains

  • competitive-research-snapshot (Workflow) — deep-dive on the players this scan surfaces

  • tam-sam-som-calculator (Component) — sizes the segments this scan maps

  • positioning-statement (Component) — positions against this landscape

  • Adapted from market-intelligence/market-landscape-scan-prompt.md in the

  • https://github.com/deanpeters/product-manager-prompts repo.