Market Scanner

Scan and map your market landscape — size, structure, trends, and seasonality. Uses Perplexity for deep market research. Output feeds every downstream research and marketing skill.

Purpose

Market Scanner is the starting point of all research. It answers:

What market are we actually in? (precise category, not vague industry)
How big is it, and where is it headed?
What macro forces are shaping it?
How is the market structured?
When does demand peak and trough?

The output — research-memory/market-landscape.md — becomes the shared context that every subsequent skill (competitor-finder, audience-profiler, brand-voice, SEO, copy, etc.) reads to stay grounded in market reality.

"Doing marketing without research is like driving without a map." — The Boring Marketer

Modes

Mode	When to Use	Behavior
Full Scan	No `market-landscape.md` exists, or it's an empty scaffold	Run all 5 steps from scratch
Refresh	`market-landscape.md` already has data	Check `research-log.md` for last scan date → update only changed sections

Auto-Load Protocol

On every invocation, BEFORE any research:

Check research-memory/ directory
If files exist → Read ALL .md files (except README.md)
Use loaded context to:
- Skip already-covered areas (avoid redundancy)
- Build on existing findings (deepen, not repeat)
- Maintain consistency with other research outputs
Check brand-memory/ (read-only) → If exists, use business description, positioning, and audience info as input context
If market-landscape.md has data AND research-log.md shows a previous scan → suggest Refresh mode

Input Gathering

Collect from the user conversationally. Do NOT dump a form — ask naturally.

Field	Required	Description
Business / Product description	YES	What does the company/product do?
Industry / Category	YES	What market does it operate in?
Current status	Optional	Revenue range, growth stage, geography
Research focus	Optional	Specific area of interest (trends, size, structure, etc.)
Known competitors	Optional	Helps triangulate market boundaries
Research intensity	Optional	"light" / "standard" / "deep" (default: deep) — 리서치 깊이와 수집량 조절
Language	Optional	결과물 작성 언어 (default: English)

If brand-memory/ exists, pre-fill from voice-profile.md and positioning.md — ask user to confirm or correct.

If this is a Refresh, show the current market-landscape.md summary and ask: "What has changed or what do you want to update?"

Research Intensity

사용자가 명시적으로 요청하면 리서치 깊이를 조절합니다. 지정하지 않으면 deep (기본값).

Level	search_context_size	수집량	용도
`light`	low	축소 (~50%)	빠른 감 잡기
`standard`	medium	보통 (~75%)	일반 리서치
`deep`	high	전체 (100%)	본격 리서치

"가볍게", "빠르게", "간단히" → light / "보통으로", "적당히" → standard / 별도 지정 없음 → deep

Process

Step 1: Define Market Category

Goal: Pin down the PRECISE market category — not "software" but "AI-powered marketing automation for SMBs."

Tool: perplexity_reason (requires analytical reasoning)

Query pattern:

What is the precise market category and sub-segment for a business that [user's business description]?

Define:
- The specific market segment (not broad industry)
- Adjacent segments that partially overlap
- Where the boundaries are (what's IN vs OUT of this market)

Be specific: "DTC home textiles" not "home goods"

Parameters:

search_context_size: Research Intensity에 따라 결정 (light→"low" / standard→"medium" / deep→"high")

Output: Category name, scope definition, boundary clarification, adjacent markets.

Step 2: Market Size & Growth (TAM / SAM)

Goal: Quantify the market opportunity with credible numbers.

Tool: perplexity_reason (numerical reasoning required)

Query pattern:

What is the current market size for [market category from Step 1]?

Provide:
1. TAM (Total Addressable Market) — global value
2. SAM (Serviceable Addressable Market) — the realistic slice for [business type/geography]
3. CAGR projection for the next 3-5 years
4. Key regional breakdown (if relevant)

For each number: cite the source name and year of data.
If multiple sources conflict, note the range.

Parameters:

search_context_size: Research Intensity에 따라 결정 (light→"low" / standard→"medium" / deep→"high")
search_recency_filter: "year"

Output: TAM, SAM, CAGR, regional split — all with source citations.

Step 3: Macro Trends + Opportunity/Threat Tagging

Goal: Identify 3-5 macro forces shaping this market, and tag each as opportunity or threat.

Tool: perplexity_ask (fact-based, current data)

Query pattern:

What are the top 3-5 macro trends shaping the [market category] market in [current year]?

For each trend, cover:
- Category: consumer behavior / technology / regulation / economic / cultural
- Description: what's happening and why it matters
- Impact on a [business type]: is this an OPPORTUNITY or THREAT?
- Timeframe: immediate (0-1yr), near-term (1-3yr), or long-term (3-5yr)
- Evidence: cite recent data points or examples

Parameters:

search_recency_filter: "month"
search_context_size: Research Intensity에 따라 결정 (light→"low" / standard→"medium" / deep→"high")

Output: 트렌드 수는 intensity에 따라 결정 (light=2-3 / standard=3 / deep=3-5), 각 트렌드에 category, opportunity/threat, timeframe, evidence 포함.

Step 4: Market Structure Map + Seasonality

Goal: Understand how the market is organized and when demand peaks/troughs.

Tool: perplexity_ask

Query pattern:

How is the [market category] market structured?

Map along these dimensions:
1. Price tiers: budget / mid-range / premium / luxury
2. Distribution channels: DTC, retail, marketplace, wholesale, SaaS, etc.
3. Customer segments: demographics, use cases, geography
4. Product sub-categories: major product/service lines

Also identify:
- Seasonal demand patterns (peak months, trough months)
- Event-driven demand spikes (holidays, industry events, budget cycles)
- Any cyclical patterns (quarterly, annual)

Parameters:

search_context_size: Research Intensity에 따라 결정 (light→"low" / standard→"medium" / deep→"high")

Output: Market structure 분석 범위는 intensity에 따라 결정 (light=2차원 핵심만 / standard=3차원 / deep=4차원 전체) + seasonality calendar.

Step 5: Save & Log

Goal: Write all findings to research-memory/market-landscape.md and log the execution.

5a. Write market-landscape.md

Language rule: 섹션 헤더와 테이블 컬럼명은 영어로 유지합니다. 본문, 셀 값, 설명, 분석 텍스트는 사용자가 지정한 언어로 작성합니다. 언어가 지정되지 않으면 English로 작성합니다.

Use the exact schema below. Fill every section with Step 1-4 findings.

# Market Landscape
> Last updated: [YYYY-MM-DD]
> Source skill: market-scanner

## Market Definition
[Category name, scope, boundaries, adjacent markets]

## Market Size (TAM / SAM)
| Metric | Value | Source | Year |
|--------|-------|--------|------|
| TAM | $XXB | [source] | [year] |
| SAM | $XXB | [source] | [year] |
| Growth Rate (CAGR) | XX% | [source] | [year range] |

[Regional breakdown if relevant]

## Growth Trajectory
[Growth stage: early / growth / mature / declining]
[Key growth drivers]
[Headwinds / risks]

## Macro Trends
| # | Trend | Category | Type | Impact | Timeframe |
|---|-------|----------|------|--------|-----------|
| 1 | [trend] | [category] | Opportunity/Threat | [impact] | [timeframe] |
| 2 | [trend] | [category] | Opportunity/Threat | [impact] | [timeframe] |
| 3 | [trend] | [category] | Opportunity/Threat | [impact] | [timeframe] |

## Market Structure Map
### By Price Tier
[budget / mid / premium / luxury breakdown]

### By Channel
[DTC, retail, marketplace, etc.]

### By Customer Segment
[demographics, use cases, geography]

### By Sub-Category
[product/service lines]

## Seasonality & Demand Cycles
[Peak months, trough months, event-driven spikes]
[Budget cycles, quarterly patterns]

For Refresh mode: Do NOT overwrite the entire file. Update only the sections that changed. Append > Updated: [date] below the section header for each changed section.

5b. Update research-log.md

Append one row to the log:

| [YYYY-MM-DD] | market-scanner | Full Scan / Refresh | [brief summary of key findings or changes] | Perplexity |

Perplexity MCP Tool Guide

Tool	When to Use	This Skill
`perplexity_reason`	Analytical reasoning, number crunching	Step 1 (category definition), Step 2 (TAM/SAM)
`perplexity_ask`	Factual Q&A, current events	Step 3 (trends), Step 4 (structure/seasonality)
`perplexity_search`	Find specific URLs/reports	Only if Steps 1-4 need source verification

Common parameters:

search_context_size: Research Intensity 레벨에 따라 결정 — 위 Research Intensity 테이블 참조
search_recency_filter: "month" for trends (Step 3), "year" for size data (Step 2)

Query best practices:

Be specific: Include the exact market category in every query
Ask for sources: Always request citation of source name + data year
Handle conflicts: When sources disagree, report the range, not a single number
One topic per query: Don't combine market size + trends in one call
Language: 사용자가 English 외 언어를 지정한 경우, 모든 query 끝에 "Respond in [language]."를 추가

Quality Checklist

Before saving, verify:

Market category is PRECISE (not "tech" but "AI-powered marketing automation for SMBs")
TAM/SAM numbers have source citations and data year
매크로 트렌드 최소 2개 (light) ~ 5개 (deep) 식별, 각각 opportunity/threat 태그 포함
Market structure 최소 2차원 (light) ~ 4차원 (deep) 커버 (price, channel, segment, sub-category)
Seasonality section is populated (even if "no strong seasonality detected")
All Perplexity responses include source URLs in the output
research-log.md updated with execution record

Example (Abbreviated)

Input: "Marketing education business selling skill packs and courses to solo marketers."

Category: Creator Economy — Marketing Education & Digital Skills TAM: $30B (global online education, marketing subset — HolonIQ 2024) SAM: $3B (English-speaking solo marketers — estimated 2024) CAGR: 12-15% (SignalFire, 2024-2029) Trends: AI democratizing execution (Opportunity), Creator economy growth (Opportunity), AI replacing traditional education (Threat) Seasonality: Q1 peak (New Year), Q4 trough (holidays), Sep mini-peak (back-to-work)

What This Skill Does NOT Do

Competitor analysis → Use competitor-finder (separate skill)
Customer profiling → Use audience-profiler (separate skill)
Customer language mining → Use voice-of-customer (separate skill)
Strategic recommendations → Use research-synthesizer (reads this output)

Market Scanner stays focused on the market itself — size, shape, forces, timing.