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claude-code-skills-reference/deep-research/references/enterprise_research_methodology.md
daymade 6d261ce801 feat(deep-research): V6.1 source accessibility policy and Counter-Review Team
- Correct source accessibility: distinguish circular verification (forbidden)
  from exclusive information advantage (encouraged)
- Add Counter-Review Team with 5 specialized agents (claim-validator,
  source-diversity-checker, recency-validator, contradiction-finder,
  counter-review-coordinator)
- Add Enterprise Research Mode: 6-dimension data collection framework
  with SWOT, competitive barrier, and risk matrix analysis
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  - source_accessibility_policy.md
  - V6_1_improvements.md
  - counter_review_team_guide.md
  - enterprise_analysis_frameworks.md
  - enterprise_quality_checklist.md
  - enterprise_research_methodology.md
  - quality_gates.md
  - report_template_v6.md
  - research_notes_format.md
  - subagent_prompt.md

Based on "深度推理" case study methodology lessons learned.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-04 09:15:17 +08:00

7.5 KiB

Enterprise Research Methodology

Six-Dimension Data Collection

Enterprise research requires parallel collection across six dimensions. Execute all six in order, writing findings to a structured draft after each dimension.

Dimension 1: Company Fundamentals

Step 1.1: Confirm legal entity
├── Clarify parent/subsidiary/affiliate boundaries
├── Query: "{company} legal entity corporate structure"
├── Output: Entity scope statement
└── Verify: Map operating entities to brands

Step 1.2: Basic information
├── Query round 1: "{company} founding date headquarters founder"
├── Query round 2: "{company} company overview profile"
├── Query round 3: "{company} CEO management team executives"
├── Source priority: Official site > Regulatory filings > Authoritative media
└── Output: Basic info table (name, founded, HQ, CEO, employees, listing status)

Step 1.3: Funding history
├── Query: "{company} funding rounds valuation IPO"
├── Key fields: round, amount, investors, post-money valuation, date
└── Output: Funding timeline table

Step 1.4: Ownership structure
├── Query: "{company} ownership structure beneficial owner"
├── Key fields: controller identity, economic interest %, voting rights %, control mechanisms (dual-class etc.)
└── Output: Ownership summary

Dimension 2: Business & Products

Step 2.1: Business landscape scan
├── Query round 1: "{company} product lines business segments"
├── Query round 2: "{company} revenue breakdown by segment"
├── Query round 3: "{company} business model monetization"
├── Key fields: segment name, positioning, revenue share, YoY growth, synergies
└── Output: Business landscape table

Step 2.2: Core product analysis
├── Query: "{company} core products DAU MAU user base"
├── Per product: positioning, target users, scale (DAU/MAU), market share, monetization, competitive advantage, trends
└── Output: Product matrix table

Step 2.3: Revenue structure analysis
├── Source: Financial reports (deep extraction)
├── Breakdown by: segment, geography, customer type, pricing model
└── Output: Revenue structure summary

Dimension 3: Competitive Position

Step 3.1: Industry position
├── Query: "{company} industry ranking market share"
├── Key fields: industry definition, TAM/SAM/SOM, company rank, share, concentration (CR3/CR5)
└── Output: Industry position analysis

Step 3.2: Competitor identification & comparison
├── Query round 1: "{company} competitors"
├── Query round 2: "{company} vs {competitor A} comparison"
├── Query round 3: "{company} vs {competitor B} differences"
├── Comparison dimensions: founding, revenue, market share, core products, user scale, valuation/market cap, strengths, weaknesses
├── Minimum: ≥3 competitors identified
└── Output: Competitive comparison table

Step 3.3: Competitive barriers assessment
├── Use quantified barrier framework (see enterprise_analysis_frameworks.md)
├── 7 dimensions: network effects, scale economies, brand, technology/patents, switching costs, regulatory licenses, data assets
└── Output: Barrier scorecard with rating

Dimension 4: Financial & Operations

Step 4.1: Financial data collection
├── Query: "{company} financial results {year} revenue profit"
├── Core metrics (3-year minimum): revenue, revenue growth, net income, gross margin, net margin, operating cash flow, R&D expense, R&D ratio
└── Output: Financial metrics table (3+ years)

Step 4.2: Operating efficiency analysis
├── Query: "{company} ROE ROA efficiency per-employee"
├── Efficiency metrics: ROE, ROA, revenue per employee, accounts receivable days, debt-to-equity
└── Output: Operating efficiency table

Step 4.3: Cross-validation
├── Require ≥2 independent sources for key financial data
├── Sources: company filings (primary), regulatory filings, authoritative financial data providers
├── Deviation rules:
│   ├── ≤10%: Pass
│   ├── 10-20%: Flag with explanation
│   └── >20%: Require third-party verification
└── Output: Validation record

Dimension 5: Recent Developments

Step 5.1: Recent news scan (past 6 months)
├── Query round 1: "{company} latest news {current year}"
├── Query round 2: "{company} strategy pivot latest developments"
├── Query round 3: "{company} executive changes leadership"
├── Query round 4: "{company} partnership acquisition latest"
├── Query round 5: "{company} product launch new release"
├── Event types: product launches, fundraising/capital, strategy shifts, executive changes, M&A/partnerships, regulatory/compliance
├── Minimum: ≥5 events identified
└── Output: Major events table

Step 5.2: Strategic signal interpretation
├── Dimensions: expansion signals, contraction signals, transformation signals, risk signals
└── Output: Strategic signal analysis

Dimension 6: Internal/Proprietary Sources

Step 6.1: Internal knowledge base query (if available)
├── Query 1: "our company's relationship with {target company}"
├── Query 2: "internal assessment of {target company}"
├── Query 3: "{target company} competitive analysis"
├── Query 4: "{target company} industry research"
└── Output: Internal perspective supplementary info

Step 6.2: If no internal sources available
├── State explicitly: "No internal/proprietary sources available for this research"
├── Compensate with additional public source depth
└── Note limitation in final report

Data Source Priority Matrix

Priority Source Type Reliability Timeliness Use Case
P0 Official filings / annual reports 10/10 High Core financial data
P0 Company website / announcements 10/10 High Basic info, updates
P1 Regulatory filings 9/10 High Ownership, licenses
P1 Authoritative industry reports 9/10 Medium Market position, trends
P2 Mainstream financial media 8/10 High News, analysis
P2 Professional research institutions 8/10 Medium Deep analysis, forecasts
P3 Social media / forums 5/10 High Sentiment signals only

Rule: P0 + P1 are primary sources. P2 for validation. P3 for reference only, never as sole source.

Cross-Validation Rules

Data Type Min Sources Max Deviation Primary Source Fallback Sources
Financial data 2 10% Official financial reports Regulatory filings, analyst reports
Market share 2 15% Industry reports Company disclosures, third-party analysis
Management info 1 N/A Company official sources Regulatory filings, reputable media
User metrics 2 20% Company disclosures Third-party analytics, industry reports

Search Strategy Best Practices

  1. Multi-angle queries: 3 different query angles per topic
  2. Time filtering: Prioritize data within last 12 months for operational data, last 3 years for financial trends
  3. Site restriction: Use site: for authoritative domains when possible
  4. Language diversity: Query in both English and the company's primary language
  5. Exclude noise: Use - to exclude irrelevant results
  6. Progressive depth: Start broad, then narrow based on gaps identified