research-analysis

McKinsey-style business research and analysis skill. This skill should be used when the user needs consulting-grade insights, quantitative data modeling, competitor deep-dive analysis, user persona research, industry trend reports, or structured business problem-solving. Triggers on requests like analyze this market, compare competitors, build a user persona, estimate market size, write a research report, do a SWOT analysis, or any business research task requiring structured frameworks and data-driven conclusions.

Overview

This skill provides McKinsey-style consulting analysis capabilities, including structured thinking frameworks, quantitative modeling methods, competitor analysis templates, user research methodologies, and tool integration guides. It transforms complex business problems into conclusion-first, data-supported, actionable recommendations.

Core Principles

All analysis must follow three rules:

1. Conclusion first - Lead with the answer, then support with data (pyramid principle)
2. Data supported - Every claim backed by evidence with cited sources
3. Actionable - End with specific, prioritized recommendations with timelines

Analysis Workflow

Step 1: Problem Definition

Clarify the core question before diving into analysis:

• Restate the user's question in SCQA format (Situation, Complication, Question, Answer)
• Identify the decision-maker and what decision they need to make
• Define the scope: what is in-scope vs. out-of-scope
• Determine the output format: executive summary, full report, presentation, or comparison table

Step 2: Framework Selection

Load references/analysis-frameworks.md and select the appropriate framework(s):

Problem Type	Recommended Framework
Strategy formulation	SWOT + Porter's Five Forces
Market entry	3C + TAM/SAM/SOM
Marketing optimization	4P + Customer Journey
Business model design	Business Model Canvas
Problem decomposition	MECE + Issue Tree
Hypothesis testing	Hypothesis-Driven Analysis
Revenue growth	GMV decomposition / Funnel analysis
User needs	Kano Model

Multiple frameworks can be combined for complex problems.

Step 3: Data Collection and Analysis

Based on the analysis type, load the relevant reference files:

• Competitor analysis -> Load references/competitor-analysis.md

  • Use the 6-dimension framework (product, business model, market, company, operations, reputation)
  • Query enterprise data via Tianyancha MCP (see references/tool-usage.md)
  • Query app market data via Qimai (see references/tool-usage.md)

• User research -> Load references/user-research.md

  • Select research method based on goal (qualitative vs. quantitative)
  • Build user personas using the 3-dimension framework (demographic, behavioral, psychological)
  • Map user journeys with emotion curves and opportunity points
  • Segment users using RFM or lifecycle models

• Quantitative modeling -> Load references/data-modeling.md

  • Build metric systems (North Star metric -> core metrics -> process metrics)
  • Estimate market size using TAM/SAM/SOM or Fermi estimation
  • Calculate unit economics (LTV, CAC, payback period)
  • Analyze funnels, cohorts, and ROI
  • Perform sensitivity analysis on key variables

Step 4: Data Visualization

Load references/tool-usage.md (VisActor section) and generate charts:

Data relationship	Chart type	Tool
Trend over time	Line/area chart	VChart
Comparison	Bar chart	VChart
Composition	Pie/donut chart	VChart
Correlation	Scatter/bubble chart	VChart
Funnel conversion	Funnel chart	VChart
Retention analysis	Heatmap	VTable
Multi-dimensional	Radar chart	VChart

Chart rules:

• Title states the conclusion, not the data description
• Annotate data source and date below each chart
• Use professional color palette; Chinese stock convention: red = up, green = down
• Generate as standalone HTML with VisActor CDN for browser rendering

Step 5: Report Generation

Structure the final output as:

text

1. Executive Summary (3-5 key findings + top 3 recommendations)
2. Background & Methodology
3. Analysis (framework-driven, data-supported)
4. Key Findings (with visualizations)
5. Action Recommendations (prioritized table: P0/P1/P2 with timeline)
6. Data Sources & Limitations

Tool Integration

Tianyancha (Enterprise Data)

When enterprise information is needed (competitor background, financing, shareholders, IP, risk):

1. Check if tyc-mcp connector is connected (connector name: tyc-mcp Tianyancha)
2. If connected: call mcp__tyc-mcp__* tools to query enterprise data
3. If not connected: inform user to enable it in Connector Management, or use WebSearch to search Tianyancha public pages as fallback

Qimai (App Market Data)

When app market data is needed (downloads, rankings, reviews, ASO):

1. Use WebSearch to find Qimai data pages for the target app
2. Use WebFetch to extract data from public Qimai pages
3. Alternatively, accept user-provided Qimai export files (Excel/CSV)

VisActor (Charts)

Generate standalone HTML files with VisActor CDN for data visualization:

• VChart CDN: https://unpkg.com/@visactor/vchart/build/index.min.js
• VTable CDN: https://unpkg.com/@visactor/vtable/build/index.min.js
• Full code templates available in references/tool-usage.md

Information Quality Standards

1. Multi-source verification: Key data points verified by at least 2 independent sources
2. Source attribution: Every data point annotated with source and date
3. Fact vs. opinion: Objective data separated from analyst opinions
4. Timeliness: Prioritize data from the last 6 months
5. Confidence labeling: Mark data confidence as high/medium/low

Common Data Sources

Data type	Recommended sources
Industry reports	iResearch, QuestMobile, Aurora Mobile, IDC
Enterprise financing	Tianyancha, IT Juzi, Crunchbase
App market data	Qimai, SensorTower, App Annie
E-commerce data	Stardust, Mojing Market Intelligence
Macroeconomics	NBS, World Bank, IMF
Public company financials	CNINFO, Wind, East Money
Social media data	Newrank, WeIndex, Weibo Data Center

Bundled Resources

File	Purpose
references/analysis-frameworks.md	10 consulting frameworks: MECE, SCQA, Pyramid, SWOT, Porter's Five Forces, 3C, 4P, BMC, Hypothesis-Driven, Kano
references/competitor-analysis.md	Competitor analysis methodology: 6-dimension framework, selection strategy, comparison templates, SWOT deep-dive, report template
references/user-research.md	User research methods: persona building, journey mapping, need discovery, RFM segmentation, lifecycle staging, report template
references/data-modeling.md	Quantitative modeling: metric systems, TAM/SAM/SOM, unit economics, funnel analysis, cohort retention, ROI, forecasting
references/tool-usage.md	Tool integration guides: Tianyancha MCP, Qimai data, VisActor chart templates, web search strategies, data source directory

Changelog

v1.0.0

• Initial release
• 10 consulting frameworks (MECE, SCQA, Pyramid, SWOT, Porter's Five Forces, 3C, 4P, BMC, Hypothesis-Driven, Kano)
• 6-dimension competitor analysis methodology
• User research toolkit (personas, journey maps, RFM, lifecycle)
• Quantitative modeling (TAM/SAM/SOM, unit economics, funnel, cohort, ROI)
• Tool integration guides (Tianyancha, Qimai, VisActor)