Market Research Automation
Mine user pain points from social media and analyze competitors. Applicable for market validation before product launch, user needs analysis, and competitor feature comparison.
Trigger Conditions
- Market research
- Competitor analysis
- market research
- competitor analysis
- User research
- survey generation
- TAM SAM SOM
- Market size estimation
Core Capabilities
Capability 1: Market Sizing — TAM/SAM/SOM Three-Layer Model
Estimate the Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) for a target market.
Capability 2: In-Depth Competitor Analysis — Feature/Pricing/User Review Comparison Matrix
Compare multiple competitors across dimensions such as features, pricing, target users, strengths, and weaknesses.
Capability 3: Automatic Generation of User Interview Frameworks and Survey Questionnaires
Automatically generate structured user survey questionnaires based on the research topic.
Usage Workflow
Scenario 1: Market Sizing Research
python3 scripts/market_researcher_tool.py research --market 'AI Writing Tools'
Scenario 2: Competitor Analysis
python3 scripts/market_researcher_tool.py compete --products 'Jasper,Copy.ai,Notion AI'
Scenario 3: Generate Survey Questionnaire
python3 scripts/market_researcher_tool.py survey --topic 'AI Writing Tools'
Command Details
research - Market Research
Purpose: Estimate market size and generate a TAM/SAM/SOM analysis report.
Parameters:
--market: Market name (required)--output, -o: Output file path (optional, defaults to console output)
Example:
python3 scripts/market_researcher_tool.py research --market 'AI Writing Tools' -o report.md
compete - Competitor Analysis
Purpose: Compare features, pricing, and user reviews of multiple competitors.
Parameters:
--products: List of competitors, comma-separated (required)--output, -o: Output file path (optional)
Example:
python3 scripts/market_researcher_tool.py compete --products 'Jasper,Copy.ai,Notion AI,ChatGPT' -o compete.md
survey - Generate Survey Questionnaire
Purpose: Automatically generate a structured user survey questionnaire.
Parameters:
--topic: Research topic (required)--output, -o: Output file path (optional)
Example:
python3 scripts/market_researcher_tool.py survey --topic 'AI Writing Tools' -o survey.md
Output Format
Market Research Report
# 📊 Market Research Automation Report
**Generated on**: YYYY-MM-DD HH:MM
## Key Findings
1. [Key Finding 1]
2. [Key Finding 2]
3. [Key Finding 3]
## Market Size Analysis (TAM/SAM/SOM)
| Metric | Value | Description |
|------|------|------|
| TAM | $XXX Billion | Total Addressable Market |
| SAM | $YYY Billion | Serviceable Available Market |
| SOM | $ZZZ Billion | Serviceable Obtainable Market |
## Actionable Recommendations
| Priority | Recommendation | Expected Outcome |
|--------|------|----------|
| 🔴 High | [Specific recommendation] | [Quantified expectation] |
Competitor Analysis Report
# 🔍 In-Depth Competitor Analysis Report
## Competitor Comparison Matrix
| Product | Pricing | User Rating | Target User | Key Strengths | Main Weaknesses |
## Competitive Strategy Recommendations
| Priority | Recommendation | Expected Outcome |
User Survey Questionnaire
# 📋 User Survey Questionnaire
## Basic Information
**Q1. What is your current job role?**
○ Product Manager ○ Marketing ○ Content Creation ...
## Current Usage
**Q2. How often do you use AI writing tools?**
○ Multiple times daily ○ Once daily ...
## Pain Points and Needs
**Q3. What feature would you most like to see improved in AI writing tools?**
________________________________________
Prerequisites
Install Python dependencies before first use:
pip install requests beautifulsoup4 pandas
References
- X/Twitter API - User discussion data
- Google Trends - Search trend analysis
- Full Market Research Agent Use Case
Notes
- All analysis is based on data obtained by the script; data is not fabricated.
- Missing data fields are marked "Data Unavailable" rather than guessed.
- It is recommended to combine with human judgment; AI analysis is for reference only.
- The current version uses mock data and can be extended to real API calls.
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