Skill: openlark/market-research-automation (version 1.0.0)

--- name: market-research-automation description: Market research automation skill. Mine user pain points from social media and analyze competitors. Applicable for market validation before product launch, user needs analysis, and competitor feature comparison. --- # 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 ```bash python3 scripts/market_researcher_tool.py research --market 'AI Writing Tools' ``` ### Scenario 2: Competitor Analysis ```bash python3 scripts/market_researcher_tool.py compete --products 'Jasper,Copy.ai,Notion AI' ``` ### Scenario 3: Generate Survey Questionnaire ```bash 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**: ```bash 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**: ```bash 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**: ```bash python3 scripts/market_researcher_tool.py survey --topic 'AI Writing Tools' -o survey.md ``` ## Output Format ### Market Research Report ```markdown # 📊 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 ```markdown # 🔍 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 ```markdown # 📋 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: ```bash pip install requests beautifulsoup4 pandas ``` ## References - [X/Twitter API](https://developer.x.com/en/docs/x-api) - User discussion data - [Google Trends](https://www.google.com/trends/) - Search trend analysis - [Full Market Research Agent Use Case](https://github.com/hesamsheikh/awesome-openclaw-usecases/blob/main/usecases/market-research-product-factory.md) ## 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)