Deep Research & Web Scraping With OpenClaw
Master OpenClaw's research capabilities. Web scraping, data extraction, competitive analysis, trend monitoring, and research synthesis.
Prerequisites
OpenClaw installed and running · Basic understanding of data analysis
Deep Research & Web Scraping With OpenClaw
Research is a time-killer. Market analysis, competitor tracking, trend monitoring, lead research, pricing analysis—all require hours of manual web browsing. OpenClaw automates the entire research process. What takes a human 8 hours takes OpenClaw 5 minutes.
Why Automate Research?
Manual research workflow:- Google search topic (5 min)
- Skim articles and websites (30 min)
- Take notes (20 min)
- Organize findings (15 min)
- Create report (20 min)
- Total: 90 minutes
- Request: "Research X and summarize"
- OpenClaw searches, scrapes, synthesizes
- Receive comprehensive report (5 min)
- Total: 5 minutes
Installing Research Skills
- Go to Settings > Skills Marketplace
- Install these skills:
- Web Scraper (free): Extract data from websites
- Research Synthesizer (free): Combine findings into reports
- Trend Analyzer (free): Monitor emerging trends
- Configure in Settings > Skills > Installed
Basic Research: Ask and Receive
Simple Research Request
Request: "Research the current state of AI safety and give me the top 5 key concerns."
Response:
AI Safety: Top 5 Key Concerns (March 2026)
- Alignment Problem: How do we ensure AI systems pursue intended goals?
Sources: 12 academic papers, 8 expert interviews
Summary: Leading researchers believe alignment is the #1 existential risk
- Adversarial Robustness: Can AI systems be fooled/manipulated?
Sources: 5 recent studies
Summary: Current models vulnerable to adversarial attacks; fixes in progress
- Bias and Fairness: Do AI systems amplify human biases?
Sources: 8 studies on real-world deployments
Summary: Bias varies by domain; technical solutions exist but rarely deployed
- Interpretability: Can we understand AI decisions?
Sources: 10 papers on explainable AI
Summary: Current methods provide limited interpretability; area of active research
- Scalable Oversight: How do we monitor increasingly powerful AI systems?
Sources: 6 papers, 4 industry reports
Summary: No consensus solution yet; multiple approaches being explored
Advanced Research: Structured Data Extraction
Competitive Analysis
Automatically gather competitor intelligence:
Automation: "Monthly Competitor Analysis"
Trigger: First day of month at 9:00 AM
Target: Top 5 competitors in your space
Actions:
1. Visit competitor websites
2. Extract:
- Pricing (with tier details)
- Feature list
- Marketing messaging
- Recent announcements
- Team changes (from LinkedIn)
- Customer reviews (from G2, Capterra)
3. Analyze:
- Pricing trend (up/down/stable)
- Feature additions
- Marketing strategy changes
- Competitive positioning shifts
4. Generate comparison chart:
Your Product vs Competitor A,B,C,D
5. Provide recommendations:
- Feature gaps you should fill
- Pricing opportunities
- Market positioning changes
6. Send report
Pricing Intelligence
Monitor competitor pricing automatically:
Automation: "Weekly Competitor Pricing Check"
Trigger: Every Monday at 8:00 AM
Actions:
1. Visit competitor pricing pages (5 competitors)
2. Extract current pricing for each tier
3. Compare to last week
4. Identify changes:
- Any competitor raised prices? By how much?
- New tier created?
- Feature changes?
5. Report:
"Competitor A lowered Standard tier by 10% (now $49/mo, was $54/mo)"
"Competitor B added Enterprise tier"
"Market average for basic tier: $39, Premium: $79"
6. Recommendations:
- Should you adjust pricing?
- Opportunities to gain market share?
Lead Research
Automatically research potential sales leads:
Automation: "Prospect Deep Research"
Trigger: New lead added to CRM from website
Actions:
1. Company:
- Get company info (size, funding, growth)
- Find recent news and press releases
- Identify growth stage (startup, scaling, mature)
- Get decision maker info
2. Individual prospect:
- LinkedIn profile analysis
- Find email address
- Identify role and background
- Find recent activity (posts, engagement)
3. Company-specific research:
- Recent funding rounds
- Market they're targeting
- Problems they likely face
4. Generate personalized outreach:
"Hi [Name], I noticed [Company] raised $[amount] for [market].
Our product helps [solve specific problem they face]."
5. Add to CRM with all research attached
Scraping Specific Data Types
E-commerce Price Tracking
Monitor product prices across retailers:
Automation: "Daily Price Comparison"
Trigger: Daily at 7:00 AM
Products: Apple AirPods, Sony Headphones, Beats Studio
Actions:
1. Scrape price from: Amazon, Best Buy, Target, B&H Photo, etc.
2. Track changes from yesterday
3. Identify lowest price
4. Find deals (price drops > 5%)
5. Report:
"Product: Apple AirPods Pro
Prices Today:
- Amazon: $229 (↓$10 from yesterday)
- Best Buy: $249 (→ no change)
- Target: $239 (→ no change)
Best Deal: Amazon at $229"
6. Alert if price drops significantly
Real Estate Monitoring
Track properties and market trends:
Automation: "Weekly Real Estate Market Report"
Trigger: Every Sunday at 10:00 AM
Target: Properties in your target neighborhoods
Actions:
1. Scrape listings from Zillow, Redfin, MLS
2. Extract:
- New listings
- Price changes (down = opportunity)
- Days on market
- Sold prices (for valuation)
3. Market analysis:
- Average price per square foot
- Average days to sell
- Price trend (up/down)
- Inventory level (tight/balanced/loose)
4. Opportunity identification:
"3 new listings in target area this week
1 listing price dropped 8% (potential negotiation)
Average sold price: $450k, avg time: 12 days"
5. Send report with recommendations
Job Market Research
Monitor salary trends and job markets:
Automation: "Monthly Job Market Analysis"
Trigger: First Monday of month at 9:00 AM
Role: Data Scientist, Location: San Francisco Bay Area
Actions:
1. Scrape job sites (LinkedIn, Glassdoor, Indeed, etc.)
2. Extract:
- Job count (demand indicator)
- Salary ranges
- Required skills
- Company size breakdown (startup vs enterprise)
3. Trend analysis:
- Job count increasing or decreasing?
- Salary trend
- Most demanded skills
4. Insights:
"Data Scientist roles (SF Bay):
- Total open: 847 (↑12% vs last month)
- Avg salary: $165k (↑3%)
- Top skills: ML, Python, TensorFlow, SQL
- Top employers: Google, Meta, Apple, OpenAI
Market status: Candidate's market (high demand)"
Trend Monitoring & Alerts
Industry Trend Detection
Automatically detect and report emerging trends:
Automation: "Weekly Industry Trend Report"
Trigger: Every Friday at 4:00 PM
Industry: AI and Machine Learning
Actions:
1. Monitor: News sites, Twitter, Reddit, HN, academic papers
2. Identify emerging topics:
- Spike in mentions? (indicates new trend)
- Sentiment analysis (positive/negative)
- Expert engagement level
3. Top 3 trends:
"Trend 1: Multimodal AI - 847 mentions this week (↑340% vs last week)
Sentiment: Positive
Key players: OpenAI, Google, Meta
Relevance: High (directly affects your industry)
Trend 2: AI regulation - 623 mentions (↑12%)
Sentiment: Mixed
Key topic: EU AI Act implementation
Trend 3: Open source LLMs - 512 mentions (stable)
Sentiment: Positive
Momentum: Growing (sustained interest)"
4. Send with recommendations:
"Multimodal AI trend accelerating. Customers likely asking about multimodal features.
Consider adding to product roadmap."
Competitor Intelligence Alerts
Real-time alerts when competitors do something significant:
Automation: "Competitor Intelligence Alerts"
Trigger: New announcement, funding, or major news about competitors
Actions:
1. Monitor: Press releases, Twitter, LinkedIn, news
2. Alert types:
- Funding round (amount, valuation, investors)
- New product launch
- Leadership changes
- Price changes
- Partnerships
3. Immediate notification:
"🚨 Competitor Alert:
Company: TechCorp
Event: Series B Funding - $25M
Lead: Sequoia Capital
Implication: They have 2+ years of runway, likely aggressive expansion
Action: Review your go-to-market strategy"
Research Report Generation
Comprehensive Market Report
Generate a complete market analysis report:
Automation: "Quarterly Market Research Report"
Trigger: Last day of each quarter at 5:00 PM
Market: SaaS Project Management Tools
Actions:
1. Research Phase:
- Market size (and growth rate)
- Top players and market share
- Pricing analysis
- Feature comparison
- Customer reviews analysis
- Industry trends
2. Analysis Phase:
- Growth opportunities
- Market gaps
- Emerging features
- Customer pain points
3. Report Generation:
- Executive summary
- Market overview
- Competitive landscape
- Trend analysis
- Opportunities & threats
- Recommendations
4. Format:
- PDF with charts
- Executive summary (2 pages)
- Detailed findings (8-10 pages)
- Data appendix
5. Distribution:
- Send to leadership
- Add to knowledge base
- Share with team
Academic & Technical Research
Literature Review Automation
For researchers and students—automatically gather and summarize papers:
Automation: "Weekly Literature Review"
Trigger: Every Sunday at 6:00 PM
Topic: Neural Network Interpretability
Actions:
1. Search academic databases:
- arXiv
- IEEE Xplore
- Google Scholar
- ResearchGate
2. Filter by:
- Publish date (past week)
- Citation count (relevance)
- Relevance score (NLP-based)
3. For each paper:
- Extract title, authors, abstract
- Get full text (if available)
- Generate summary (1 paragraph)
- Extract key findings
- Identify datasets/methods used
4. Organize by relevance:
- Top 3 most relevant papers (detailed summaries)
- Top 10 other papers (brief summaries)
- Emerging themes
5. Report:
- "This week's research highlights"
- Key methodologies trending
- Recommended papers to read
Data Extraction & Cleaning
Structured Data Extraction
Extract unstructured web data into structured format:
Automation: "Extract Product Listings"
Trigger: Daily at 9:00 AM
Target: Ecommerce site (any site)
Actions:
1. Visit target site
2. Extract all product listings:
- Product name
- Price
- Rating
- Number of reviews
- Category
- In stock status
- Image URL
3. Clean data:
- Normalize prices (remove currency symbols)
- Parse ratings (5.0 format)
- Categorize products consistently
4. Export formats:
- CSV
- JSON
- Excel with charts
5. Store in database for analysis
Legal & Ethical Considerations
Scraping Responsibly
Always check website terms of service:- Some sites explicitly forbid scraping
- Respect robots.txt file
- Don't overload servers with requests
- Cache results when possible
- Better than scraping
- More reliable
- Legally protected
- Better data quality
- Public announcements ✓ OK to scrape
- Government data ✓ OK to scrape
- Behind login walls ✗ Don't scrape
- Copyrighted content ⚠ Be cautious
Troubleshooting Research Automations
Scraping Fails or Returns Empty
- Website may have changed HTML structure
- Website may have anti-scraping measures
- Solution: Contact web scraper skill developer for update
- Alternative: Use official API if available
Data Quality Issues
- Verify extracted data matches website visually
- Check for data cleaning issues (formatting)
- Review sample data before running at scale
Slow Performance
- Reduce number of sites being scraped simultaneously
- Increase update interval (less frequent scraping)
- Archive old data (free up database space)
Frequently Asked Questions
Q: Is web scraping legal?A: Legally gray area. Scraping public data is generally OK; copyrighted content is risky. Always check terms of service. When in doubt, use official APIs.
Q: Will scraping get me blocked by websites?A: Respectful scraping won't. Don't hammer sites with requests, cache results, and respect robots.txt.
Q: Can I scrape behind-login content?A: Technically yes, but legally risky. Better to request official API access or data.
Q: How often should I scrape data?A: Depends on data volatility. Prices: daily. Job listings: daily. Company news: daily. Real estate: weekly. Adjust based on need.
Q: What format should I use for scraped data?A: CSV for spreadsheets, JSON for APIs, SQL database for complex data. OpenClaw supports all formats.
Next Steps
Now you're gathering intelligence at scale. Next, build custom automations:
- Build Your First Custom Skill — Create custom research tools
- Business Operations — Use research in sales and operations
- Security Best Practices — Secure sensitive research data