Prompt
What's the best way to build a lead list from public websites?
Latest observation
The best approach is to build a targeted, compliant, and maintainable lead list rather than trying to scrape everything.
1) Define your ideal lead profile first
Before collecting anything, be specific about:
- Industry
- Company size
- Geography
- Job titles / functions
- Tech stack or buying signals
- Exclusions
This keeps the list high quality and reduces wasted effort.
2) Use public, legitimate sources
Common sources include:
- Company websites
- Public directories and association member lists
- Conference/exhibitor pages
- Job boards
- Press releases / news
- Government or public registry sites
- Social profiles that are publicly visible
- Review sites or marketplace listings
Prefer sources that clearly allow browsing and reuse. Review their terms of service and robots.txt where relevant.
3) Collect only useful fields
A practical lead list usually includes:
- Company name
- Website
- Industry/category
- Location
- Contact page or public email
- Phone number
- Key decision-maker name and role, if publicly listed
- Source URL
- Date found
- Notes / qualification tags
Avoid collecting more personal data than you need.
4) Use a repeatable workflow
A solid workflow looks like this:
- Find source pages that match your target criteria
- Extract company/contact details
- Normalize data into a spreadsheet or CRM
- Deduplicate records
- Enrich with firmographic data if needed
- Validate emails/phones
- Score and prioritize leads
- Refresh periodically
5) Automate carefully
If you need scale, use:
- Search queries
- RSS feeds
- Public APIs
- Scraping tools with rate limiting
- Browser automation only when allowed
Good practices:
- Respect site policies
- Rate limit requests
- Don’t bypass login walls, CAPTCHAs, or anti-bot systems
- Keep logs of source URLs
- Re-check data freshness regularly
6) Organize leads in a CRM or spreadsheet
At minimum, create columns for:
- Lead ID
- Company
- Contact name
- Title
- Phone
- Website
- Source
- Qualification status
- Last updated
7) Qualify before outreach
Not every found contact is worth pursuing. Score leads based on:
- Match to ICP
- Relevance of role
- Recent activity
- Company growth signals
- Geographic fit
8) Stay compliant
Depending on your region and use case, consider:
- GDPR / UK GDPR
- CCPA/CPRA
- CAN-SPAM
- Local anti-spam and privacy laws
- Website terms of service
If you’ll use the data for outreach, make sure you have a lawful basis and provide required notices/opt-out mechanisms.
A simple practical stack
For many teams:
- Sources: Google search + directories + company sites
- Capture: spreadsheet + browser bookmarks or a scraping script
- Cleanup: deduping and validation tools
- Store: CRM like HubSpot/Salesforce/Airtable
- Outreach: email platform with suppression lists and opt-outs
If you want, I can help you design a safe lead-generation workflow for your specific industry, or give you a sample spreadsheet template and a source list to start from.
Observation history
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How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.