Prompt

What's the best way to build a lead list from public websites?

Latest observation

Jul 15, 2026 · OpenAI APIWeb search: off

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:

  1. Find source pages that match your target criteria
  2. Extract company/contact details
  3. Normalize data into a spreadsheet or CRM
  4. Deduplicate records
  5. Enrich with firmographic data if needed
  6. Validate emails/phones
  7. Score and prioritize leads
  8. 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
  • Email
  • 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.