Prompt

How do I get address and phone number data from business listing sites?

Technology / API Platforms1 observationLast seen Oct 4, 2026

Latest observation

Oct 4, 2026OpenAI APIWeb search: off

The easiest way is to use a combination of search, extraction, and cleanup—but how you do it depends on the site and whether it allows automated access.

1) Start with allowed sources

Before collecting data, check:

  • the site’s Terms of Service
  • robots.txt
  • whether it offers an API or export feature

If there’s an API, that’s usually the safest and cleanest option.

2) Common ways to collect address and phone data

A. Manual collection

Good for small lists.

  • Search the business listing site
  • Open each listing
  • Copy fields like:
    • business name
    • address
    • phone number
    • website
  • Paste into a spreadsheet

B. Web scraping

Good for larger volumes, if permitted. Typical process:

  1. Identify the listing page structure
  2. Extract fields from HTML
  3. Save to CSV/Excel/database
  4. Normalize and deduplicate

Common tools:

  • Python + BeautifulSoup for static pages
  • Scrapy for larger scraping projects
  • Selenium/Playwright for pages loaded by JavaScript

C. Use public APIs / data providers

Some listing platforms and business directories provide:

  • business search APIs
  • place/location APIs
  • partner feeds

This is usually more reliable than scraping.

3) What fields to collect

A practical dataset often includes:

  • business name
  • street address
  • city
  • state/province
  • postal code
  • country
  • phone number
  • website
  • category
  • source URL

4) Data quality tips

Business listing data can be messy, so:

  • normalize phone numbers into one format
  • split addresses into components
  • remove duplicates
  • verify against the official business website when possible
  • watch for outdated listings

5) Example workflow

If you’re doing this at scale:

  1. Get a list of business names or categories
  2. Search the listing site
  3. Extract address/phone
  4. Clean the data
  5. Store in a spreadsheet or database
  6. Re-check periodically for updates

6) Important caution

Avoid collecting or using data in ways that violate:

  • site terms
  • privacy laws
  • anti-bot restrictions

If you want, I can show you:

  • a Python scraping example
  • a no-code approach
  • or a specific method for one listing site.

Observation history

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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.

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