The Ultimate Yellow Pages Scraper Guide to More Leads

A Yellow Pages scraper is a tool or workflow that automatically collects public business listings from Yellow Pages sites and turns them into structured data you can use—think company names, phone numbers, addresses, websites, categories, hours, and more. Instead of copying and pasting hundreds of listings by hand, a scraper visits each results page, opens the individual business profiles, and extracts the fields you care about. The output is typically a CSV or Excel file that you can filter, sort, and feed into your CRM or outreach tools.

Used responsibly, Yellow Pages scraping helps marketers, local agencies, recruiters, and sales teams build targeted prospect lists faster and with better consistency than manual collection.

What Data Can a Yellow Pages Scraper Collect?

Depending on the market and the specific listing, you can usually gather:

Business name
Category / subcategory
Phone number
Address (street, city, state/province, ZIP/postal code)
Website URL
Rating / review count (if present)
Working hours
Short description or “About” text
Additional metadata (e.g., “Years in business,” attributes like “Wheelchair accessible,” etc., when available)

Important note about emails: Yellow Pages listings rarely show email addresses directly. If you need emails, your workflow typically includes visiting the business website found on the listing and then discovering contact emails there (or via a contact form). Keep your method compliant with anti-spam laws (more on this below).

How a Yellow Pages Scraper Works

Input your search
Choose a category/keyword (e.g., “plumbers,” “cafés,” “CPA firms”) and a location (city, state/province, or ZIP/postal code).
Navigate results pages
The scraper loads the search results page and iterates through pagination (page 1, 2, 3, …).
Open each business profile
For higher-quality data, it visits each listing’s detail page to capture additional fields not visible in the results grid.
Extract and normalize fields
It pulls text from the page into a structured format and standardizes things like phone formats or address components.
De-duplicate
If a business appears in multiple searches (e.g., neighborhood and city-wide), the scraper merges duplicates by matching phone, domain, or a normalized name+address key.
Export
Save your output to CSV/Excel/JSON and optionally push to CRM or sheets.

Why Use a Yellow Pages Scraper?

Speed: Build a list of hundreds or thousands of businesses in minutes.
Consistency: Standardized, structured data beats messy manual copy-paste.
Targeting: Filter precisely by category and location to focus on true prospects.
Research depth: Combine Yellow Pages data with your enrichment (e.g., website tech stack or social links) for smarter outreach.

Yellow Pages Scraper USA (yellowpages.com)

The US version (yellowpages.com) is rich in categories and metropolitan coverage. Here’s a sensible approach tailored to the U.S. market:

Recommended Workflow

Define your ICP
Decide on business type (e.g., “HVAC contractors”), geography (e.g., “Phoenix, AZ”), and any firmographic rules (e.g., “exclude big franchises”).
Run your search on yellowpages.com
Note the URL pattern and pagination. Your scraper should handle next-page links and occasional “More results” UI.
Go deeper into profiles
Many helpful fields—hours, website links, and descriptions—live on the business detail page. Scraping these improves accuracy.
Normalize US addresses
Standardize to Street | City | State | ZIP to support map tools and route planning.
Handle duplicates
In the U.S., duplicates can happen across neighborhoods and ZIP code variants. Match on domain + phone where possible.
Respect the site and the law
Implement rate limits (e.g., 1–3 seconds between requests), backoff, and a human-like crawl pattern.

Typical US CSV Header

Url,Title,category,rate,Phone,Address,Website,Years in Business,Quote,emails

Yellow Pages Scraper Canada (YellowPages.ca)

YellowPages.ca serves Canada’s provinces and bilingual regions. While broadly similar to the U.S. site, there are a few differences to plan for:

Canada-Specific Considerations

Bilingual fields: Some listings appear in English and French. Consider language detection or store original text.
Province normalization: Use official two-letter abbreviations (ON, QC, BC, AB, MB, SK, NS, NB, NL, PE, NT, YT, NU) and standardize Canadian postal codes (e.g., “M5V 2T6”).
Map links and directions: These can differ in structure—make sure your scraper follows the correct selector paths.
Compliance: If you plan email outreach in Canada, understand CASL (Canada’s Anti-Spam Legislation). It’s stricter than many other regimes and often requires express consent.

Typical Canada CSV Header

Url,Title,category,rate,Phone,Address,Website,Directions,Quote,emails

No-Code vs. DIY: How to Approach Scraping

Option A: No-Code / Low-Code Tools

Pros: Fast to start, user-friendly, often include built-in pagination and export to CSV/Excel.
Cons: Less control over edge cases, anti-bot challenges, or custom enrichment logic.

Option B: Browser Automation (Playwright/Selenium)

Pros: Flexible, closely simulates a human browser (better for dynamic content and CAPTCHAs).
Cons: Requires coding, dev time, and maintenance when the site changes.

Option C: HTTP + Parsing (Requests + Parsers)

Pros: Lightweight and fast when pages are simple.
Cons: Breaks easily if the site relies on JavaScript rendering.

Tip: For Yellow Pages US/Canada, browser automation tends to be more robust because pages can include dynamic elements and lazy-loaded content.

Handling Common Scraping Challenges

Pagination & “Load More”
Implement both classic numbered pagination and infinite scroll detection where needed.
Anti-Bot & CAPTCHAs
Use human-like delays, rotate residential or high-quality proxies if allowed, and consider headful browsing (not headless) to mimic real use. Never bypass security measures unlawfully.
Duplicates & Collisions
Create a unique key like normalized_name + normalized_address or combine domain + phone. Fuzzy-string matching helps with slight spelling differences.
Data Cleaning
- Normalize phone numbers to E.164 or a consistent local format.
- Split addresses into components.
- Strip tracking parameters from website URLs.
- Remove placeholder text (“Learn more,” “Directions”) from description fields.
Change Resilience
Write your selectors to be resilient (e.g., anchor by text labels where possible). Add monitors so you’re alerted if extraction rates drop—often a sign the site changed its layout.

Legal, Ethical, and Compliance Basics (Read This)

Scraping only publicly available information is a starting point—but it’s not the whole story. You are responsible for how you collect, store, and use data. Keep in mind:

Terms of Service: Always review the site’s ToS. If they forbid automated access, don’t scrape.
Robots.txt & Rate Limiting: Treat these as guardrails. Crawl politely and avoid overloading servers.
Privacy Laws: If your dataset includes personal data (even business emails can be personal in some jurisdictions), understand the rules where you operate and where your contacts live.
- USA: For email outreach, learn CAN-SPAM. For telemarketing/SMS, study TCPA and Do Not Call rules.
- Canada: CASL is strict about consent and identification requirements in commercial electronic messages.
Data Security: Store scraped data securely and honor deletion requests when appropriate.
Provenance: Keep a note of the source and date collected; this helps with audits and updates.

This is not legal advice—consult counsel for your use case.

Step-by-Step: Building a Niche Prospect List

Define scope
“Residential plumbers” in “Tampa, FL” or “Dental clinics” in “Toronto, ON.”
Run a pilot scrape
Pull 50–100 records to check field coverage, duplicates, and address accuracy.
Refine filters
Tighten category keywords (e.g., “cosmetic dentist” vs. “dentist”), and confirm the right city/province/state.
Scale up
Scrape all pages for your target area. Respect delays and backoff when pages load slowly.
Enrich (optional)
Visit website URLs to collect emails, social links, or services offered. Do this ethically, and follow local laws.
Clean & de-dupe
Normalize phones, unify address formats, and merge duplicates.
Export & use
Save to CSV/Excel and import into your CRM, Google Sheets, or marketing stack. Create views for “missing website,” “no hours listed,” etc., to drive follow-up tasks.

Practical Tips for Better Results

Use precise categories: “Property management” yields better relevance than “real estate.”
Segment by neighborhood: In dense cities, a neighborhood filter improves quality and reduces duplicates.
Don’t chase volume only: 300 high-fit leads beat 3,000 mixed ones.
Document your selectors: Future you (or your team) will thank you when you revisit or update the scraper.
Refresh quarterly: Listings change. A light rescrape every 60–120 days keeps your data current.

FAQs

Is scraping Yellow Pages legal?
It depends on the site’s Terms of Service, your jurisdiction, and how you use the data. Only collect publicly available info, follow the ToS, respect robots.txt, and comply with marketing and privacy laws. When in doubt, speak with a lawyer.

Can I get emails from Yellow Pages?
Usually not directly. You’ll typically collect the business website from the listing and then discover emails on the site or use a compliant contact method (e.g., forms). Always comply with CAN-SPAM (US) and CASL (Canada).

How many records can I scrape?
There’s no universal number. It depends on the category, city size, and your tooling. Start small, evaluate quality, then scale with careful rate limits.

What formats can I export to?
CSV and Excel are most common. JSON is useful for developers. Some workflows also sync directly to a CRM.

What’s different between the USA and Canada sites?
Address formats, province abbreviations, bilingual content in some regions, and compliance frameworks (CASL in Canada). Structurally, both sites are similar, but selectors and page elements can differ—test them separately.

Final Thoughts

A Yellow Pages scraper—when used responsibly—can be a powerful engine for local market research and targeted lead generation. Start with a clear niche, scrape politely, normalize your data, and stay compliant with relevant laws. For the USA, focus on accurate state/ZIP mapping and de-duplication across neighborhoods. For Canada, pay attention to bilingual content, province normalization, and CASL compliance in your outreach.

Public Scraper