How to scrape Yellow Pages?

 Scraping Yellow Pages helps businesses collect essential contact information like company names, phone numbers, addresses, websites, and reviews from various industries. To begin, inspect the Yellow Pages website using browser developer tools to identify HTML tags containing the desired data, such as business names in <h2> or <a> tags and phone numbers in <p> tags.

Use Python tools like BeautifulSoup, Scrapy, or Selenium to automate the extraction process. BeautifulSoup is ideal for static content, while Selenium works better for dynamic, JavaScript-loaded pages. Send requests using the Requests library, parse the HTML structure, and save the collected data into CSV, Excel, or JSON formats for further use.

Since Yellow Pages employs anti-scraping measures, use rotating proxies, user-agent rotation, and delays to prevent being blocked. You can also integrate CAPTCHA-solving services if required.

For faster, hassle-free, and large-scale data extraction, use Web Scraping HQ’s Yellow Pages Scraper. It automatically gathers verified business data, cleans duplicates, and delivers structured results without coding — saving hours of manual work.

✅ Tip: Always comply with Yellow Pages’ terms of service and use scraped data ethically for lead generation, business analysis, and marketing research.

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