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What I learned scraping Website Contact: schema, gotchas and the tooling that worked

DEV Community·Can Yılmaz·6 months ago
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#webscraping#apify#leadgen#contact#article
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I had a short window this week to evaluate Website Contact as a data source. Here is the condensed write-up of what the data looks like, what surprised me, and the bits of infrastructure that paid off.

The source

Website Contact Scraper Email, Phone & Social Media Extractor Extract emails, phone numbers, LinkedIn, Instagram, Twitter/X, Facebook, and YouTube links from any website automatically. The relevant questions for any new source are always: is the markup stable, is pagination sensible, and how aggressively does it rate-limit. For this one, all three answers are "good enough that you can build on it" -- which is honestly more than I can say for a lot of supposedly easy targets.

The schema

What you get back per record:

url -- url

rootDomain -- root domain

pageType -- page type

pageTitle -- page title

metaDescription -- meta description

emails -- emails

phones -- phones

socials -- socials

scrapedAt -- scraped at

Nothing exotic, which is exactly what you want from a feed.…

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