Lead Scraping Workflows
Find and capture fresh leads automatically from websites, directories, and social platforms, then clean, enrich, and route them to your CRM or sheets so your team can follow up fast.
📊 About Lead Scraping
How does Lead Scraping automation work?
A typical workflow starts with a source, like a directory URL list, Google Search results, or an Apify/Bright Data actor. It then fetches pages, extracts fields (company, role, location, email when available), and cleans the data so it’s consistent. Next, it deduplicates and enriches records (for example, adding industry or a short company summary using OpenAI). Finally, it routes leads into Airtable or HubSpot and alerts you in Slack so follow-up happens right away.
Do I need technical skills to automate Lead Scraping?
Usually, no. Most Flowpast workflows are plug-and-play: connect your accounts, paste a few URLs or keywords, and you’re live.
How much time can automation save for Lead Scraping?
Honestly, it can save about 2 hours a day if you’re doing manual research, copy/paste, and cleanup. Automation handles the repetitive parts: collecting results, extracting fields, standardizing columns, and removing duplicates. You still choose your targeting and review quality, which is where your judgment matters. Many teams also see faster speed-to-lead because new prospects arrive in the CRM continuously instead of in weekly batches.
What do I need to get started with Lead Scraping workflows?
You’ll need an n8n workspace (cloud or self-hosted) and at least one destination to store leads, like Airtable or HubSpot. For many setups, you also connect a scraper such as Apify or Bright Data, plus an email or messaging tool for notifications. Some workflows ask for a list of search terms, locations, or seed URLs to target. If you want AI enrichment, add an OpenAI key; it’s optional, but it makes lead notes and categorization much cleaner.
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