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Find local business leads and send personalized cold emails

An n8n agent scrapes Google Maps for businesses, enriches leads with Owler and Apollo, writes personalized cold emails and logs leads in Google Sheets.

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Use case overview

An n8n agent scrapes Google Maps for businesses, enriches leads with Owler and Apollo, writes personalized cold emails and logs leads in Google Sheets.

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Reported experience

  1. What they did

    Two n8n workflows. The first takes a neighborhood and industry, scrapes Google Maps through Bright Data, and saves the raw leads to Google Sheets for review. The second finds each company's Owler profile through a Google Search dataset and scrapes it. It then cross-checks with Apollo, and GPT writes the email, subject and follow-ups. Leads are flagged qualified or disqualified.

  2. How it went

    The author reports over 5000 leads a day at a 98% success rate and better response rates than manual research. These figures are self-reported with no breakdown. Early emails read as generic.

  3. Worth knowing

    The author says per-lead cost is about $0.005 to $0.02. Getting good emails took repeated prompt tuning, and feeding GPT more company context (industry, size, details) was what fixed the generic tone.

Example prompts

Try with n8n
Build an n8n agent that finds [type of business] in [city or region] on Google Maps, enriches each lead with company and contact details from [Apollo or similar], and writes a short personalized cold email based on [my offer]. Log every lead and draft in a Google Sheet at [sheet link]. Don't send anything automatically; stop after [number] leads and show me the drafts for approval before any emails go out.

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