Inbound leads land enriched with firmographics, website intel, and a personalized first-touch — before a human sees them.
Speed-to-lead matters, but so does personalization. The rep who responds in 5 minutes with a generic 'thanks for reaching out' loses to the rep who responds in 7 minutes referencing the prospect's company news. An enrichment agent fires the moment a form is submitted: pulls firmographics, scrapes the company website, summarizes their About page, and generates a personalized opener — all before the rep opens the lead.
Webhook from your form (Typeform, native HTML, HubSpot) fires the n8n / Lindy workflow with the lead's email and company domain.
Hit Clearbit / Apollo / People Data Labs for firmographics: industry, size, revenue, tech stack, location. Cache results to avoid repeat API costs.
Use Firecrawl or Browserless to pull the homepage + About page. Feed to GPT-4 with prompt: 'Summarize what this company does in one sentence and identify one likely pain point that maps to [our service].'
Prompt: 'Draft a 3-sentence reply email. Sentence 1: thank + acknowledge their inquiry. Sentence 2: one specific reference to their company drawn from the summary. Sentence 3: a concrete next step.'
Create the CRM record with all enrichment data. Send the rep a Slack DM with a ready-to-send draft email and a one-line context brief. Rep reviews, hits send.
Tag each draft with 'sent_unedited', 'sent_with_edits', 'rejected'. Use this signal to keep tuning the prompt — high edit rate means the model is missing something obvious.
Use these templates as-is or customize for your business.
You are analyzing a company website to brief a sales rep. Input: {{scraped_html_text}}. Output JSON: {"company_one_liner": "What they do in one sentence.", "likely_pain_point": "One specific pain point that maps to our offering of [your service].", "recent_signal": "Anything time-sensitive — funding, hiring, launch, etc. Empty string if none."}Draft a 3-sentence email reply to a new inbound lead. Use this brief: {{summary_json}}. Lead context: {{form_submission}}. Constraints: sentence 1 = thank + acknowledge specific thing they asked. Sentence 2 = ONE specific, non-generic reference to their company drawn from the brief. Sentence 3 = propose a concrete next step (a 15-minute call, a specific resource). No exclamation marks. Sound like a human who actually read their site.🆕 *New lead: {{first_name}} @ {{company}}*
• What they do: {{company_one_liner}}
• Likely pain: {{likely_pain_point}}
• Signal: {{recent_signal}}
• Their ask: {{form_message}}
📩 *Draft reply ready in inbox* — review + send.Get a new AI workflow every week. Prompts, tool stacks, and ROI math included.
Single agent with function-calling: one LLM with a defined toolbox (CRM, calendar, knowledge base) decides which tool to invoke at each turn. Easiest to debug; appropriate for most well-scoped business workflows.
Learn the agentic glossary →Where this workflow tends to break in production — and what to put in place before you ship it.
Enrichment API miss leaves blank fields
Mitigation: Fallback to LLM summary of the domain's homepage if structured data is missing.
Draft sounds AI-generated
Mitigation: Hard rules: no 'Hope this email finds you well', no 'I came across'; reject drafts containing them.
Skip if your inbound volume is under 5 leads/week — manual personalization is faster. Also skip for transactional/local-service inquiries where speed matters more than personalization (e.g., emergency plumbing).
A phased approach to get this workflow running and delivering ROI.
Days 1–30
Foundation
Days 31–60
Optimization
Days 61–90
Scale
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