AI Email Personalization at Scale Workflow

Steps

1. 1

   Prospect Data Enrichment

   For each prospect in your list, gather: company website, recent LinkedIn posts, job title, company size, and any public projects or news.

   Data sources:\n- LinkedIn profile (title, posts, activity)\n- Company website (about page, recent news)\n- Google News (company mentions)\n- Industry publications

2. 2

   AI Research Summary

   Feed prospect data to AI with prompt: Summarize this persons role and likely pain points in 2 sentences. What would make them respond to a cold email about [your product]?

3. 3

   Opening Line Generation

   AI generates unique opening line referencing something specific about the prospect. Must feel hand-written, not templated.

   Good opening lines:\n- Reference a specific LinkedIn post they made\n- Mention a project their company completed\n- Note a challenge common to their exact role\n- Comment on their company growth/news\n\nBad: Hi [Name], I hope this finds you well

4. 4

   Value Prop Matching

   Based on prospect profile, AI selects the most relevant value proposition from your library. Different angles for different roles/industries.

   Pro tip: A purchasing manager cares about cost savings. An operations manager cares about reliability. Same product, different angle.

5. 5

   Email Assembly

   Combine: personalized opening + matched value prop + standard CTA. Review for quality. Flag any that feel generic for manual rewrite.

6. 6

   Quality Gate

   Human reviews 10% sample for quality. If >80% pass, approve batch. If not, adjust AI prompts and regenerate. Never send without spot-checking.

Tools Required