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personalization-at-scale

Generate unique personalized first lines for hundreds of prospects using company news, LinkedIn activity, and mutual connections. Saves 10+ hours of manual research per campaign. Use when you need personalized outreach at volume.

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OneWave-AI/claude-skills
연동 도구LinkedIn
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포함된 파일(7)

  • SKILL.md2.4 KB
  • references/benchmarks.md1.8 KB
  • references/example-campaigns.md1.6 KB
  • references/fallbacks.md1.2 KB
  • references/output-template.md2.5 KB
  • references/patterns-by-type.md5.9 KB
  • references/research-sources.md1.5 KB

SKILL.md(원문)

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Personalization at Scale

Generate hundreds of unique, researched first lines in minutes instead of hours, making cold outreach feel warm.

Contents

  • references/research-sources.md - signal sources, personalization styles, quality standards
  • references/patterns-by-type.md - sample first lines and tables for each angle (congrats, observation, mutual connection, company news, hiring, tech stack, thought leadership, shared background)
  • references/fallbacks.md - role/stage/industry/competitor lines for prospects with no angle
  • references/output-template.md - full campaign deliverable structure
  • references/benchmarks.md - expected lift, A/B reference data, pro tips (do/don't)
  • references/example-campaigns.md - worked campaign examples by persona

Workflow

  1. Ingest the prospect list (CSV or pasted). Require First Name, Last Name, Title, Company; use LinkedIn URL, email, website, industry, size, and location when available.

  2. Confirm preferences: which personalization styles to prioritize (1-3), tone (professional, casual, direct, consultative), and any exclusions (recency cutoff, personal topics, sensitive subjects).

  3. Research each prospect across the sources in references/research-sources.md. Identify the strongest, most recent, verifiable angle per prospect.

  4. Match each prospect to its angle and draft from the matching pattern in references/patterns-by-type.md. For prospects with no angle, draft from references/fallbacks.md.

  5. Generate 2-3 first-line options per prospect, each with a confidence score (High/Medium/Low) and notes on alternative angles. Follow the structure in references/output-template.md.

  6. Quality-check the first 10 manually. Confirm each line is specific, recent, relevant, natural, and verifiable before scaling the batch.

  7. Export in the requested format: CSV with personalization columns, merge fields for the outreach tool (Outreach, Salesloft), individual drafts, or copy-paste blocks.

  8. Track response rates by personalization type and refresh personalizations every 30 days as activity changes.

See references/benchmarks.md for target success rates and references/example-campaigns.md for persona-specific approaches.

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