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personalization-at-scale

personalization-at-scale

github.com/onewave-aiMarketing & growth398342 installsUpdated 1w ago
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About personalization-at-scale

A personalization skill for outreach teams that researches prospect lists and drafts tailored opening lines at scale. It provides several options and confidence notes per prospect, with exports for campaigns and drafts.

Key features

  1. 01Research prospects from a list
  2. 02Draft multiple personalized openers
  3. 03Add confidence and alternative angles
  4. 04Export CSVs, drafts, or copy-paste blocks
  5. 05Check relevance and verifiability

Use cases

  1. 01Create cold-email openers in batches
  2. 02Tailor outreach by role or industry
  3. 03Export personalized campaign content
  4. 04Compare response rates by personalization type

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/onewave-ai/claude-skills --skill personalization-at-scale

After installing, type/personalization-at-scalein Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
benchmarks.md
example-campaigns.md
fallbacks.md
output-template.md
patterns-by-type.md
research-sources.md

Details

From the project README

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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