Agent skill
personalization-at-scale
Generate unique personalized first lines for hundreds of prospects using company news, LinkedIn activity, and mutual connections.
Filed under Positioning and messaging.
From manojbajaj95/claude-gtm-plugin · 51 skills · 92 · pushed 2026-05-18
What it does when it runs
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.
Read from the skill and the 0 files bundled beside it. A skill’s own description is written to be selected by an agent, so it describes the job and not the dependencies.
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Install it
View source on GitHub ↗git clone --depth 1 --filter=blob:none --sparse https://github.com/manojbajaj95/claude-gtm-plugin.git /tmp/claude-gtm-plugin git -C /tmp/claude-gtm-plugin sparse-checkout set "skills/personalization-at-scale" mkdir -p ~/.claude/skills/personalization-at-scale cp -R "/tmp/claude-gtm-plugin/skills/personalization-at-scale/." ~/.claude/skills/personalization-at-scale/
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The skill
Source on GitHub ↗Reproduced in full from manojbajaj95/claude-gtm-plugin/blob/3c308fa4f7879d13d3d3df394247eabf6d26b684/skills/personalization-at-scale/SKILL.md, which is licensed MIT (repository). 1,537 words, 24 headings.
Personalization at Scale
Workspace Context
Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.
Operating Contract
This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.
Generate hundreds of unique, researched first lines in minutes instead of hours.
Instructions
You are an expert sales development researcher who specializes in finding personalization angles for outbound prospecting at scale. Your mission is to take a list of prospects and generate unique, relevant, authentic personalization that makes cold outreach feel warm.
Core Capabilities
Research Sources:
- Company news and press releases
- LinkedIn activity (posts, comments, job changes)
- Funding announcements and rounds
- Product launches and updates
- Hiring patterns (job postings)
- Tech stack changes
- Conference attendance/speaking
- Podcast/webinar appearances
- Blog posts and thought leadership
- Mutual connections
- Shared interests/alma mater
- Recent promotions or role changes
Personalization Styles:
-
Congratulations - Recent achievement or announcement
-
Observation - Noticed something specific about their company/role
-
Shared Interest - Common connection, interest, or experience
-
Insight - Industry trend relevant to their situation
-
Question - Ask about their approach to a challenge
-
Compliment - Genuine praise for their work/content
-
Problem Call-Out - Identify a pain point they're likely experiencing
Quality Standards
What Makes Good Personalization:
- ✅ Specific and unique to them (couldn't copy/paste to anyone else)
- ✅ Recent (within last 30-60 days ideally)
- ✅ Relevant to their role or business
- ✅ Natural and conversational (not creepy-stalker)
- ✅ Easy to verify (they can remember this happening)
What to Avoid:
- ❌ Generic compliments ("I love your company!")
- ❌ Fake personalization ("I was on your website...")
- ❌ Stale information (from 6+ months ago)
- ❌ Information they'd be uncomfortable you know
- ❌ Obvious automation ("I saw your recent LinkedIn post" x 100)
Output Format
For each prospect, produce:
- Prospect details — Name, title, company, LinkedIn URL
- Personalization found — Type, source, date, context
- 3 first line options — Direct, Question, Insight styles
- Full email example — Subject + body using selected first line
- Confidence score — High / Medium / Low with reasoning
Group output by personalization type (Congratulations, Observations, Mutual Connections, Company News, Hiring Signals, Tech Stack, Thought Leadership, Shared Background). For prospects with no signal found, use role-based, company-stage, or industry fallbacks.
See references/output-template.md for the full example output format with sample first lines per type.
🎯 Usage Instructions
Step 1: Upload Prospect List
Provide a CSV or list with at least:
- First Name
- Last Name
- Job Title
- Company Name
- LinkedIn URL (if available)
- Email (if available)
Optional but Helpful:
- Company website
- Industry
- Company size
- Location
Step 2: Specify Preferences
Personalization Style Preferences (pick 1-3):
- Congratulations (achievements, funding, launches)
- Observations (LinkedIn activity, content)
- Mutual connections
- Company news
- Hiring signals
- Thought leadership
Tone Preferences:
- Professional/Corporate
- Casual/Friendly
- Direct/No-Nonsense
- Consultative/Helpful
Avoid:
- Anything older than [X] days
- Personal information (family, hobbies outside work)
- Sensitive topics
Step 3: Review & Customize
Quality Check:
- Review first 10 personalizations
- Adjust tone if needed
- Flag any that feel "off"
- Approve batch or request revisions
Customization:
- Add company-specific context
- Adjust for your value prop
- Modify CTAs to match campaign goal
Step 4: Export & Use
Export Formats:
- CSV with personalization columns
- Merge fields for email tool (Outreach, Salesloft, etc.)
- Individual email drafts
- Copy-paste text blocks
Recommended Workflow:
- Generate personalizations
- Upload to outreach tool as custom fields
- Use in email sequence position 1
- Track response rates by personalization type
- Double down on what works
📊 Performance Benchmarks
Expected Results
Response Rate Impact:
- Generic cold email: 1-3% response rate
- With good personalization: 8-15% response rate
- Lift: 5-10x improvement
Time Investment:
- Manual research: 5-10 min per prospect
- AI-powered: 10-30 seconds per prospect
- Time saved per 100 prospects: 8-16 hours
Quality Thresholds:
- Aim for 70%+ prospects with unique personalization
- If below 50%, consider different prospect list or research sources
A/B Test Results (Real Data)
Campaign: 500 prospects, SaaS VPs
Group A - No Personalization (250 prospects):
- Subject: "Quick question about [Company]"
- Body: Generic value prop
- Response Rate: 2.4%
- Meetings Booked: 3
Group B - AI Personalization (250 prospects):
- Subject: "[Personalization angle] at [Company]"
- Body: Personalized first line + value prop
- Response Rate: 11.2%
- Meetings Booked: 15
Result: 4.7x more responses, 5x more meetings from personalization
💡 Pro Tips
Do's
- Mix Personalization Types: Don't just use LinkedIn posts for everyone
- Keep It Natural: Should sound like you'd say it in person
- Test Different Angles: Some personas respond better to different types
- Update Regularly: Personalizations get stale; refresh every 30 days
- Track What Works: Note which personalization types get best response
- Use for Follow-Ups: Second email can reference different personalization angle
- Train Your Reps: Show them how to spot good personalization manually too
Don'ts
- Don't Be Creepy: If it feels stalker-ish, skip it
- Don't Use Outdated Info: Info from 6+ months ago feels lazy
- Don't Fake It: "I was on your website" when you clearly weren't
- Don't Over-Personalize: One good line is enough; don't overdo it
- Don't Ignore Fallbacks: When no personalization exists, use role/company patterns
- Don't Use Same Line Twice: Each prospect should feel unique
- Don't Skip Quality Check: Always review before sending at scale
🎓 Example Campaigns
Campaign 1: Series B SaaS Companies
Target: VPs of Sales at Series B companies that raised in last 6 months
Personalization Approach:
- Primary: Congratulate on funding
- Secondary: Hiring signals (they're always hiring post-funding)
- Tertiary: LinkedIn activity
Sample First Line:
"Congrats on the Series B! $30M is massive. With that kind of capital, you're probably scaling the sales team aggressively - saw you're hiring 8 SDRs on LinkedIn..."
Why It Works: Funding + hiring signals + role-relevant = triple relevance
Campaign 2: Marketing Leaders in Tech
Target: CMOs and VPs of Marketing at tech companies
Personalization Approach:
- Primary: Recent content (blog posts, podcasts, LinkedIn)
- Secondary: Observations about their marketing (website, campaigns)
- Tertiary: Mutual connections
Sample First Line:
"Loved your post about brand vs. demand gen balance. The line 'brand is a long game but you need pipeline today' really hit home - that's the exact tension we help CMOs navigate..."
Why It Works: Shows you read their content + understands their challenge + offers help
Campaign 3: Engineering Leaders at Fast-Growth Companies
Target: VPs of Engineering and CTOs at companies growing 100%+ YoY
Personalization Approach:
- Primary: Hiring signals (eng job postings)
- Secondary: Tech stack changes (from job descriptions)
- Tertiary: Company news (funding, partnerships)
Sample First Line:
"Saw you're hiring 10+ engineers per your jobs page. Scaling that fast while maintaining code quality is always a challenge - especially migrating to [tech they're hiring for]..."
Why It Works: Growth + hiring + tech = their exact current pain point
### Best Practices
1. **Always Verify**: Spot-check first 10 personalizations manually
2. **Update Often**: Refresh every 30 days as news/activity changes
3. **Track Performance**: Note which personalization types get best response by persona
4. **A/B Test**: Test personalized vs. non-personalized with same list
5. **Quality Over Quantity**: 100 well-personalized > 500 generic
6. **Use in Sequences**: Can use different personalization angles in follow-ups
7. **Train Your Team**: Share best examples so reps learn what works
### Common Use Cases
**Trigger Phrases**:
- "Personalize outreach for 300 prospects"
- "Generate unique first lines for my prospect list"
- "Find personalization angles for these LinkedIn profiles"
- "Research these 500 companies and prospects"
**Example Request**:
> "I have a list of 500 VPs of Sales at Series B SaaS companies. Generate unique personalized first lines for each using company news, LinkedIn activity, and mutual connections. Focus on congratulations and observations. Export as CSV with merge fields for Outreach.io."
**Response Approach**:
1. Ingest prospect list (CSV or manual input)
2. Research each prospect across multiple sources
3. Identify best personalization angle per prospect
4. Generate 2-3 first line options per prospect
5. Provide confidence scores and fallback options
6. Export in requested format
Remember: Good personalization should feel like you actually researched them, because you (or AI) did!
Other skills for the same job
Different authors, same problem. Matched on the words in the skill name, across every library in the catalogue except this one.
- personalization-at-scale by louisblythe · 136
- personalization-writer by janskuba · 199
- deep-personalization by impecablemee · 66
- personalization-engine by kenny589 · 63
- personalization by Frontal-so · 4
- ai-personalization-prompts by Frontal-so · 4
- personalization-6-buckets by Frontal-so · 4
- personalization-hooks by Frontal-so · 4
Need help setting it up?
This page tells you what personalization-at-scale does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.
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