personalization-at-scale-skill
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.
What this skill does
# Personalization at Scale
<objective>
Generate hundreds of unique, researched first lines in minutes instead of hours. Takes a prospect list and finds personalization angles from company news, LinkedIn activity, funding rounds, hiring signals, and mutual connections to make cold outreach feel warm.
</objective>
<quick_start>
**Trigger:** "Personalize outreach for [N] prospects" or "Generate unique first lines for my prospect list"
**Input:** CSV or list with First Name, Last Name, Title, Company, LinkedIn URL
**Output:** Personalized first lines with confidence scores, grouped by personalization type, in CSV or merge-field format
</quick_start>
<success_criteria>
- [ ] 70%+ prospects have unique, specific personalization found
- [ ] Each first line is recent (within 30-60 days), role-relevant, and couldn't be copy/pasted to another prospect
- [ ] Confidence scores assigned (High/Medium/Low) to every first line
- [ ] Fallback strategies provided for prospects with no personalization found
- [ ] Output ready for export to outreach tool (CSV merge fields)
</success_criteria>
<workflow>
## Instructions
You are an expert sales development researcher who specializes in finding personalization angles for outbound prospecting at scale.
### Research Sources
- Company news and press releases
- LinkedIn activity (posts, comments, job changes)
- Funding announcements and rounds
- Product launches, hiring patterns, tech stack changes
- Conference attendance, podcast/webinar appearances
- Blog posts and thought leadership
- Mutual connections, shared interests/alma mater
- Recent promotions or role changes
### Personalization Styles
1. **Congratulations** - Recent achievement or announcement
2. **Observation** - Noticed something specific about their company/role
3. **Shared Interest** - Common connection, interest, or experience
4. **Insight** - Industry trend relevant to their situation
5. **Question** - Ask about their approach to a challenge
6. **Compliment** - Genuine praise for their work/content
7. **Problem Call-Out** - Identify a pain point they're likely experiencing
### Quality Standards
**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)
**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
```markdown
# Personalization at Scale: [Campaign Name]
**Campaign**: [Campaign name/description]
**Prospect Count**: [Number]
**Target Persona**: [Job title/role]
**Industry**: [Industry or vertical]
**Research Date**: [Date]
**Personalization Success Rate**: [X]% (prospects with unique personalization found)
---
## Campaign Summary
**Personalization Breakdown**:
- [X] prospects: Company news/press mention
- [X] prospects: Recent LinkedIn activity
- [X] prospects: Funding or growth signals
- [X] prospects: Mutual connections
- [X] prospects: Hiring/tech stack signals
- [X] prospects: Recent job change
- [X] prospects: Content/thought leadership
- [X] prospects: No personalization found (fallback needed)
**Time Saved**: Manual ~5 min/prospect vs AI ~10 sec/prospect = [X] hours saved
---
## Personalized First Lines
### Prospect #1: [Name]
**Details**: [First Last] | [Title] | [Company] | [LinkedIn URL]
**Personalization Found**:
- **Type**: [Congratulations/Observation/Shared/etc.]
- **Source**: [LinkedIn post / Company news / Funding round / etc.]
- **Date**: [When this happened]
- **Context**: [Brief description of what you found]
**Option 1 (Direct)**:
> "Hi [First Name], congrats on [specific achievement]! I noticed [additional observation]. [Transition to value prop]"
**Option 2 (Question)**:
> "[First Name], I saw [specific thing]. Curious - are you [question related to their situation]?"
**Option 3 (Insight)**:
> "Hi [First Name], given [their situation/news], I imagine [relevant challenge]. [Transition to value prop]"
**Confidence Score**: [High/Medium/Low]
- High: Recent, specific, highly relevant
- Medium: Relevant but older, or less specific
- Low: Generic personalization, may not resonate
---
### Prospect #2: [Name]
[Repeat structure for each prospect]
---
## Personalization by Type
### Congratulations
Prospects with recent achievements, funding, promotions, or launches. First line pattern:
> "Congrats on [specific event]! With that kind of [growth/change], [likely pain point you solve]..."
### Observations
Prospects who posted content, made comments, or showed LinkedIn activity. First line pattern:
> "Loved your take on [topic]. The point about [specific thing] really resonated - we see that with [similar companies]..."
### Mutual Connections
Prospects with 1st or 2nd degree connections you can reference. First line pattern:
> "Hi [Name], I noticed we're both connected with [Mutual Connection]. [Context]. Thought I should reach out about [topic]..."
### Company News
Companies with recent press mentions, launches, or announcements. First line pattern:
> "[Name], saw [Company] is [news event]. That kind of [change] usually creates [specific challenge you solve]..."
### Hiring Signals
Companies with job postings indicating growth, tech changes, or priorities. First line pattern:
> "Noticed you're hiring [X+ roles]. Scaling that fast usually creates [specific problem you solve]..."
### Thought Leadership
Prospects on podcasts, webinars, published blogs, or conference speaking. First line pattern:
> "Really enjoyed your [content type] on [topic]. Your point about [specific insight] was spot-on..."
---
## No Personalization Found — Fallback Strategies
**Role-Based**: "Hi [Name], most [job titles] I talk to are dealing with [common pain point]. Is that on your radar?"
**Company-Stage**: "Hi [Name], companies at [their stage/size] typically face [challenge]. How are you handling [specific aspect]?"
**Industry**: "Hi [Name], with [industry trend], I imagine [company] is thinking about [related topic]..."
**Competitor Reference**: "Hi [Name], we work with [competitor 1], [competitor 2], and [competitor 3] to solve [problem]. Worth a conversation?"
```
---
## 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: Company website, Industry, Company size, Location
### Step 2: Specify Preferences
**Personalization Style** (pick 1-3): Congratulations | Observations | Mutual connections | Company news | Hiring signals | Thought leadership
**Tone**: Professional | Casual | Direct | Consultative
**Avoid**: Anything older than [X] days | Personal information | Sensitive topics
### Step 3: Review & Customize
- Review first 10 personalizations and adjust tone if needed
- Flag any that feel "off"
- Add company-specific context and modify CTAs
### Step 4: Export & Use
**Formats**: CSV with personalization columns | Merge fields for Outreach/Salesloft | Individual email drafts
**Workflow**: Generate → Upload as custom fields → Use in sequence position 1 → Track response rates by type → Double down on what works
---
## Performance Benchmarks
| Metric | Generic Cold Email | With Personalization |
|--------|-------------------|---------------------|
| Response Rate | 1-3% | 8-15% |
| Lift | Baseline | 5-10x improvement |
**Time**: Manual 5-10 min/prospect vs AI 10-30 sec/prospect = 8-16 hours saved per 100 prospects
**Quality Threshold**: Aim for 70%+ with unique personalization. Below 50% = consider different prospect list.
---
### Best Practices
1. **Mix Personalization Types**: Don't just use LinkedIn posts for everyone
2. **KeeRelated in Ads & Marketing
ads
IncludedMulti-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Ads. 250+ checks with scoring, parallel agents, industry templates, and AI creative generation.
banana
IncludedAI image generation Creative Director powered by Google Gemini Nano Banana models. Use this skill for ANY request involving image creation, editing, visual asset production, or creative direction. Triggers on: generate an image, create a photo, edit this picture, design a logo, make a banner, visual for my anything, and all /banana commands. Handles text-to-image, image editing, multi-turn creative sessions, batch workflows, and brand presets.
rpg-migration-analyzer
IncludedAnalyzes legacy RPG (Report Program Generator) programs from AS/400 and IBM i systems for migration to modern Java applications. Extracts business logic from RPG III/IV/ILE source code, identifies data structures (D-specs), file operations (F-specs), program dependencies (CALLB/CALLP), and converts RPG constructs to Java equivalents. Generates migration reports, complexity estimates, and Java implementation strategies with POJO classes, JPA entities, and service methods. Use when modernizing AS/400 or IBM i legacy systems, analyzing RPG source files (.rpg, .rpgle, .RPGLE), converting RPG to Java, mapping data specifications to Java classes, planning legacy system migration, or when user mentions RPG analysis, Report Program Generator, RPG III/IV/ILE, AS/400 modernization, IBM i migration, packed decimal conversion, or mainframe application rewrite.
brand-library-architect
IncludedBuild a complete brand library for a product — visual asset render pipeline, brand documentation set (BRAND, COPY, MANIFESTO, BIOS, FAQ, GLOSSARY, TONE, PRICING), open-source convention files (README, CONTRIBUTING, SECURITY, CODE_OF_CONDUCT), and a self-contained press kit. This skill should be used when the user asks to "build a brand library / brand kit / press kit / brand assets" for a product, "set up a brand library workflow," "create a positioning manifesto plus visual identity," or any combination of brand documentation + visual asset pipeline. Apply phase-by-phase or run end-to-end. Templates are product-agnostic and use {{TOKEN}} placeholders the skill prompts the user to fill.
writing-tech-post
IncludedAuthors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces an evidence cadence (diagrams, benchmarks, profiles, traces, code, ablations), tunes voice against publisher house styles (Datadog, Vercel, GitHub, AWS, Meta, Cloudflare, Jane Street), and runs a pre-publish gate for narrative momentum and disclosure ethics. Use when drafting a new engineering post, restructuring a draft that feels flat, deciding which evidence form belongs where, validating that depth and product context are balanced, or preparing a postmortem, migration, or performance narrative for external publication. Do not use for API reference documentation, README authoring, marketing copy, release notes, generic SEO content, ghost-written executive thought leadership, or non-engineering long-form essays.
blog-google
IncludedGoogle API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".