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personalization-at-scale大规模个性化

Agent Skill

personalization-at-scale 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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549

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22

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:personalization-at-scale(大规模个性化)
来源仓库:https://github.com/nicepkg/ai-workflow
仓库路径:skills/personalization-at-scale
安装命令:
npx skills add https://github.com/nicepkg/ai-workflow --skill personalization-at-scale
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/nicepkg/ai-workflow --skill personalization-at-scale

简介

personalization-at-scale 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于大规模个性化相关的关键词搜索和信息筛选场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装并使用该技能。
  • 安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Personalization at Scale

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:

  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

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

# 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)

**Average Research Time**:
- Manual: ~5 minutes per prospect = [X] hours total
- AI-Powered: ~10 seconds per prospect = [X] minutes total
- **Time Saved**: [X] hours

---

## 🎯 Personalized First Lines

### Prospect #1: [Name]

**Details**:
- **Name**: [First Last]
- **Title**: [Job Title]
- **Company**: [Company Name]
- **LinkedIn**: [Profile URL]
- **Email**: [Email address if known]

**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]

**Recommended First Line** (Option 1 - Direct):
> "Hi [First Name], congrats on [specific achievement/announcement]! I noticed [additional observation]. [Transition to value prop]"

**Alternative First Line** (Option 2 - Question):
> "[First Name], I saw [specific thing]. Curious - are you [question related to their situation]? [Transition to value prop]"

**Alternative First Line** (Option 3 - Insight):
> "Hi [First Name], given [their situation/news], I imagine [relevant challenge]. [Transition to value prop]"

**Full Email Example**:

Subject: [Company Name] + [Your Company] re: [their situation]

Hi [First Name],

[Personalized first line from above]

[Reason you're reaching out - 1-2 sentences]

[Value prop - 1 sentence]

[CTA - specific and low friction]

[Your Name]

**Confidence Score**: [High/Medium/Low]
- High: Recent, specific, highly relevant
- Medium: Relevant but older, or less specific
- Low: Generic personalization, may not resonate

**Notes**:
- [Any additional context or warnings]
- [Alternative angles if main one doesn't work]

---

### Prospect #2: [Name]

[Repeat structure for each prospect]

---

## 📈 Personalization by Type

### 🎉 Congratulations (15 prospects)

These prospects have recent achievements, funding, promotions, or launches to congratulate them on.

#### Example: [Company Name] - Series B Announcement

**First Line**:
> "Congrats on the Series B! $25M is awesome validation. With that kind of growth, [likely pain point you solve]..."

**Why This Works**:
- Timely (announced 2 weeks ago)
- Shows you're paying attention
- Transitions naturally to their likely needs during scale-up

**Similar Prospects**:
- [Company 2] - Series A ($5M)
- [Company 3] - Promoted to VP
- [Company 4] - Product launch

---

#### Example: [Prospect Name] - New Role

**First Line**:
> "[Name], saw you recently joined [Company] as [Title]. Congrats! First 90 days in a new role are always [crazy/exciting/challenging]. I imagine [relevant challenge]..."

**Why This Works**:
- New job = open to new vendors/solutions
- First 90 days is common pain point
- They're likely evaluating tools now

---

### 🔍 Observations (28 prospects)

These prospects have posted content, made comments, or shown activity that gives you an opening.

#### Example: LinkedIn Post About [Topic]

**First Line**:
> "Loved your take on [topic] in your recent post. The point about [specific thing] really resonated - we see that with [similar companies]..."

**Why This Works**:
- Shows you read their content (flattering)
- Specific callback to what they said
- Connects their thought to your expertise

**Prospects in This Category**:
| Name | Company | Observation | Source | Date |
|------|---------|-------------|--------|------|
| [Name 1] | [Company] | Posted about [topic] | LinkedIn | [Date] |
| [Name 2] | [Company] | Commented on [industry news] | LinkedIn | [Date] |
| [Name 3] | [Company] | Speaking at [conference] | Event page | [Date] |

---

### 🤝 Mutual Connections (12 prospects)

These prospects have 1st or 2nd degree connections you can reference.

#### Example: Shared Connection

**First Line**:
> "Hi [Name], I noticed we're both connected with [Mutual Connection]. She and I worked together at [Company] and when I saw you're the [Title] at [Company], thought I should reach out about [topic]..."

**Why This Works**:
- Mutual connection creates instant credibility
- Feels less "cold"
- Can potentially get warm intro

**Alternative Approach**:
- Ask mutual connection for intro first
- Reference in follow-up: "[Mutual] suggested I reach out..."

**Prospects with Strong Mutual Connections**:
| Prospect | Mutual Connection | Relationship |
|----------|------------------|--------------|
| [Name 1] | [Connection] | Former colleague |
| [Name 2] | [Connection] | Both attended [School] |
| [Name 3] | [Connection] | [Connection] is customer |

---

### 📰 Company News (22 prospects)

These companies have had recent press mentions, launches, or announcements.

#### Example: Company Expansion

**First Line**:
> "[Name], saw [Company] is opening 3 new offices across [region]. That kind of expansion is exciting but usually creates [specific challenge you solve]..."

**Why This Works**:
- Shows company-level awareness
- Ties expansion to likely pain point
- Timely and relevant

**Recent Company News by Prospect**:

**[Company 1]** - New product launch
- Date: [Date]
- Source: [TechCrunch/PR Newswire/etc.]
- Angle: "Launching a new product means your team is probably underwater with [problem]..."

**[Company 2]** - Opened Series C funding
- Date: [Date]
- Source: [Crunchbase]
- Angle: "With $50M to deploy, you're probably hiring aggressively and facing [problem]..."

**[Company 3]** - Partnership announcement
- Date: [Date]
- Source: [Company blog]
- Angle: "Partnership with [Big Company] is huge. Curious how you're handling [related challenge]..."

---

### 💼 Hiring Signals (18 prospects)

These companies have job postings that indicate growth, tech changes, or priorities.

#### Example: Multiple Engineering Hires

**First Line**:
> "Noticed you're hiring 5+ engineers according to your LinkedIn jobs page. Scaling eng teams that fast usually creates [specific problem you solve]..."

**Why This Works**:
- Job postings are public but not everyone notices
- Hiring = growth = budget
- Can infer pain points from the roles they're hiring

**Hiring Signal Analysis**:

| Company | Open Roles | Signal | Likely Pain Point | Relevance |
|---------|-----------|--------|------------------|-----------|
| [Company 1] | 8 SDRs | Scaling outbound | Need for [your solution] | High |
| [Company 2] | 5 DevOps | Infrastructure growth | Cloud cost management | High |
| [Company 3] | 3 Data Engineers | Building data team | Data pipeline tool | Medium |

---

### 🛠️ Tech Stack Changes (8 prospects)

These companies recently adopted or announced technology changes visible through job descriptions, case studies, or tech blogs.

#### Example: Migrating to [Technology]

**First Line**:
> "I saw in a recent job posting that you're migrating to [Technology]. We help companies during that transition with [specific problem]..."

**Why This Works**:
- Migration = change = potential for new vendors
- Shows technical awareness
- Timely opportunity

---

### 🎤 Thought Leadership (14 prospects)

These prospects have appeared on podcasts, webinars, published blogs, or spoken at events.

#### Example: Podcast Appearance

**First Line**:
> "Really enjoyed your appearance on [Podcast Name]. Your point about [specific insight] was spot-on - we actually help companies with exactly that..."

**Why This Works**:
- Flattering (they'll appreciate you listened/read)
- Can reference specific talking points
- Shows genuine interest

**Thought Leadership Activity**:

| Prospect | Activity | Topic | Source | Quality |
|----------|----------|-------|--------|---------|
| [Name 1] | Podcast guest | [Topic] | [Podcast] | High - Recent, specific quotes |
| [Name 2] | Conference speaker | [Topic] | [Conference] | High - Can reference session |
| [Name 3] | Blog post author | [Topic] | [Publication] | Medium - 3 months old |

---

### 🎓 Shared Background (6 prospects)

These prospects share alma mater, previous company, location, or interest with you or someone on your team.

#### Example: Same University

**First Line**:
> "Go [Mascot]! Saw you graduated from [University] too. I was there [years]. Anyway, I'm reaching out because [value prop]..."

**Why This Works**:
- Instant rapport with alums
- Shared identity = trust boost
- Breaking the ice

**Alternative Example: Same Previous Company**:
> "Small world - I saw you worked at [Company] from [years]. I was there around the same time in [department]. [Transition to business]..."

---

## 🚫 No Personalization Found (12 prospects)

These prospects have minimal online presence, no recent activity, or no obvious personalization angles.

**Fallback Strategies**:

### Fallback Option 1: Role-Based Personalization
> "Hi [Name], most [job titles] I talk to are dealing with [common pain point]. Is that on your radar?"

**Example**:
> "Hi Sarah, most VPs of Sales I talk to are struggling with forecast accuracy right now. Is that on your radar at Acme Corp?"

---

### Fallback Option 2: Company-Stage Personalization
> "Hi [Name], companies at [their stage/size] typically face [challenge]. How are you handling [specific aspect]?"

**Example**:
> "Hi John, Series B companies scaling from 50 to 200 employees typically face [challenge]. How's Acme handling [specific aspect]?"

---

### Fallback Option 3: Industry Personalization
> "Hi [Name], with [industry trend], I imagine [company] is thinking about [related topic]..."

**Example**:
> "Hi Lisa, with all the AI hype in fintech, I imagine Acme is evaluating how to implement without breaking compliance..."

---

### Fallback Option 4: Competitor Reference
> "Hi [Name], we work with [competitor 1], [competitor 2], and [competitor 3] to solve [problem]. Worth a conversation about how we could help Acme?"

**Example**:
> "Hi Mark, we work with Stripe, Square, and PayPal to reduce payment fraud by 40%. Worth a conversation about Acme?"

---

## 🎯 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**:
1. Generate personalizations
2. Upload to outreach tool as custom fields
3. Use in email sequence position 1
4. Track response rates by personalization type
5. 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

1. **Mix Personalization Types**: Don't just use LinkedIn posts for everyone
2. **Keep It Natural**: Should sound like you'd say it in person
3. **Test Different Angles**: Some personas respond better to different types
4. **Update Regularly**: Personalizations get stale; refresh every 30 days
5. **Track What Works**: Note which personalization types get best response
6. **Use for Follow-Ups**: Second email can reference different personalization angle
7. **Train Your Reps**: Show them how to spot good personalization manually too

### Don'ts

1. **Don't Be Creepy**: If it feels stalker-ish, skip it
2. **Don't Use Outdated Info**: Info from 6+ months ago feels lazy
3. **Don't Fake It**: "I was on your website" when you clearly weren't
4. **Don't Over-Personalize**: One good line is enough; don't overdo it
5. **Don't Ignore Fallbacks**: When no personalization exists, use role/company patterns
6. **Don't Use Same Line Twice**: Each prospect should feel unique
7. **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!

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