feat(linkedin-thought-leadership): v1.0.0 — initial open-source import
Build LinkedIn thought leadership with algorithmic understanding, strategic consistency, and AI-assisted content creation. Updated for the January 2026 360Brew algorithm change. 16 agents, 25 commands, 6 skills, 9 hooks, 24 reference docs. Personal data sanitized: voice samples generalized to template, high-engagement posts cleared, region-specific references replaced with placeholders. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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# Audience Demographics
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Track WHO is actually engaging with your content. LinkedIn Analytics provides this data for free - use it to understand your real audience vs. your intended audience.
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## How to Access This Data
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1. Go to LinkedIn Analytics: https://www.linkedin.com/analytics/
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2. Click on any post
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3. Navigate to "Demographics" tab
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4. Review data monthly and update this file
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---
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## Current Demographics (Last Updated: [Date])
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### Industries (Top 10)
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Based on LinkedIn Analytics → Post Analytics → Demographics
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| Rank | Industry | % of Engagement | Trend |
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|------|----------|----------------|--------|
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| 1 | [Industry name] | [X]% | [↑/→/↓] |
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| 2 | [Industry name] | [X]% | [↑/→/↓] |
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| 3 | [Industry name] | [X]% | [↑/→/↓] |
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| 4 | [Industry name] | [X]% | [↑/→/↓] |
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| 5 | [Industry name] | [X]% | [↑/→/↓] |
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| 6 | [Industry name] | [X]% | [↑/→/↓] |
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| 7 | [Industry name] | [X]% | [↑/→/↓] |
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| 8 | [Industry name] | [X]% | [↑/→/↓] |
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| 9 | [Industry name] | [X]% | [↑/→/↓] |
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| 10 | [Industry name] | [X]% | [↑/→/↓] |
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**Key insights:**
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- [Observation 1 - e.g., "60% from government sector, higher than expected"]
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- [Observation 2 - e.g., "Tech companies underrepresented vs. my assumptions"]
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- [Implication - e.g., "Should increase public sector case studies"]
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---
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### Job Functions (Top 10)
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| Rank | Function | % of Engagement | Trend |
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|------|----------|----------------|--------|
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| 1 | [Function] | [X]% | [↑/→/↓] |
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| 2 | [Function] | [X]% | [↑/→/↓] |
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| 3 | [Function] | [X]% | [↑/→/↓] |
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| 4 | [Function] | [X]% | [↑/→/↓] |
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| 5 | [Function] | [X]% | [↑/→/↓] |
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| 6 | [Function] | [X]% | [↑/→/↓] |
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| 7 | [Function] | [X]% | [↑/→/↓] |
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| 8 | [Function] | [X]% | [↑/→/↓] |
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| 9 | [Function] | [X]% | [↑/→/↓] |
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| 10 | [Function] | [X]% | [↑/→/↓] |
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**Key insights:**
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- [Who is actually engaging]
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- [Implication for content framing]
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---
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### Seniority Levels
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| Level | % of Engagement | Change vs. Last Month |
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|-------|----------------|----------------------|
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| Entry level | [X]% | [+/-X%] |
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| Individual contributor | [X]% | [+/-X%] |
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| Manager | [X]% | [+/-X%] |
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| Director | [X]% | [+/-X%] |
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| VP | [X]% | [+/-X%] |
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| C-level | [X]% | [+/-X%] |
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| Owner/Partner | [X]% | [+/-X%] |
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**Key insights:**
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- **Dominant level:** [Which level engages most]
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- **Decision-maker presence:** [% at Director+ level]
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- **Content implication:** [How technical/strategic should content be?]
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---
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### Geographic Distribution (Top 10 Countries)
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| Rank | Country | % of Engagement | Trend |
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|------|---------|----------------|--------|
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| 1 | [Country] | [X]% | [↑/→/↓] |
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| 2 | [Country] | [X]% | [↑/→/↓] |
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| 3 | [Country] | [X]% | [↑/→/↓] |
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| 4 | [Country] | [X]% | [↑/→/↓] |
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| 5 | [Country] | [X]% | [↑/→/↓] |
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| 6 | [Country] | [X]% | [↑/→/↓] |
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| 7 | [Country] | [X]% | [↑/→/↓] |
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| 8 | [Country] | [X]% | [↑/→/↓] |
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| 9 | [Country] | [X]% | [↑/→/↓] |
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| 10 | [Country] | [X]% | [↑/→/↓] |
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**Key insights:**
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- **Primary market:** [Where most engagement comes from]
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- **Time zone implications:** [Optimal posting times]
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- **Regional context:** [Does content need localization?]
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---
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### Company Size (Of Engagers)
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| Size | % of Engagement | Trend |
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|------|----------------|--------|
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| 1-10 employees | [X]% | [↑/→/↓] |
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| 11-50 | [X]% | [↑/→/↓] |
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| 51-200 | [X]% | [↑/→/↓] |
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| 201-500 | [X]% | [↑/→/↓] |
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| 501-1000 | [X]% | [↑/→/↓] |
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| 1001-5000 | [X]% | [↑/→/↓] |
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| 5001-10000 | [X]% | [↑/→/↓] |
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| 10000+ | [X]% | [↑/→/↓] |
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**Key insights:**
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- **Dominant segment:** [Enterprise/Mid-market/SMB]
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- **Content implication:** [Scale of examples, budget assumptions]
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- **Opportunity:** [Underserved segment to target]
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---
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## Intended vs. Actual Audience
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### Who I Thought My Audience Was
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- **Industries:** [Your original assumptions]
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- **Roles:** [Your original assumptions]
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- **Seniority:** [Your original assumptions]
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- **Geography:** [Your original assumptions]
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### Who My Audience Actually Is
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- **Industries:** [Reality from data above]
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- **Roles:** [Reality from data above]
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- **Seniority:** [Reality from data above]
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- **Geography:** [Reality from data above]
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### Strategic Implications
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**Content adjustments needed:**
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1. [Adjustment 1 - e.g., "Increase public sector examples, decrease startup references"]
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2. [Adjustment 2 - e.g., "Frame for Director-level, not just technical ICs"]
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3. [Adjustment 3 - e.g., "Add European regulatory context"]
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**Opportunities identified:**
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1. [Opportunity 1 - e.g., "Large enterprise segment underserved by competitors"]
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2. [Opportunity 2 - e.g., "Growing Nordic audience interested in topic X"]
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---
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## Follower vs. Engager Analysis
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**Important distinction:**
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- Your followers = who follows you
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- Your engagers = who actually interacts with content
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Often these are different groups. LinkedIn prioritizes showing your content to engagers, not just followers.
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### Follower Demographics
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[If you have LinkedIn Premium, note follower demographics here]
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- [Key differences from engager demographics]
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### Insight
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[What the difference between followers and engagers tells you]
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---
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## Competitive Audience Analysis
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How does your audience compare to key competitors/peers?
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| Peer | Their Primary Industry | Their Seniority Level | Difference from Mine |
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|------|----------------------|---------------------|---------------------|
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| [Name] | [Industry] | [Level] | [What's different] |
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| [Name] | [Industry] | [Level] | [What's different] |
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| [Name] | [Industry] | [Level] | [What's different] |
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**Content gap opportunity:**
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[Where your unique audience positioning creates content opportunities]
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---
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## Month-over-Month Trends
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### [Current Month] vs. [Previous Month]
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**Industry shifts:**
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- [What changed and why]
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**Seniority shifts:**
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- [What changed and why]
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**Geographic shifts:**
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- [What changed and why]
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**Analysis:**
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[What these trends indicate about content resonance and audience evolution]
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---
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## Update Schedule
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- **Monthly:** Update all demographics from LinkedIn Analytics
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- **Quarterly:** Deep analysis of trends and strategic implications
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- **Yearly:** Major review of intended vs. actual audience fit
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---
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## Update Log
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- **[Date]:** Initial demographics captured
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- **[Date]:** Observed [significant change] in [demographic category]
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- **[Date]:** Shifted content strategy based on [insight]
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