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