BREAKING CHANGE: the marketplace slug, the agent namespace (linkedin-studio:<agent>), and the runtime state-file path (~/.claude/linkedin-studio.local.md) all change. Reinstall required; existing state migrated in place (post metrics, streak, history preserved). The /linkedin:* commands are unchanged — the command namespace is set per-command in frontmatter and was always independent of the plugin slug. Functionality is byte-identical to v2.4.0; this release is pure identity. - dir + manifests: plugins/linkedin-studio + plugin.json + root marketplace.json - agent namespace updated in commands/newsletter.md (only functional invoker) - state path updated in 4 hook scripts + topic-rotation prompt + state template - catch-all skill dir renamed skills/linkedin-studio (5 functional skills unchanged) - docs + version bump to 3.0.0 across README badge, CHANGELOG, root README/CLAUDE.md - historical records (CHANGELOG past entries, docs/ build artifacts, config-audit v5.0.0 snapshots) intentionally retain the old slug Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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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
- Go to LinkedIn Analytics: https://www.linkedin.com/analytics/
- Click on any post
- Navigate to "Demographics" tab
- 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:
- [Adjustment 1 - e.g., "Increase public sector examples, decrease startup references"]
- [Adjustment 2 - e.g., "Frame for Director-level, not just technical ICs"]
- [Adjustment 3 - e.g., "Add European regulatory context"]
Opportunities identified:
- [Opportunity 1 - e.g., "Large enterprise segment underserved by competitors"]
- [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]