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>
267 lines
7.7 KiB
Markdown
267 lines
7.7 KiB
Markdown
# My Audience Engagement Patterns
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Track YOUR audience's specific behaviors and preferences here. This data is more valuable than generic "best practices" because it's based on YOUR actual results.
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## Update Frequency
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**Weekly (5 minutes):** Update posting times and add best-performing topic from the week
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**Monthly (15 minutes):** Deep dive into patterns, update demographics, analyze format performance
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---
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## Best Posting Times (Based on MY Data)
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**Important:** These should be YOUR times based on YOUR analytics, not generic advice. Track this in LinkedIn Analytics under "Post impressions by time of day."
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### Primary Posting Windows
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1. **[Day] at [Time]:** Avg. impressions: [X] | Avg. engagement: [Y]
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- Why this works: [e.g., "My audience (public sector leaders) checks LinkedIn during lunch break"]
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2. **[Day] at [Time]:** Avg. impressions: [X] | Avg. engagement: [Y]
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- Why this works: [Your analysis]
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3. **[Day] at [Time]:** Avg. impressions: [X] | Avg. engagement: [Y]
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- Why this works: [Your analysis]
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### Worst Posting Times (To Avoid)
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- [Day/Time]: [Why it underperforms for YOUR audience]
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- [Day/Time]: [Why it underperforms for YOUR audience]
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**Update Log:**
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- [Date]: [Change observed - e.g., "Tuesday 2pm now outperforms Friday 8am"]
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---
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## Top-Performing Topics (Last 90 Days)
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Track which topics YOUR audience actually engages with, not what you think they should care about.
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1. **[Topic]:** Avg. engagement: [X] | Posts: [Y]
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- Best-performing post example: [Brief description]
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- Why it resonates: [Your analysis]
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2. **[Topic]:** Avg. engagement: [X] | Posts: [Y]
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- Best-performing post example: [Brief description]
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- Why it resonates: [Your analysis]
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3. **[Topic]:** Avg. engagement: [X] | Posts: [Y]
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- Best-performing post example: [Brief description]
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- Why it resonates: [Your analysis]
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### Topics That Surprisingly Underperformed
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- **[Topic]:** [Why you thought it would work] → [Why it didn't]
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- **[Topic]:** [Analysis]
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**Implication for content strategy:**
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[What you'll do differently based on this data]
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---
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## Format Performance (MY Audience)
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Based on YOUR analytics, not generic benchmarks. Track in LinkedIn Analytics and your own spreadsheet.
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### Format Rankings (By Engagement)
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1. **[Format - e.g., "Story-based posts"]:**
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- Avg. impressions: [X]
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- Avg. engagement rate: [Y%]
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- Best time to post: [When]
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- Character sweet spot: [Range]
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2. **[Format - e.g., "Framework posts"]:**
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- Avg. impressions: [X]
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- Avg. engagement rate: [Y%]
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- Best time to post: [When]
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- Character sweet spot: [Range]
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3. **[Format - e.g., "Data/research posts"]:**
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- [Same metrics]
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4. **[Format - e.g., "Case study posts"]:**
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- [Same metrics]
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### Visual Content Performance
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- **Posts with images:** Avg. engagement: [X] vs text-only: [Y]
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- **Posts with documents:** Avg. engagement: [X]
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- **Posts with carousels:** Avg. engagement: [X]
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- **Video posts:** Avg. engagement: [X]
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**Your insights:**
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[What format performs best for YOUR audience and why]
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---
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## Hook Types That Work for ME
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Not all hook styles work for all audiences. Track which hooks YOUR audience responds to.
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### Top-Performing Hook Styles
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1. **[Hook type - e.g., "Counterintuitive stat"]**
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- Example: [Actual hook you used]
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- Avg. engagement: [X]
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- Why it works for your audience: [Analysis]
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2. **[Hook type - e.g., "Bold contrarian statement"]**
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- Example: [Actual hook]
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- Avg. engagement: [X]
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- Why it works: [Analysis]
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3. **[Hook type - e.g., "Personal story opening"]**
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- Example: [Actual hook]
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- Avg. engagement: [X]
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- Why it works: [Analysis]
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### Hook Styles That Don't Work for YOUR Audience
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- **[Hook type]:** [Why it underperforms with your specific audience]
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- **[Hook type]:** [Why it underperforms]
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---
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## CTA Performance Analysis
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Which calls-to-action actually drive engagement from YOUR audience?
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### High-Performing CTAs
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1. **[CTA type - e.g., "Specific implementation question"]**
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- Example: "Which stage is your organization in?"
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- Avg. comments generated: [X]
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2. **[CTA type]**
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- Example: [Actual CTA]
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- Avg. comments generated: [X]
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### Low-Performing CTAs (To Avoid)
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- **[CTA type]:** [Why YOUR audience doesn't respond to this]
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---
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## Audience Demographics (Who Actually Engages)
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Based on LinkedIn Analytics → Analytics → Demographics of people who interacted with your posts
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### Industries (Top 5)
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1. [Industry]: [% of engagement]
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2. [Industry]: [% of engagement]
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3. [Industry]: [% of engagement]
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4. [Industry]: [% of engagement]
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5. [Industry]: [% of engagement]
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**Insight:** [What this means for content focus]
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### Job Functions (Top 5)
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1. [Function]: [% of engagement]
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2. [Function]: [% of engagement]
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3. [Function]: [% of engagement]
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4. [Function]: [% of engagement]
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5. [Function]: [% of engagement]
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**Insight:** [How this should shape your content]
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### Seniority Levels
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- C-level: [%]
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- VP/Director: [%]
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- Manager: [%]
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- Individual contributor: [%]
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- Entry level: [%]
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**Insight:** [Technical depth and framing implications]
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### Geographic Distribution (Top 5 Countries)
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1. [Country]: [%]
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2. [Country]: [%]
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3. [Country]: [%]
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4. [Country]: [%]
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5. [Country]: [%]
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**Insight:** [Time zone and regional context considerations]
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### Company Size (Of Engagers)
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- 1-10 employees: [%]
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- 11-50: [%]
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- 51-200: [%]
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- 201-500: [%]
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- 501-1000: [%]
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- 1001-5000: [%]
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- 5001-10000: [%]
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- 10000+: [%]
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**Insight:** [Scale and organizational context implications]
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---
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## Content Length Performance (YOUR Data)
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Track the optimal length for YOUR audience, not generic advice.
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- **800-1000 characters:** Avg. engagement: [X]
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- **1000-1200 characters:** Avg. engagement: [X]
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- **1200-1500 characters:** Avg. engagement: [X]
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- **1500-1900 characters:** Avg. engagement: [X]
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- **1900+ characters:** Avg. engagement: [X]
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**Your sweet spot:** [Range that consistently performs best]
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**Why:** [Your analysis of why this works for your audience]
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---
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## Engagement Velocity Patterns
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How quickly does YOUR content gain traction?
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### First Hour Performance
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- **Average engagement in first 60 minutes:** [X] likes, [Y] comments
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- **Threshold for algorithm boost:** [Based on your data, when does reach accelerate?]
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- **Your current hit rate:** [% of posts that hit the threshold]
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### 24-Hour Patterns
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- **Most engagement happens in:** [Time window - e.g., "First 3 hours"]
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- **Secondary surge times:** [If applicable]
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- **Typical engagement curve:** [Description of how your posts perform over 24 hours]
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---
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## Strategic Insights (The "So What")
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Based on all the data above, what should you do differently?
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### Content Strategy Adjustments
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1. **More of this:** [What data says you should double down on]
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2. **Less of this:** [What data says isn't working]
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3. **Test this:** [New hypotheses based on patterns]
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### Audience Alignment
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- **Who you thought your audience was:** [Original assumption]
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- **Who actually engages:** [Reality based on data]
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- **Strategic implication:** [How content should shift]
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### Competitive Edge Opportunities
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Based on YOUR unique audience makeup:
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- **Gap 1:** [Underserved need you could fill]
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- **Gap 2:** [Content angle competitors miss]
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- **Gap 3:** [Format opportunity]
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---
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## Monthly Comparison
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Track month-over-month to see if patterns are stable or shifting.
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### [Current Month]
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- Avg. impressions per post: [X]
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- Avg. engagement per post: [Y]
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- Follower growth: [+X]
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- Best-performing topic: [Topic]
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- Best-performing format: [Format]
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### [Previous Month]
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- [Same metrics for comparison]
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**Key changes:** [What's different and why]
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---
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## Update Log
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- **[Date]:** [Significant finding - e.g., "Discovered Thursday posts now outperform Tuesday"]
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- **[Date]:** [Pattern shift - e.g., "Framework posts have overtaken story posts in engagement"]
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- **[Date]:** [Audience insight - e.g., "Realize 60% of engagers are from enterprise, not SMB"]
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