Easy

LinkedIn Post Performance Tracker

See which LinkedIn posts actually perform. Get a data-driven content report with engagement metrics and actionable recommendations.

Works with:LinkedInLinkedIn

Free to start

1,000 credits included

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Setup time

~5 min

Time saved

30 min/report

Difficulty

Easy

Tools

1 connected

How it works

1

Pull All Posts

Gets every recent post with full content and metadata

2

Measure Engagement

Counts reactions and comments on each post with breakdowns

3

Identify Patterns

Groups posts by topic and format to find what works

4

Generate Report

Produces a structured content report with recommendations

Try asking

Analyze my LinkedIn post performance for the last 30 days — what topics got the most engagement?
Compare my LinkedIn content performance vs. our competitor's CMO over the last quarter
Generate a monthly LinkedIn content report for our company page with top posts and recommendations

View the agent prompt

See the full instructions this agent runs on — copy, edit, or customize it

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The Prompt

Task

Track LinkedIn post performance for a person or company over time. Pull all recent posts, measure engagement (reactions and comments) on each, and generate a content performance report that shows what is working, what is not, and what to do next.

Input

The user provides:

  • Person name/LinkedIn URL or company name to analyze
  • Optional: time period (e.g., "last 30 days", "Q1 2025", "last 3 months")
  • Optional: comparison target (e.g., "compare against [competitor]")

Context

Workflow

  1. Use @LinkedIn/Get PostsName it "LinkedIn/Get Posts" and call it with @LinkedIn/Get Posts to pull all recent posts for the target person or profile
  2. For each post, use @LinkedIn/Get Post ReactionsName it "LinkedIn/Get Post Reactions" and call it with @LinkedIn/Get Post Reactions to get reaction counts and type breakdown
  3. Use @LinkedIn/Get Post CommentsName it "LinkedIn/Get Post Comments" and call it with @LinkedIn/Get Post Comments to count comments and identify high-engagement threads
  4. Optionally, use @LinkedIn/Search PostsName it "LinkedIn/Search Posts" and call it with @LinkedIn/Search Posts to find competitor posts on similar topics for benchmarking
  5. Calculate performance metrics and identify patterns
  6. Generate a content performance report with actionable recommendations

Metrics to Calculate

  • Total reactions per post (and breakdown: like, celebrate, insightful, etc.)
  • Comment count per post
  • Engagement rate (reactions + comments relative to the person's typical baseline)
  • Post frequency (posts per week or month)
  • Best and worst performing posts
  • Performance by content format (text, image, video, carousel, poll)
  • Performance by topic or theme
  • Posting day and time correlation with engagement

What to Flag

  • Top 3 posts by total engagement
  • Bottom 3 posts by engagement
  • Any post that significantly outperformed or underperformed the average
  • Trending topics that consistently drive engagement
  • Content formats that over- or underperform

Output

LinkedIn Post Performance Report: [Name/Company]

Period: [date range] Total Posts: [count] Average Engagement: [avg reactions] reactions, [avg comments] comments per post

Top Performers:

| # | Post Preview | Date | Reactions | Comments | Format | Topic | |---|-------------|------|-----------|----------|--------|-------| | 1 | [first 50 chars] | [date] | [count] | [count] | [format] | [topic] | | 2 | [first 50 chars] | [date] | [count] | [count] | [format] | [topic] | | 3 | [first 50 chars] | [date] | [count] | [count] | [format] | [topic] |

Underperformers:

| # | Post Preview | Date | Reactions | Comments | Format | Topic | |---|-------------|------|-----------|----------|--------|-------| | 1 | [first 50 chars] | [date] | [count] | [count] | [format] | [topic] |

Performance by Format:

  • Text posts: avg [X] reactions
  • Image posts: avg [X] reactions
  • Video posts: avg [X] reactions
  • Polls: avg [X] reactions

Performance by Topic:

  • [Topic 1]: avg [X] engagement, [Y] posts
  • [Topic 2]: avg [X] engagement, [Y] posts

Recommendations:

  1. [Specific recommendation based on data]
  2. [Specific recommendation based on data]
  3. [Specific recommendation based on data]

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