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LinkedIn Post Performance Tracker

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

Content analyticsPerformance trackingContent strategyCompetitor benchmarking

The Challenge

LinkedIn gives you basic impressions on your own posts, but no way to compare performance over time, analyze by topic, or benchmark against competitors. To build a real content report, you end up scrolling through weeks of posts, manually counting reactions, and trying to remember which ones did well. There is no export, no dashboard, and no trend analysis — just a feed.

What This Prompt Does

Pull All Posts

Gets every recent post with full content and metadata

Measure Engagement

Counts reactions and comments on each post with breakdowns

Identify Patterns

Groups posts by topic and format to find what works

Generate Report

Produces a structured content report with recommendations

The Prompt

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]

Example Usage

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"