name: anysite-content-analytics
description: Track and analyze content performance across Instagram, YouTube, LinkedIn, Twitter/X, and Reddit using anysite MCP server. Measure engagement metrics, analyze post effectiveness, benchmark content strategy, identify top-performing content, and optimize posting strategies. Supports post performance tracking, engagement analysis, content type comparison, and competitive benchmarking. Use when users need to measure content ROI, optimize social strategy, identify viral content patterns, or analyze content engagement across platforms.

anysite Content Analytics

Measure and optimize content performance across social platforms using anysite MCP. Track engagement, identify top performers, and refine your content strategy.

Overview

• Track post performance across Instagram, YouTube, LinkedIn, Twitter/X
• Analyze engagement metrics (likes, comments, shares, views)
• Identify top content and viral patterns
• Benchmark against competitors for strategy insights
• Optimize posting strategy based on data

Coverage: 80% - Strong for Instagram, YouTube, LinkedIn, Twitter, Reddit

Supported Platforms

• ✅ Instagram: Posts, Reels, likes, comments, engagement rates
• ✅ YouTube: Videos, views, likes, comments, watch time indicators
• ✅ LinkedIn: Posts, articles, reactions, comments, shares
• ✅ Twitter/X: Tweets, retweets, likes, replies
• ✅ Reddit: Posts, upvotes, comments, awards

Quick Start

Step 1: Collect Content Data

Platform-specific:
- Instagram: get_instagram_user_posts(username, count=50)
- LinkedIn: get_linkedin_user_posts(urn, count=50)
- Twitter: get_twitter_user_posts(user, count=100)
- YouTube: get_youtube_channel_videos(channel, count=30)

Step 2: Analyze Engagement

Calculate metrics:
- Engagement rate: (likes + comments + shares) / followers
- Best performing content: Top 10% by engagement
- Content types: Video vs. image vs. text
- Posting frequency: Posts per week

Step 3: Identify Patterns

Look for:
- Best posting times (day of week, time)
- Top-performing topics/themes
- Optimal content length
- High-engagement formats

Step 4: Optimize Strategy

Based on findings:
- Double down on top content types
- Post more during peak engagement times
- Replicate successful topics
- Adjust content mix

Common Workflows

Workflow 1: Instagram Content Audit

Steps:

1. Get All Posts

get_instagram_user_posts(username, count=100)

1. Calculate Metrics

For each post:
- Engagement rate = (likes + comments) / follower_count
- Engagement per hour = engagement / hours_since_posted
- Content type (Reel, carousel, single image, video)

1. Identify Top Performers

Sort by engagement rate
Top 10%: Analyze for common patterns
- Topics/themes
- Visual style
- Caption style and length
- Hashtag strategy

1. Analyze Content Mix

Count by type:
- Reels: X% of posts, Y% of engagement
- Carousels: X% of posts, Y% of engagement
- Single images: X% of posts, Y% of engagement

1. Benchmark Against Competitors

For each competitor:
  get_instagram_user_posts(competitor, count=50)
Compare:
- Posting frequency
- Engagement rates
- Content types
- Top themes

Expected Output:
- Content performance report
- Top 10 performing posts
- Content type effectiveness
- Posting frequency analysis
- Competitive benchmark

Workflow 2: LinkedIn Content Strategy Analysis

Steps:

1. Collect Post History

get_linkedin_user_posts(urn, count=100)

1. Categorize Content

Group by type:
- Text-only posts
- Image posts
- Video posts
- Article shares
- LinkedIn articles
- Polls

1. Analyze Engagement by Type

For each content type:
- Average reactions
- Average comments
- Average shares
- Engagement rate

1. Topic Analysis

Extract themes from top posts:
- Industry insights
- Personal stories
- How-to/educational
- Company news
- Thought leadership

1. Posting Timing Analysis

Group posts by:
- Day of week
- Time of day
Calculate average engagement for each group

Expected Output:
- Best content types for engagement
- Top topics by engagement
- Optimal posting times
- Content frequency recommendations

Workflow 3: YouTube Channel Performance Analysis

Steps:

1. Get Channel Videos

get_youtube_channel_videos(channel, count=50)

1. Analyze Each Video

For each video:
  get_youtube_video(video_id)

Metrics:
- Views
- Likes/dislikes
- Comments
- View velocity (views per day since upload)

1. Identify Patterns

Analyze top 20% by views:
- Video length
- Titles (keywords, style)
- Thumbnail patterns
- Topics/themes
- Upload timing

1. Engagement Analysis

Check comments:
  get_youtube_video_comments(video_id, count=100)

Analyze:
- Comment quality
- Questions asked
- Sentiment
- Engagement timing

1. Content Mix Optimization

Compare:
- Long-form (>10 min) vs short (<5 min)
- Tutorial vs entertainment vs review
- Series vs one-offs

Expected Output:
- Video performance rankings
- Optimal video length
- Best topics and formats
- Title and thumbnail insights
- Upload strategy recommendations

MCP Tools Reference

Instagram

• get_instagram_user_posts(user, count) - Get posts with engagement
• get_instagram_post(post_id) - Get detailed post metrics
• get_instagram_post_likes(post, count) - Analyze likers
• get_instagram_post_comments(post, count) - Get comments

LinkedIn

• get_linkedin_user_posts(urn, count) - Get post history
• get_linkedin_company_posts(urn, count) - Company page posts

Twitter/X

• get_twitter_user_posts(user, count) - Get tweets
• search_twitter_posts(query, count) - Find trending tweets

YouTube

• get_youtube_channel_videos(channel, count) - All videos
• get_youtube_video(video) - Video details and metrics
• get_youtube_video_comments(video, count) - Comments

Reddit

• reddit_user_posts(username, count) - User's posts
• search_reddit_posts(query, count) - Find popular posts

Key Metrics

Engagement Rate:
- Formula: (Likes + Comments + Shares) / Followers × 100
- Instagram benchmark: 3-6%
- LinkedIn benchmark: 2-5% of connections
- Twitter benchmark: 0.5-1%

Content Performance Score:

Score = (Engagement Rate × 40) +
        (Comments/Likes Ratio × 30) +
        (Share Rate × 30)

Viral Potential Indicators:
- Engagement rate >2x average
- High share rate (>5% of engagement)
- Rapid engagement velocity (50% within 24h)
- Quality comments (questions, discussions)

Output Formats

Chat Summary:
- Top 5 performing posts
- Key insights and patterns
- Recommendations for optimization

CSV Export:
- Post URL, date, type
- Likes, comments, shares
- Engagement rate
- Performance rank

JSON Export:
- Full post data with metadata
- Time-series engagement data
- Historical trends

Reference Documentation

• METRICS_GUIDE.md - Detailed metrics definitions, calculation formulas, and benchmarks

Ready to analyze content? Ask Claude to help you track performance, identify top content, or optimize your posting strategy!