social-analytics
Analyze social media profiles and engagement. Use when: auditing competitor social presence; calculating engagement rates; identifying top-performing content; tracking profile growth; benchmarking social metrics
Works with
--- name: social-analytics description: Analyze social media profiles and engagement. Use when: auditing competitor social presence; calculating engagement rates; identifying top-performing content; tracking profile growth; benchmarking social metrics license: MIT --- # Social Analytics > Analyze social media profiles and calculate engagement metrics - understand what content works for competitors and your own accounts. ## When to Use This Skill - **Competitor analysis** - Audit competitor social presence - **Engagement benchmarking** - Calculate and compare engagement rates - **Content analysis** - Identify top-performing post types - **Profile audit** - Assess social media health - **Reporting** - Generate social performance reports ## What Claude Does vs What You Decide | Claude Does | You Decide | |-------------|------------| | Structures analysis frameworks | Metric definitions | | Identifies patterns in data | Business interpretation | | Creates visualization templates | Dashboard design | | Suggests optimization areas | Action priorities | | Calculates statistical measures | Decision thresholds | ## Dependencies ```bash pip install click pandas requests beautifulsoup4 # For authenticated API access: pip install tweepy instaloader ``` ## Commands ### Analyze Profile ```bash python scripts/main.py analyze @competitor --platform twitter python scripts/main.py analyze @brand --platform instagram ``` ### Calculate Engagement ```bash python scripts/main.py engagement @profile --platform twitter --days 30 python scripts/main.py engagement @profile --platform linkedin --posts 50 ``` ### Find Top Posts ```bash python scripts/main.py top-posts @profile --platform twitter --count 10 python scripts/main.py top-posts @profile --metric likes ``` ### Export Data ```bash python scripts/main.py export @profile --platform twitter --format csv python scripts/main.py export @profile --platform instagram --output report.json ``` ### Compare Profiles ```bash python scripts/main.py compare @brand1 @brand2 @brand3 --platform twitter ``` ## Examples ### Example 1: Competitor Social Audit ```bash # Analyze competitor profile python scripts/main.py analyze @competitor_brand --platform twitter # Output: # Profile Analysis: @competitor_brand # ───────────────────────────────────── # Followers: 45,230 # Following: 1,234 # Total Posts: 2,456 # Avg Likes: 234 # Avg Retweets: 45 # Engagement: 2.3% # Post Frequency: 3.2/day # Top Hashtags: #marketing, #growth, #startup ``` ### Example 2: Benchmark Engagement Rates ```bash # Compare engagement across competitors python scripts/main.py compare @brand1 @brand2 @brand3 --platform twitter # Output: # Engagement Comparison # ───────────────────── # Profile Followers Eng.Rate Posts/Day # @brand1 45,230 2.3% 3.2 # @brand2 32,100 3.1% 2.1 # @brand3 89,500 1.8% 4.5 # Winner: @brand2 (highest engagement despite fewer followers) ``` ### Example 3: Find Winning Content ```bash # Identify top performing posts python scripts/main.py top-posts @marketing_pro --platform twitter --count 10 # Output: # Top 10 Posts by Engagement # ────────────────────────── # 1. "Here's what nobody tells you about..." # Likes: 2,345 RTs: 456 Eng: 6.2% # Type: Thread Time: Tuesday 9am # 2. "The biggest mistake I see founders make..." # Likes: 1,890 RTs: 312 Eng: 4.8% # Type: Single Time: Wednesday 8am ``` ## Engagement Rate Benchmarks ### Twitter/X | Account Size | Good | Great | Excellent | |--------------|------|-------|-----------| | <10K | 1-3% | 3-6% | >6% | | 10K-100K | 0.5-1% | 1-3% | >3% | | 100K+ | 0.2-0.5% | 0.5-1% | >1% | ### Instagram | Account Size | Good | Great | Excellent | |--------------|------|-------|-----------| | <10K | 3-6% | 6-10% | >10% | | 10K-100K | 1-3% | 3-6% | >6% | | 100K+ | 0.5-1% | 1-3% | >3% | ### LinkedIn | Account Size | Good | Great | Excellent | |--------------|------|-------|-----------| | Personal | 2-4% | 4-8% | >8% | | Company | 0.5-1% | 1-2% | >2% | ## Metrics Explained | Metric | Formula | What It Measures | |--------|---------|------------------| | **Engagement Rate** | (likes + comments + shares) / followers | Overall content resonance | | **Amplification** | shares / followers | Content virality | | **Conversation** | comments / followers | Community engagement | | **Applause** | likes / followers | Content appreciation | ## Output Formats | Format | Best For | |--------|----------| | `text` | Quick terminal review | | `csv` | Spreadsheet analysis | | `json` | Programmatic use | | `md` | Reports and docs | ## Skill Boundaries ### What This Skill Does Well - Structuring data analysis - Identifying patterns and trends - Creating visualization frameworks - Calculating statistical measures ### What This Skill Cannot Do - Access your actual data - Replace statistical expertise - Make business decisions - Guarantee prediction accuracy ## Related Skills - [content-repurposer](../../automation/content-repurposer/) - Repurpose top-performing content - [hashtag-analyzer](../hashtag-analyzer/) - Deep dive into hashtag performance ## Skill Metadata - **Mode**: centaur ```yaml category: social subcategory: analytics dependencies: [pandas, requests, beautifulsoup4] difficulty: intermediate time_saved: 4+ hours/week ```
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