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 pip install click pandas requests beautifulsoup4
For authenticated API access:
pip install tweepy instaloader Commands Analyze Profile python scripts/main.py analyze @competitor --platform twitter python scripts/main.py analyze @brand --platform instagram Calculate Engagement python scripts/main.py engagement @profile --platform twitter --days 30 python scripts/main.py engagement @profile --platform linkedin --posts 50 Find Top Posts python scripts/main.py top-posts @profile --platform twitter --count 10 python scripts/main.py top-posts @profile --metric likes Export Data python scripts/main.py export @profile --platform twitter --format csv python scripts/main.py export @profile --platform instagram --output report.json Compare Profiles python scripts/main.py compare @brand1 @brand2 @brand3 --platform twitter Examples Example 1: Competitor Social Audit
Analyze competitor profile
python scripts/main.py analyze @competitor_brand --platform twitter
Output:
Profile Analysis: @competitor_brand
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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
Compare engagement across competitors
python scripts/main.py compare @brand1 @brand2 @brand3 --platform twitter
Output:
Engagement Comparison
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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
Identify top performing posts
python scripts/main.py top-posts @marketing_pro --platform twitter --count 10
Output:
Top 10 Posts by Engagement
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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