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social-media-analyzer

social-media-analyzer

github.com/alirezarezvaniMarketing & growth89775 installsUpdated 50w ago
Repository

About social-media-analyzer

A skill for analyzing social media campaign performance from supplied data, aimed at marketing agencies and campaign analysts. It calculates engagement and ROI metrics, examines audience and content patterns, and produces recommendations and reports; platform data must be provided by the user.

Key features

  1. 01Cross-platform campaign analysis
  2. 02Engagement and reach metrics
  3. 03Cost and ROI calculations
  4. 04Audience and content insights
  5. 05Trend analysis and benchmarking
  6. 06Recommendations and visual reports

Use cases

  1. 01Review performance across platforms
  2. 02Calculate campaign engagement and ROI
  3. 03Identify strong posts and posting patterns
  4. 04Prepare client campaign reports

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/alirezarezvani/claude-code-skill-factory --skill social-media-analyzer

After installing, type/social-media-analyzerin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

analyze_performance.py
calculate_metrics.py
expected_output.json
HOW_TO_USE.md
sample_input.json

Details

From the project README

Social Media Campaign Analyzer

This skill provides comprehensive analysis of social media campaign performance, helping marketing agencies deliver actionable insights to clients.

Capabilities

  • Multi-Platform Analysis: Track performance across Facebook, Instagram, Twitter, LinkedIn, TikTok
  • Engagement Metrics: Calculate engagement rate, reach, impressions, click-through rate
  • ROI Analysis: Measure cost per engagement, cost per click, return on ad spend
  • Audience Insights: Analyze demographics, peak engagement times, content performance
  • Trend Detection: Identify high-performing content types and posting patterns
  • Competitive Benchmarking: Compare performance against industry standards

Input Requirements

Campaign data including:

  • Platform metrics: Likes, comments, shares, saves, clicks
  • Reach data: Impressions, unique reach, follower growth
  • Cost data: Ad spend, campaign budget (for ROI calculations)
  • Content details: Post type (image, video, carousel), posting time, hashtags
  • Time period: Date range for analysis

Formats accepted:

  • JSON with structured campaign data
  • CSV exports from social media platforms
  • Text descriptions of key metrics

Output Formats

Results include:

  • Performance dashboard: Key metrics with trends
  • Engagement analysis: Best and worst performing posts
  • ROI breakdown: Cost efficiency metrics
  • Audience insights: Demographics and behavior patterns
  • Recommendations: Data-driven suggestions for optimization
  • Visual reports: Charts and graphs (Excel/PDF format)

How to Use

"Analyze this Facebook campaign data and calculate engagement metrics" "What's the ROI on this Instagram ad campaign with $500 spend and 2,000 clicks?" "Compare performance across all social platforms for the last month"

Scripts

  • calculate_metrics.py: Core calculation engine for all social media metrics
  • analyze_performance.py: Performance analysis and recommendation generation

Best Practices

  1. Ensure data completeness before analysis (missing metrics affect accuracy)
  2. Compare metrics within same time periods for fair comparisons
  3. Consider platform-specific benchmarks (Instagram engagement differs from LinkedIn)
  4. Account for organic vs. paid metrics separately
  5. Track metrics over time to identify trends
  6. Include context (seasonality, campaigns, events) when interpreting results

Limitations

  • Requires accurate data from social media platforms
  • Industry benchmarks are general guidelines and vary by niche
  • Historical data doesn't guarantee future performance
  • Organic reach calculations may vary by platform algorithm changes
  • Cannot access data directly from platforms (requires manual export or API integration)
  • Some platforms limit data availability (e.g., TikTok analytics for business accounts only)

Comments

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