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Social Media Analyzer

by @alirezarezvani

Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media pe...

Versionv2.1.1
Downloads2,374
Installs19
Stars⭐ 1
TERMINAL
clawhub install social-media-analyzer

πŸ“– About This Skill


name: "social-media-analyzer" description: Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards. triggers: - analyze social media - calculate engagement rate - social media ROI - campaign performance - compare platforms - benchmark engagement - Instagram analytics - Facebook metrics - TikTok performance - LinkedIn engagement

Social Media Analyzer

Campaign performance analysis with engagement metrics, ROI calculations, and platform benchmarks.


Table of Contents

  • Analysis Workflow
  • Engagement Metrics
  • ROI Calculation
  • Platform Benchmarks
  • Tools
  • Examples

  • Analysis Workflow

    Analyze social media campaign performance:

    1. Validate input data completeness (reach > 0, dates valid) 2. Calculate engagement metrics per post 3. Aggregate campaign-level metrics 4. Calculate ROI if ad spend provided 5. Compare against platform benchmarks 6. Identify top and bottom performers 7. Generate recommendations 8. Validation: Engagement rate < 100%, ROI matches spend data

    Input Requirements

    | Field | Required | Description | |-------|----------|-------------| | platform | Yes | instagram, facebook, twitter, linkedin, tiktok | | posts[] | Yes | Array of post data | | posts[].likes | Yes | Like/reaction count | | posts[].comments | Yes | Comment count | | posts[].reach | Yes | Unique users reached | | posts[].impressions | No | Total views | | posts[].shares | No | Share/retweet count | | posts[].saves | No | Save/bookmark count | | posts[].clicks | No | Link clicks | | total_spend | No | Ad spend (for ROI) |

    Data Validation Checks

    Before analysis, verify:

  • [ ] Reach > 0 for all posts (avoid division by zero)
  • [ ] Engagement counts are non-negative
  • [ ] Date range is valid (start < end)
  • [ ] Platform is recognized
  • [ ] Spend > 0 if ROI requested

  • Engagement Metrics

    Engagement Rate Calculation

    Engagement Rate = (Likes + Comments + Shares + Saves) / Reach Γ— 100
    

    Metric Definitions

    | Metric | Formula | Interpretation | |--------|---------|----------------| | Engagement Rate | Engagements / Reach Γ— 100 | Audience interaction level | | CTR | Clicks / Impressions Γ— 100 | Content click appeal | | Reach Rate | Reach / Followers Γ— 100 | Content distribution | | Virality Rate | Shares / Impressions Γ— 100 | Share-worthiness | | Save Rate | Saves / Reach Γ— 100 | Content value |

    Performance Categories

    | Rating | Engagement Rate | Action | |--------|-----------------|--------| | Excellent | > 6% | Scale and replicate | | Good | 3-6% | Optimize and expand | | Average | 1-3% | Test improvements | | Poor | < 1% | Analyze and pivot |


    ROI Calculation

    Calculate return on ad spend:

    1. Sum total engagements across posts 2. Calculate cost per engagement (CPE) 3. Calculate cost per click (CPC) if clicks available 4. Estimate engagement value using benchmark rates 5. Calculate ROI percentage 6. Validation: ROI = (Value - Spend) / Spend Γ— 100

    ROI Formulas

    | Metric | Formula | |--------|---------| | Cost Per Engagement (CPE) | Total Spend / Total Engagements | | Cost Per Click (CPC) | Total Spend / Total Clicks | | Cost Per Thousand (CPM) | (Spend / Impressions) Γ— 1000 | | Return on Ad Spend (ROAS) | Revenue / Ad Spend |

    Engagement Value Estimates

    | Action | Value | Rationale | |--------|-------|-----------| | Like | $0.50 | Brand awareness | | Comment | $2.00 | Active engagement | | Share | $5.00 | Amplification | | Save | $3.00 | Intent signal | | Click | $1.50 | Traffic value |

    ROI Interpretation

    | ROI % | Rating | Recommendation | |-------|--------|----------------| | > 500% | Excellent | Scale budget significantly | | 200-500% | Good | Increase budget moderately | | 100-200% | Acceptable | Optimize before scaling | | 0-100% | Break-even | Review targeting and creative | | < 0% | Negative | Pause and restructure |


    Platform Benchmarks

    Engagement Rate by Platform

    | Platform | Average | Good | Excellent | |----------|---------|------|-----------| | Instagram | 1.22% | 3-6% | >6% | | Facebook | 0.07% | 0.5-1% | >1% | | Twitter/X | 0.05% | 0.1-0.5% | >0.5% | | LinkedIn | 2.0% | 3-5% | >5% | | TikTok | 5.96% | 8-15% | >15% |

    CTR by Platform

    | Platform | Average | Good | Excellent | |----------|---------|------|-----------| | Instagram | 0.22% | 0.5-1% | >1% | | Facebook | 0.90% | 1.5-2.5% | >2.5% | | LinkedIn | 0.44% | 1-2% | >2% | | TikTok | 0.30% | 0.5-1% | >1% |

    CPC by Platform

    | Platform | Average | Good | |----------|---------|------| | Facebook | $0.97 | <$0.50 | | Instagram | $1.20 | <$0.70 | | LinkedIn | $5.26 | <$3.00 | | TikTok | $1.00 | <$0.50 |

    See references/platform-benchmarks.md for complete benchmark data.


    Tools

    Calculate Metrics

    python scripts/calculate_metrics.py assets/sample_input.json
    

    Calculates engagement rate, CTR, reach rate for each post and campaign totals.

    Analyze Performance

    python scripts/analyze_performance.py assets/sample_input.json
    

    Generates full performance analysis with ROI, benchmarks, and recommendations.

    Output includes:

  • Campaign-level metrics
  • Post-by-post breakdown
  • Benchmark comparisons
  • Top performers ranked
  • Actionable recommendations

  • Examples

    Sample Input

    See assets/sample_input.json:

    {
      "platform": "instagram",
      "total_spend": 500,
      "posts": [
        {
          "post_id": "post_001",
          "content_type": "image",
          "likes": 342,
          "comments": 28,
          "shares": 15,
          "saves": 45,
          "reach": 5200,
          "impressions": 8500,
          "clicks": 120
        }
      ]
    }
    

    Sample Output

    See assets/expected_output.json:

    {
      "campaign_metrics": {
        "total_engagements": 1521,
        "avg_engagement_rate": 8.36,
        "ctr": 1.55
      },
      "roi_metrics": {
        "total_spend": 500.0,
        "cost_per_engagement": 0.33,
        "roi_percentage": 660.5
      },
      "insights": {
        "overall_health": "excellent",
        "benchmark_comparison": {
          "engagement_status": "excellent",
          "engagement_benchmark": "1.22%",
          "engagement_actual": "8.36%"
        }
      }
    }
    

    Interpretation

    The sample campaign shows:

  • Engagement rate 8.36% vs 1.22% benchmark = Excellent (6.8x above average)
  • CTR 1.55% vs 0.22% benchmark = Excellent (7x above average)
  • ROI 660% = Outstanding return on $500 spend
  • Recommendation: Scale budget, replicate successful elements

  • Reference Documentation

    Platform Benchmarks

    references/platform-benchmarks.md contains:

  • Engagement rate benchmarks by platform and industry
  • CTR benchmarks for organic and paid content
  • Cost benchmarks (CPC, CPM, CPE)
  • Content type performance by platform
  • Optimal posting times and frequency
  • ROI calculation formulas
  • Proactive Triggers

  • Engagement rate below platform average β†’ Content isn't resonating. Analyze top performers for patterns.
  • Follower growth stalled β†’ Content distribution or frequency issue. Audit posting patterns.
  • High impressions, low engagement β†’ Reach without resonance. Content quality issue.
  • Competitor outperforming significantly β†’ Content gap. Analyze their successful posts.
  • Output Artifacts

    | When you ask for... | You get... | |---------------------|------------| | "Social media audit" | Performance analysis across platforms with benchmarks | | "What's performing?" | Top content analysis with patterns and recommendations | | "Competitor social analysis" | Competitive social media comparison with gaps |

    Communication

    All output passes quality verification:

  • Self-verify: source attribution, assumption audit, confidence scoring
  • Output format: Bottom Line β†’ What (with confidence) β†’ Why β†’ How to Act
  • Results only. Every finding tagged: 🟒 verified, 🟑 medium, πŸ”΄ assumed.
  • Related Skills

  • social-content: For creating social posts. Use this skill for analyzing performance.
  • campaign-analytics: For cross-channel analytics including social.
  • content-strategy: For planning social content themes.
  • marketing-context: Provides audience context for better analysis.
  • πŸ’‘ Examples

    Sample Input

    See assets/sample_input.json:

    {
      "platform": "instagram",
      "total_spend": 500,
      "posts": [
        {
          "post_id": "post_001",
          "content_type": "image",
          "likes": 342,
          "comments": 28,
          "shares": 15,
          "saves": 45,
          "reach": 5200,
          "impressions": 8500,
          "clicks": 120
        }
      ]
    }
    

    Sample Output

    See assets/expected_output.json:

    {
      "campaign_metrics": {
        "total_engagements": 1521,
        "avg_engagement_rate": 8.36,
        "ctr": 1.55
      },
      "roi_metrics": {
        "total_spend": 500.0,
        "cost_per_engagement": 0.33,
        "roi_percentage": 660.5
      },
      "insights": {
        "overall_health": "excellent",
        "benchmark_comparison": {
          "engagement_status": "excellent",
          "engagement_benchmark": "1.22%",
          "engagement_actual": "8.36%"
        }
      }
    }
    

    Interpretation

    The sample campaign shows:

  • Engagement rate 8.36% vs 1.22% benchmark = Excellent (6.8x above average)
  • CTR 1.55% vs 0.22% benchmark = Excellent (7x above average)
  • ROI 660% = Outstanding return on $500 spend
  • Recommendation: Scale budget, replicate successful elements