skills/openclaw/skills/social-media-analyzer

social-media-analyzer

SKILL.md

Social Media Analyzer

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


Table of Contents


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 × 100

Metric Definitions

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