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social-media-analyzer

Analyze social media post data to calculate engagement, click rates, and estimated returns on advertising spend. Compare results with supplied platform benchmarks, identify strong and weak posts, and generate recommendations for improving campaign performance.

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Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use when analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards. Also use when the user mentions "social media audit," "engagement rate," or "which platform performs best."

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Good for

  • Review social campaign performance
  • Identify posts with strong or weak engagement
  • Estimate advertising returns and interaction costs
  • Compare results across social platforms

Files included (7)

  • SKILL.md8.4 KB
  • assets/expected_output.json1.5 KB
  • assets/sample_input.json867 B
  • HOW_TO_USE.md1.8 KB
  • references/platform-benchmarks.md5.9 KB
  • scripts/analyze_performance.py7.2 KB
  • scripts/calculate_metrics.py5.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

FieldRequiredDescription
platformYesinstagram, facebook, twitter, linkedin, tiktok
posts[]YesArray of post data
posts[].likesYesLike/reaction count
posts[].commentsYesComment count
posts[].reachYesUnique users reached
posts[].impressionsNoTotal views
posts[].sharesNoShare/retweet count
posts[].savesNoSave/bookmark count
posts[].clicksNoLink clicks
total_spendNoAd 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

MetricFormulaInterpretation
Engagement RateEngagements / Reach × 100Audience interaction level
CTRClicks / Impressions × 100Content click appeal
Reach RateReach / Followers × 100Content distribution
Virality RateShares / Impressions × 100Share-worthiness
Save RateSaves / Reach × 100Content value

Performance Categories

RatingEngagement RateAction
Excellent> 6%Scale and replicate
Good3-6%Optimize and expand
Average1-3%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

MetricFormula
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

ActionValueRationale
Like$0.50Brand awareness
Comment$2.00Active engagement
Share$5.00Amplification
Save$3.00Intent signal
Click$1.50Traffic value

ROI Interpretation

ROI %RatingRecommendation
> 500%ExcellentScale budget significantly
200-500%GoodIncrease budget moderately
100-200%AcceptableOptimize before scaling
0-100%Break-evenReview targeting and creative
< 0%NegativePause and restructure

Platform Benchmarks

Engagement Rate by Platform

PlatformAverageGoodExcellent
Instagram1.22%3-6%>6%
Facebook0.07%0.5-1%>1%
Twitter/X0.05%0.1-0.5%>0.5%
LinkedIn2.0%3-5%>5%
TikTok5.96%8-15%>15%

CTR by Platform

PlatformAverageGoodExcellent
Instagram0.22%0.5-1%>1%
Facebook0.90%1.5-2.5%>2.5%
LinkedIn0.44%1-2%>2%
TikTok0.30%0.5-1%>1%

CPC by Platform

PlatformAverageGood
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 → Content isn't resonating. Analyze top performers for patterns.
  • Follower growth stalled → Content distribution or frequency issue. Audit posting patterns.
  • High impressions, low engagement → Reach without resonance. Content quality issue.
  • Competitor outperforming significantly → 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 → What (with confidence) → Why → How to Act
  • Results only. Every finding tagged: 🟢 verified, 🟡 medium, 🔴 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.

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