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."
Campaign performance analysis with engagement metrics, ROI calculations, and platform benchmarks.
Analyze social media campaign performance:
| 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) |
Before analysis, verify:
Engagement Rate = (Likes + Comments + Shares + Saves) / Reach × 100
| 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 |
| 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 |
Calculate return on ad spend:
| 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 |
| 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 % | 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 | 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% |
| 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% |
| 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.
python scripts/calculate_metrics.py assets/sample_input.json
Calculates engagement rate, CTR, reach rate for each post and campaign totals.
python scripts/analyze_performance.py assets/sample_input.json
Generates full performance analysis with ROI, benchmarks, and recommendations.
Output includes:
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
}
]
}
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%"
}
}
}
The sample campaign shows:
references/platform-benchmarks.md contains:
| 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 |
All output passes quality verification:
Copy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/social-media-analyzer · pinned to the source commit
# Run from your project root
git clone https://github.com/alirezarezvani/claude-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 19392f7a08264ed00486a251f5b2098321771f94
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/.gemini/skills/social-media-analyzer" ".claude/skills/"
rm -rf .skillboard-tmpReview the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
sudo apt update && sudo apt install -y gitnpm install -g @anthropic-ai/claude-code# Run from your project root
git clone https://github.com/alirezarezvani/claude-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 19392f7a08264ed00486a251f5b2098321771f94
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/.gemini/skills/social-media-analyzer" ".claude/skills/"
rm -rf .skillboard-tmpDestination: .claude/skills/social-media-analyzer
Scanner static-checks@0.1.0 · commit 19392f7a0826. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.
No static rules matched. This is not a safety guarantee.