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:

• Validate input data completeness (reach > 0, dates valid)

• Calculate engagement metrics per post

• Aggregate campaign-level metrics

• Calculate ROI if ad spend provided

• Compare against platform benchmarks

• Identify top and bottom performers

• Generate recommendations

• 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:

• Sum total engagements across posts

• Calculate cost per engagement (CPE)

• Calculate cost per click (CPC) if clicks available

• Estimate engagement value using benchmark rates

• Calculate ROI percentage

• 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

Proactive Triggers

• Engagement rate below platform average -- Content isn't resonating. Analyze top performers for patterns to replicate.

• Follower growth stalled -- Content distribution or frequency issue. Audit posting patterns and content mix.

• High impressions, low engagement -- Reach without resonance. Content quality or relevance issue needs addressing.

• Competitor outperforming significantly -- Content gap detected. Analyze their successful posts for format and topic insights.

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

"Campaign ROI" Full ROI calculation with engagement value estimates

Communication

All output passes quality verification:

• Self-verify: source attribution, assumption audit, confidence scoring

• Output format: Bottom Line first, then What (with confidence), Why, How to Act

• Every finding tagged with confidence level: verified, medium confidence, or assumed

Related Skills

• campaign-analytics: For cross-channel analytics including social alongside other channels.

• content-creator: For creating social media content optimized by analysis findings.

• marketing-demand-acquisition: For integrating social media into broader demand gen strategy.

• marketing-strategy-pmm: For aligning social content with product marketing positioning.