Analyzes social media campaign performance across platforms with engagement metrics, ROI calculations, and audience insights for data-driven marketing decisions
Cost data: Ad spend, campaign budget (for ROI calculations)
Content details: Post type (image, video, carousel), posting time, hashtags
Time period: Date range for analysis
Formats accepted:
JSON with structured campaign data
CSV exports from social media platforms
Text descriptions of key metrics
Output Formats
Results include:
Performance dashboard: Key metrics with trends
: Best and worst performing posts
Engagement analysis
ROI breakdown: Cost efficiency metrics
Audience insights: Demographics and behavior patterns
Recommendations: Data-driven suggestions for optimization
Visual reports: Charts and graphs (Excel/PDF format)
How to Use
"Analyze this Facebook campaign data and calculate engagement metrics"
"What's the ROI on this Instagram ad campaign with $500 spend and 2,000 clicks?"
"Compare performance across all social platforms for the last month"
Scripts
calculate_metrics.py: Core calculation engine for all social media metrics
analyze_performance.py: Performance analysis and recommendation generation
Best Practices
Ensure data completeness before analysis (missing metrics affect accuracy)
Compare metrics within same time periods for fair comparisons
Consider platform-specific benchmarks (Instagram engagement differs from LinkedIn)
Account for organic vs. paid metrics separately
Track metrics over time to identify trends
Include context (seasonality, campaigns, events) when interpreting results
Limitations
Requires accurate data from social media platforms
Industry benchmarks are general guidelines and vary by niche
Historical data doesn't guarantee future performance
Organic reach calculations may vary by platform algorithm changes
Cannot access data directly from platforms (requires manual export or API integration)
Some platforms limit data availability (e.g., TikTok analytics for business accounts only)
