Content Analytics Expert Overview
This skill enables Claude to analyze content analytics data, generate comprehensive reports, identify performance trends, calculate ROI and revenue attribution, and provide actionable insights for content optimization.
When to Use This Skill
This skill activates automatically when users:
Ask analytics questions or request performance reports Need help analyzing content performance data Want ROI calculations or revenue attribution analysis Request trend identification from analytics data Need content optimization recommendations based on data Want to understand which content performs best and why Core Capabilities 1. Generate Analytics Reports
To generate comprehensive analytics reports:
Collect Analytics Data
Access analytics platform data (discover from project) Aggregate performance metrics across platforms Gather engagement data (views, likes, comments, shares) Collect conversion and revenue data (if available)
Create Report Structure
Weekly/Monthly performance reports Platform-specific performance analysis Content type performance comparison Audience engagement reports ROI and revenue attribution reports
Generate Report Content
Summarize key metrics and insights Create data visualizations (charts, graphs) Identify top-performing content Highlight trends and patterns Provide actionable recommendations
Example User Request: "Generate a monthly performance report for my content"
Integration (discover from project):
Analytics Platform: Access performance data Content Management Platform: Store and share reports Publishing Platform: Use insights for scheduling optimization 2. Identify Top-Performing Content Patterns
To identify patterns in top-performing content:
Analyze Performance Data
Review content performance metrics Identify top-performing content pieces Analyze common characteristics of successful content
Extract Patterns
Content topics and themes Content formats and types Posting times and frequencies Platform-specific patterns Engagement drivers (hooks, CTAs, visuals)
Generate Insights
Document successful content patterns Recommend content strategies based on patterns Suggest content replication opportunities
Example User Request: "What patterns do you see in my top-performing content?"
Integration (discover from project):
Analytics Platform: Analyze performance data Content Creation Tools: Apply patterns to new content generation Content Management Platform: Store pattern insights 3. Predict Content Performance
To predict content performance before publishing:
Analyze Historical Data
Review similar content performance Identify factors that correlate with success Build performance prediction models
Evaluate New Content
Compare new content to historical patterns Assess content against success factors Calculate predicted performance scores
Provide Recommendations
Suggest content improvements Recommend optimal posting times Identify best platforms for content Predict viral potential
Example User Request: "Predict how well this content will perform before I publish it"
Integration (discover from project):
Analytics Platform: Use historical data for predictions Content Creation Tools: Optimize content before generation Publishing Platform: Optimize scheduling based on predictions 4. ROI Analysis and Attribution
To calculate ROI and revenue attribution:
Track Revenue Metrics
Link content to conversions and revenue Track attribution through project's tracking links (discover format from project docs) Calculate cost per content piece (API costs, time)
Calculate ROI
Revenue per content piece Cost to create content ROI percentage calculation Revenue per platform/channel
Generate ROI Reports
Content-level ROI analysis Platform ROI comparison Campaign ROI tracking Revenue optimization recommendations
Example User Request: "Calculate the ROI for my content and show me which pieces drive the most revenue"
Integration (discover from project):
Analytics Platform: Track conversions and revenue Content Management Platform: Store ROI data and reports Publishing Platform: Optimize distribution based on ROI 5. Trend Identification
To identify trends from analytics data:
Analyze Time-Series Data
Review performance trends over time Identify growth or decline patterns Detect seasonal trends
Identify Emerging Trends
Content topics gaining traction Platform trends and shifts Audience behavior changes Engagement pattern shifts
Provide Trend Insights
Document identified trends Recommend actions based on trends Predict future trend directions
Example User Request: "What trends do you see in my content performance over the last 3 months?"
Integration (discover from project):
Analytics Platform: Analyze time-series data Content Management Platform: Store trend insights Content Creation Tools: Apply trends to content generation Project Context Discovery
Before analyzing analytics, discover the project's context:
Scan Project Documentation:
Check .agent/SYSTEM/ARCHITECTURE.md for analytics platform details Review .agent/SYSTEM/SUMMARY.md for analytics capabilities Look for analytics-related documentation
Identify Analytics Platform:
Check for analytics service integrations in codebase Look for analytics API endpoints or SDKs Review environment variables for analytics services
Discover Available Metrics:
Review analytics API documentation if available Check for analytics data models or schemas Identify what metrics the project tracks
Common Analytics Data Types (adapt based on discovery):
Post-level metrics: Views, Likes, Comments, Shares, Engagement Rate Platform-specific metrics: Performance by platform Time-based metrics: Performance over time (7d, 30d, 90d) Conversion metrics: Clicks, signups, revenue (via tracking links) Content type metrics: Performance by content type
Key Metrics:
Engagement Rate: (Likes + Comments + Shares) / Views ROI: (Revenue - Cost) / Cost × 100 Conversion Rate: Conversions / Clicks Average Performance: Aggregate metrics across content Best Practices Data-Driven Insights: Base all recommendations on actual analytics data Context Matters: Consider platform, timing, and audience when analyzing data Actionable Recommendations: Provide specific, actionable insights, not just data Comparative Analysis: Compare performance against benchmarks and historical data Continuous Monitoring: Recommend regular analytics review and optimization Resources references/ analytics-api-reference.md: Project analytics API endpoints and data structures (discover from project docs) roi-calculation-guide.md: ROI calculation methods and formulas performance-benchmarks.md: Industry benchmarks for content performance assets/ analytics-report-template.md: Template for analytics reports roi-report-template.md: Template for ROI analysis reports trend-analysis-template.md: Template for trend identification reports Complementary Skills (External)
For A/B testing and analytics tracking, pair with coreyhaines31/marketingskills:
/plugin marketplace add coreyhaines31/marketingskills
Skill Why analytics-tracking Tracking setup and event configuration ab-test-setup A/B test design and implementation