AI-Powered Content Performance Analysis
Overview
Content teams often struggle to connect creation effort to business impact. We’re building an AI-driven analysis pipeline that ingests content performance data and surfaces actionable insights.
Current Progress
We’ve completed the data ingestion and prompt architecture phases. The system currently:
- Pulls engagement metrics from analytics platforms
- Categorizes content by topic, format, and funnel stage
- Generates natural language performance summaries
- Identifies emerging topic trends
Next Steps
- Predictive scoring for proposed content topics
- Automated content brief generation
- Integration with editorial planning workflows
Technical Stack
The pipeline uses Claude for natural language analysis, with structured prompts that enforce consistent output formatting for downstream dashboards.