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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.