Publisher Scoring System

Overview

I developed a platform that evaluates and scores digital content publishers based on multiple metrics. The system evolved through two versions, with V1 providing baseline scoring and V2 delivering enhanced algorithmic assessment.

Key Features

• Comprehensive Publisher Evaluation: Analyzes publishers using metrics including content quality, engagement rates, and audience reach
• Dual Scoring Methodology: Implements both V1 baseline scoring and V2 enhanced algorithmic assessment
• Data-Driven Insights: Provides objective publisher quality metrics to inform partner selection
• Automated Assessment: Streamlines the publisher evaluation process with minimal manual intervention

Technical Implementation

• Backend Services: Built with Python and FastAPI to create efficient data processing endpoints
• Modern Frontend: Implemented with Next.js for an interactive dashboard experience
• Optimized Data Storage: Utilized PostgreSQL for reliable metric storage and retrieval
• Performance Optimization: Implemented Redis caching for frequently accessed scoring data
• Containerized Deployment: Packaged with Docker for consistent deployment across environments

Business Impact

This scoring system transformed publisher evaluation from a manual process to an automated, data-driven workflow. It enables faster identification of quality publishing partners while maintaining objective assessment standards. The platform significantly reduces the time required to evaluate publishers while increasing the reliability of quality assessments.