The Problem
Native YouTube analytics obscure deep content strategy insights, making it difficult to accurately benchmark engagement, evaluate true "hit" videos against shifting API methodologies, or forecast format-specific revenue.
Development Process
Serverless Proxy Routing
Engineered secure Next.js Route Handlers to mask YouTube Data API v3 credentials and execute data fetching entirely on the server.
Edge Rate-Limiting
Implemented an Upstash Redis sliding-window algorithm at the edge to aggressively protect API quotas and prevent malicious endpoint abuse.
Concurrent Data Pipeline
Built a non-blocking, token-based API pagination pipeline using batch fetching to render extensive historical channel data with sub-second latency.
Algorithmic Benchmarking
Developed a custom date-aware evaluation engine to normalize 0-second video starts against legacy metrics, ensuring precise head-to-head channel matchups and format-aware revenue projections.
Dynamic Visualization
Integrated React and Recharts to render interactive, GPU-accelerated charts that map out real-time reach and view momentum.
Tech Stack
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GET IN TOUCHSystem Architecture
The architecture of Stats-Tube, featuring high-performance proxy routing and batch fetching data pipeline.
Feature Spotlight
Device Responsive Interphase
Creator Dashboard detailed with channel stats
Analytics Visualization with recharts package
Momentum Graph (Video vs Millions)
Video Library detailed with video analytics.
Creator Head-to-Head Comparison with metrics.
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