Youtube outlier detector (find trending content based on your competitors)

Video explanation This n8n workflow helps you identify trending videos within your niche by detecting outlier videos that significantly outperform a channel's average views. It automates the process of monitoring competitor channels, saving time and streamlining content research. Included in the Workflow - Automated Competitor Video Tracking Monitors videos from specified competitor channels, fetching data directly from the YouTube API. - Outlier Detection Based on Channel Averages Compares each video’s performance against the channel’s historical average to identify significant spikes in viewership. - Historical Video Data Management Stores video statistics in a PostgreSQL database, allowing the workflow to only fetch new videos and optimize API usage. - Short Video Filtering Automatically removes short videos based on duration thresholds. - Flexible Video Retrieval Fetches up to 3 months of historical data on the first run and only new videos on subsequent runs. - PostgreSQL Database Integration Includes SQL queries for database setup, video insertion, and performance analysis. - Configurable Outlier Threshold Focuses on videos published within the last two weeks with view counts at least twice the channel's average. - Data Output for Analysis Outputs best-performing videos along with their engagement metrics, making it easier to identify trending topics. Requirements - n8n installed on your machine or server - A valid YouTube Data API key - Access to a PostgreSQL database This workflow is intended for educational and research purposes, helping content creators gain insights into what topics resonate with audiences without manual daily monitoring.