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.