Back to Templates
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.