YouTube Outlier Detector n8n Workflow: Track Trending Videos

Find YouTube “outlier” trends in your niche—automatically

This YouTube Outlier Detector n8n Workflow tracks competitor channels and pinpoints videos that dramatically outperform their usual performance—so you can spot trending topics faster and spend less time manually researching YouTube.

What this workflow does

• Automated competitor video tracking: Monitors specified competitor channels and fetches video data directly from the YouTube API (no manual scraping needed).
• Outlier detection vs. channel averages: Compares each video’s views to the channel’s historical average and flags significant spikes.
• Historical data management with PostgreSQL: Stores video statistics in a PostgreSQL database, so the workflow fetches only new videos and optimizes API usage.
• Short video filtering: Automatically removes short videos based on configured duration thresholds.
• Flexible retrieval schedule: On the first run, it pulls up to 3 months of historical data; on subsequent runs, it retrieves only newly published videos.
• Configurable outlier rule: Focuses on videos published within the last two weeks that have view counts of at least 2× the channel’s average.
• Actionable output: Produces a list of best-performing outliers along with engagement metrics to support faster decision-making.

Use cases

• SaaS operators and content strategists researching what’s trending in a market segment.
• Automation engineers building monitoring workflows for competitor performance using n8n.
• Niche creators identifying which topics are driving unusual view spikes so they can plan content accordingly.

Technical details

• n8n workflow nodes/tools: if, set, code, YouTube, PostgreSQL, sticky note
• Database support: Includes SQL queries for database setup, video insertion, and performance analysis.
• Requirements: You must have n8n installed on your machine or server.