Youtube Outlier Detector (Find trending content based on your competitors)

n8n template #2903

Summary

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

How to set it up

Open template #2903 on n8n.io and click Use for free, or copy the template JSON and paste it onto an empty canvas in n8n.
Create 2 credentials under Credentials → Add credential: Postgres, YouTube. Then open each of those nodes and pick the credential.
Click Execute workflow and step through each node's output to confirm the data looks right.
Toggle the workflow to Active so its trigger runs on its own.

Hand off to your agent

Prompt

Help me set up the n8n workflow "Youtube Outlier Detector (Find trending content based on your competitors)" (https://n8n.io/workflows/2903). It uses: HTTP Request, Postgres, YouTube, Code. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.

Paste into Claude Code and it will do the rest.

Apps and nodes

HTTP Request Postgres YouTube Code

Questions

Yes. Leonardo Grigorio published it free on n8n.io as a verified creator, and it has 5,386 views. It runs on n8n Cloud or a self-hosted n8n instance.

Postgres, YouTube. The other 2 nodes are built into n8n.

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