Automate Trending Video Detection on YouTube Using Competitor Analysis
This n8n workflow identifies trending YouTube videos by analyzing competitor channels for outliers that significantly outperform average views. It streamlines content research by automating data collection and analysis.
The workflow automates the process of monitoring specified competitor channels on YouTube to identify videos that are trending based on view count spikes. It integrates with the YouTube API to fetch video data and uses PostgreSQL for data storage and analysis. The workflow filters out short videos, manages historical data, and outputs the best-performing videos for further analysis. This is particularly useful for content creators looking to understand what topics are resonating with audiences w
- Platform
- n8n
- Category
- Data & Analytics
- Price
- $14.99
- Creator
- Zainab Ali
- if
- set
- code
- youTube
- postgres
- stickyNote
- httpRequest
- manualTrigger
- splitInBatches
- executeWorkflowTrigger
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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