HTTP Request node
+6

API that extracts engaging moments from YouTube videos

Published 1 month ago

Created by

maxtkacz
Max T

Categories

Marketing

Template description

How it works

This template takes a YouTube video ID and identifies potentially engaging moments based on the intensity of specific timestamps 👇

Screenshot 20240228 at 15.51.02.png

Ideal for vloggers and YouTube content creators, it serves as a foundation for various automations to streamline content calendars or highlight popular moments in your videos. You can leverage it for:

  • Automatic processes to analyze YouTube videos and create sizzle reels or clips for social media, particularly effective for microcontent strategies like those endorsed by Gary Vee.
  • Instant alerts via Slack, Telegram, Email, or WhatsApp when significant moments occur in your videos.
  • Utilizing transcripts of these moments with AI to refine content ideas or brainstorm chatbots in your editorial workflow.

Example response from the Workflow-as-an-API

A GET request to {your instance URL}/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy returns 👇

successresponse.png

The workflow generates multiple moments; the screenshot above shows a truncated version.

Not all videos contain timestamp intensity data, the workflow handles this case as well 👇
errorresponse.png

How to use

  1. Import the template into your n8n workspace or self-hosted instance, then activate the workflow.
  2. Open the Webhook trigger node and copy the Production URL.
  3. In a web browser or any tool capable of consuming HTTP Requests (e.g., native code, Bubble app, n8n workflow, another automation tool, Postman, etc.), pass along the URL parameter ?ytID={youtube video ID} when invoking the API endpoint.

Your URL should resemble something like https://acme.app.n8n.cloud/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy.

Keep in mind
This workflow relies on an unofficial YouTube API graciously hosted for free by the folks at lemnoslife.com. It's not recommended for high-volume production usecases.

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