Build YouTube Data Archive in Notion with Make.com & Apify

Overview

This is an enterprise-grade video data collection solution tailored for content creators and data analysts.

By combining Apify’s powerful scraping capabilities, Make.com’s logic orchestration, and Notion’s database management, you can achieve fully automated YouTube video archival:

1. Input Channels - Batch input multiple YouTube channel links
2. Data Collection - Apify automatically scrapes video metadata and subtitles
3. Data Processing - Iterator splits each video for processing
4. Smart Filtering - Filter handles videos without subtitles
5. Archive Storage - Automatically writes to Notion database

Database schema design including title, URL, views, and other core fields

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Core Decision Factors

When choosing a video data collection solution, consider:

• Configuration Barrier - Whether coding is required (this solution needs no low-level code but requires JSON understanding)
• Data Granularity - Can it scrape subtitles, thumbnails, likes, and other deep data
• Error Handling - Will the workflow break when encountering videos without subtitles
• Scalability - How easy is it to add new monitoring channels

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Technical Specifications

Specification	Value	Notes
Core Platform	Make.com	Logic orchestration and data flow
Scraping Engine	Apify	YouTube Scraper Actor
Target Database	Notion	Store metadata and gallery view
Trigger Method	Manual/Scheduled	Supports batch or periodic updates
Max Scrape Count	Configurable	20/500/1000, etc.
Wait Timeout	120 seconds	Make waits for Apify completion
Data Fields	Title/Duration/Views/Likes/Subtitles	Covers core metadata
Time Filter	thisWeek/thisYear	Filter by time range

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Prerequisites

Before starting, ensure you have:

• Make.com account (free registration)
• Apify account and API key (apify.com)
• Notion account and database

Notion Database Structure

Create a video library with the following fields:

• Title (Title) - Video title
• URL (URL) - Video link
• Channel (Text) - Channel name
• Views (Number) - View count
• Likes (Number) - Like count
• Duration (Text) - Video length
• Published Date (Date) - Publication time
• Thumbnail (Files & Media) - Video thumbnail

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Workflow Architecture

Core Modules

1. Basic Trigger - Input channel link list
2. Iterator - Split multiple channels for individual processing
3. Apify Actor - Call YouTube Scraper
4. Filter - Filter videos without subtitles
5. Notion - Write to database

Using Iterator to process multiple channel links

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Step 1: Configure Channel Input

Use Make’s Basic Trigger with Iterator to input multiple channel links at once:

Steps:

1. Add Basic Trigger module
2. Input channel URL array
3. Add Iterator to split array

Important: URL format must include https:// or http://, otherwise transmission to Apify will fail.

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Step 2: Configure Apify Scraping

Control scraper behavior via JSON

Add Apify module in Make, configure YouTube Scraper Actor:

JSON Parameter Example:

{
  "startUrls": [
    {"url": "{{channel_url}}"}
  ],
  "maxResults": 20,
  "dateFilter": "thisWeek",
  "downloadSubtitles": true
}

Key Parameters:

• maxResults - Maximum scrape count
• dateFilter - Time filter (thisWeek/thisYear)
• downloadSubtitles - Whether to download subtitles

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Step 3: Configure Data Mapping

Map Apify data to corresponding Notion fields

Important: Before configuring Notion mapping, you must run the Apify module once completely to get sample data. Otherwise Make cannot recognize the data structure and subsequent steps won’t find mappable variables.

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Step 4: Handle Missing Subtitles

Set condition: Subtitles exist

Not all YouTube videos have subtitles. Without a filter, empty values written to Notion will cause workflow errors.

Solution:

1. Add Filter module
2. Set condition to: Subtitle field Exists
3. Only videos with subtitles continue processing

Subtitle Storage Method

Subtitle content is typically very long, exceeding Notion table property character limits.

Correct Approach:

• Cannot store in Text property
• Use Append a page content method
• Add subtitles as paragraph blocks in page body

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Two Practical Strategies

Strategy 1: Historical Data Deep Clean

Configuration:

• MaxResults: 500 or 1000
• dateFilter: thisYear or not set
• Run Method: Manual one-time

Purpose: Build a complete archive of a channel’s past videos in one go.

Strategy 2: Periodic Incremental Updates

Configuration:

• MaxResults: 20
• dateFilter: thisWeek
• Schedule: Every Sunday evening

Purpose: Low-cost automated tracking of latest updates, keeping knowledge base fresh.

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Important Notes

Common “pitfalls” in actual deployment:

1. URL format must be precise - Channel links must include https://, otherwise Apify errors

2. “Run once first” forced logic - Must run Apify first to get sample data before configuring Notion mapping

3. Missing subtitles cause crashes - Must set Filter to filter videos without subtitles

4. Notion cell character limit - Subtitle content must use Append Page Content to write to body

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Use Cases

Recommended For

• Content Creators - Monitor competitor channels or find content inspiration
• AI Application Developers - Need large amounts of video subtitle text as datasets
• Knowledge Management Enthusiasts - Build personalized video knowledge bases

May Not Suit

• Complete beginners with no JSON/API knowledge
• Users who just need simple video bookmarking (YouTube’s built-in feature suffices)

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FAQ

How many videos can I scrape?

Configure via MaxResults parameter - supports 20, 500, 1000, etc., depending on your Apify quota and needs.

What if a video has no subtitles?

You must set up a Filter to check if subtitles exist. Otherwise, empty values will cause the entire workflow to fail.

How to store long subtitle content?

Subtitles exceed Notion table property character limits. You must use the Append Page Content method to add them as paragraph blocks in the page body.

Does it support scheduled auto-updates?

Yes. Set it to run weekly with the thisWeek filter for incremental updates, keeping your knowledge base fresh at low cost.

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Next Steps

After mastering the basic workflow, you can try:

• Add AI summary module to auto-generate video summaries
• Integrate translation API to handle multilingual subtitles
• Add more channel monitoring
• Set up notification alerts for new videos

Feel free to leave comments if you have questions!