How do I connect Make to Scrapernode?

Use Make's webhook trigger to receive data from Scrapernode. Copy the webhook URL from Make and paste it into Scrapernode's webhook settings for the scraper. Each completed job sends results automatically.

What YouTube channels data fields are sent to Make?

All 19 output fields from the YouTube Channels scraper are included: url, handle, handle_md5, banner_img, profile_image, name, and more. The full payload is sent as structured JSON — no fields are filtered out.

Can I schedule recurring YouTube scrapes to Make?

Yes. Use Make's scheduling features to trigger Scrapernode scrapes on a recurring basis via the REST API. You can also set up Make to process results as they arrive via webhooks.

How much does it cost to scrape YouTube channels into Make?

Each channels record costs 1 credit. Credits start at $9 for 3,000 credits (Starter plan). The Make integration itself is included free — no additional charges for data delivery.

What happens if the Make delivery fails?

Your scraped data is always stored in Scrapernode regardless of the integration status. If delivery to Make fails, you can re-trigger the sync or download results manually as CSV or JSON from the job details page.

YouTubeMake

How to Scrape YouTube Channels into Make

Extract channels data from YouTube and pipe into Make automatically

Step-by-step guide

Choose the YouTube Channels scraper

Navigate to the YouTube Channels scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.

Set up your Make connection

Create a new Make scenario with a Webhook trigger module. Copy the webhook URL into Scrapernode's webhook settings. Use Make's built-in JSON parser to map scraper fields to downstream modules like "Create Spreadsheet Row" or "Send Email".

Provide your YouTube input URLs

Paste the YouTube URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and content pages.

Launch the scraping job

Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.

Receive data in Make

When the job completes, Scrapernode sends the full results to your Make workflow. Each record includes 19 fields like url, handle, handle_md5, banner_img. Route the data to any downstream app — CRMs, databases, email tools, and more.

Cost per record

1 credit

Output fields

19 fields

Destination

Make

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5

Url

sample_url

Handle

sample_handle

Handle Md5

sample_handle_md5

Banner Img

sample_banner_img

Profile Image

sample_profile_image

Name

Sarah Chen

Subscribers

330,800

Description

sample_Description

Videos Count

1,000

Created Date

sample_created_date

Views

344,860

Details

sample_Details

Links

sample_Links

Identifier

sample_identifier

Discovery Input

sample_discovery_input

ACoAABcXYZ123

Has Podcast

Yes

Data Dictionary

19 fields returned per record

URL that links directly to the YouTube profile (100.00% fill rate)

Unique to each user (e.g., @name) (100.00% fill rate)

MD5 hash of the handle field (97.66% fill rate)

URL that links to the banner photo (43.10% fill rate)

URL that links to the profile picture (99.97% fill rate)

Profile name (99.97% fill rate)

How many subscribers the profile has (90.53% fill rate)

Brief descriptions or statements that users write to introduce themselves (47.89% fill rate)

How many videos the profile has (97.67% fill rate)

The date the profile was created (99.94% fill rate)

How many views the profile has (97.24% fill rate)

Profile details (22.81% fill rate)

Sub-fields

labelTextDetail label

valueTextDetail value

External websites that users may link to from their YouTube profiles (17.23% fill rate)

Sub-fields

titleTextLink title

urlTextLink URL

Identifier (99.88% fill rate)

Discovery input value (24.06% fill rate)

Sub-fields

keywordTextSearch keyword

Channel ID (99.88% fill rate)

Whether the channel has a podcast (99.90% fill rate)

Top videos from the channel (90.70% fill rate)

Sub-fields

urlTextVideo URL

titleTextVideo title

viewsNumberNumber of views

thumbnailTextVideo thumbnail URL

Frequently Asked Questions

Common questions about How to Scrape YouTube Channels into Make

Ready to connect YouTube data to Make?

Start extracting youtube channels data and pipe into Make in minutes.

Go to YouTube Channels scraper Browse all integration guides

No code requiredAuto-delivery to Make19 data fields