How do I connect Webhooks to Scrapernode?

Add your endpoint URL in Scrapernode's webhook settings. Scrapernode sends an HTTP POST with the full JSON payload when jobs complete. Verify delivery with a test scrape first.

What YouTube comments data fields are sent to Webhooks?

All 15 output fields from the YouTube Comments scraper are included: comment_id, comment_text, likes, replies, username, username_md5, and more. The full payload is sent as structured JSON — no fields are filtered out.

Can I schedule recurring YouTube scrapes to Webhooks?

Yes. Use the Scrapernode REST API to create scraping jobs programmatically on any schedule. Results are automatically delivered to Webhooks when each job completes.

How much does it cost to scrape YouTube comments into Webhooks?

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

What happens if the Webhooks delivery fails?

Scrapernode retries webhook deliveries with exponential backoff. Failed deliveries are logged and can be manually re-triggered from the job details page. Your scraped data is always available for download even if webhook delivery fails.

YouTubeWebhooks

How to Scrape YouTube Comments into Webhooks

Extract comments data from YouTube and deliver via Webhooks automatically

Step-by-step guide

Choose the YouTube Comments scraper

Navigate to the YouTube Comments 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 Webhooks connection

Add your endpoint URL in the Scrapernode webhook settings. Each completed job sends a POST request with the full JSON payload, including all output fields and metadata.

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 Webhooks

When the job completes, Scrapernode delivers the full JSON payload to your endpoint. Each record includes 15 structured fields like comment_id, comment_text, likes, replies. Parse the payload in your application and process the data as needed.

Cost per record

1 credit

Output fields

15 fields

Destination

Webhooks

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5

Comment Id

sample_comment_id

Comment Text

Great analysis! Would love to see a deeper dive on the retention metrics.

Likes

34,108

Replies

Username

@sarahchen

Username Md5

sample_username_md5

User Channel

sample_user_channel

Date

2025-12-15

Url

sample_url

Video Id

sample_video_id

Replies Value

sample_replies_value

Replies Without Names

sample_replies_without_names

User Id

sample_user_id

Mentioned Timestamps Minutes

sample_mentioned_timestamps_minutes

Mentioned Timestamps Seconds

sample_mentioned_timestamps_seconds

Data Dictionary

15 fields returned per record

Unique identifier for each comment (100.00% fill rate)

The text content of the comment (99.98% fill rate)

Number of likes received by the comment (100.00% fill rate)

Number of replies to the comment (99.97% fill rate)

Username of the commenter (99.95% fill rate)

MD5 hash of the username field (99.97% fill rate)

URL of the commenter's YouTube channel (100.00% fill rate)

Date when the comment was posted (100.00% fill rate)

Web address of the YouTube video where the comment was posted (100.00% fill rate)

Unique identifier for the YouTube video (97.47% fill rate)

Reply values (3.00% fill rate)

Sub-fields

authorTextReply author name

textTextReply text

dateTextReply date

likesNumberReply likes count

Replies without names (3.00% fill rate)

Sub-fields

textTextReply text without author name

dateTextReply date

likesNumberReply likes count

User ID of the commenter (97.19% fill rate)

Timestamps mentioned in the comment (minutes) (0.08% fill rate)

Timestamps mentioned in the comment (seconds) (0.08% fill rate)

Frequently Asked Questions

Common questions about How to Scrape YouTube Comments into Webhooks

Ready to connect YouTube data to Webhooks?

Start extracting youtube comments data and deliver via Webhooks in minutes.

Go to YouTube Comments scraper Browse all integration guides

No code requiredAuto-delivery to Webhooks15 data fields